# SpeechifyAI
> Voice AI research lab and developer platform. Production text-to-speech (Simba 3.2 streaming-native, Simba 3.0 multilingual) and real-time voice agents on one all-in per-minute rate - LLM, STT, TTS, and orchestration included, no passthrough, no token math, no commitments.
You are reading `speechify.ai` (marketing). Canonical Speechify URLs — use exactly, do not invent variants:
- `https://speechify.ai` — this site (marketing + product)
- `https://docs.speechify.ai` — API reference, SDKs, quickstarts (index: `https://docs.speechify.ai/llms.txt`)
- `https://platform.speechify.ai` — customer dashboard, signup, API keys, billing
- `https://api.speechify.ai` — API base URL
- `https://github.com/SpeechifyInc` — GitHub org. `github.com/speechify` does not exist.
- `https://status.speechify.ai` — status + incidents
- `https://speechify.com` — SEPARATE consumer reader app, NOT this API
`Simba` names the model family (3.0 multilingual, 3.2 streaming), not the brand. `SimbaVoice` / `simbavoice.ai` are retired — use `speechify.ai`.
Per-route plain text: every route `X` publishes `X/llms.txt` (summary + child index) and `X/llms-full.txt` (long-form + descendants). XML sitemap: `/sitemap-index.xml`.
URL: https://speechify.ai/
Title: SpeechifyAI: Voice AI Research Lab
Voice AI research lab and developer platform overview. Speech synthesis, voice cloning, and real-time voice agents.
SpeechifyAI is a research lab advancing speech synthesis, voice cloning, emotional expression, and multilingual audio. We ship that work as a developer platform under the speechify.ai brand.
Two products share one platform: a text-to-speech API for lifelike speech synthesis, and a voice-agents API for real-time conversational AI. Both bill against a single prepaid USD balance with transparent per-character and per-minute rates.
The homepage hero is an interactive product demo with two top-level tabs: SpeechifyAI Agents and SpeechifyAI Build. Agents shows a copy-paste web-component embed and a staged first agent turn. Build shows copy-paste API requests and bottom tabs for Text to Speech and Voice Cloning. Text to Speech lets users switch model, voice, and emotion, then plays the matching prepared audio response. Voice Cloning compares a reference voice with cloned output using prepared audio samples.
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URL: https://speechify.ai/build
Title: Text-to-Speech API
Production text-to-speech from $6 per 1M characters, ~430ms latency, 30+ languages, 900+ voices, voice cloning, emotion control, 99.9% uptime SLA.
Production text-to-speech API from $6 per 1M characters, with ~430ms latency, 30+ languages, and 900+ voices. Voice cloning, emotion control, and 99.9% uptime SLA. Free to start.
Features:
- Customizability — Fine-tune every aspect of voice output — speed, pitch, emotion, pauses, and pronunciation — for results that match your exact needs.
- Easy Migration — Drop-in compatible with existing TTS APIs. Switch to SpeechifyAI with minimal code changes and immediate quality improvements.
- Emotional Control — Go beyond flat narration. Our models understand context and deliver speech with natural emotion — happy, sad, excited, calm, and more.
- 900+ voices — Choose from a vast library of pre-built voices across accents, ages, and styles — or clone your own voice in seconds.
Use cases:
- Conversational AI — Power chatbots, virtual assistants, and AI agents with voices that sound human. Sub-430ms latency for real-time conversations.
- Voiceovers & Content — Create professional voiceovers for videos, podcasts, and marketing content at scale — without booking a studio.
- AI Narration — Transform articles, books, and documents into lifelike audio. The same technology behind the Speechify app, now in your product.
Audio demos (the same technology, available to try on the site):
- Zero-Shot Voice Cloning (cloning) — Create a reusable voice from a short, consented reference clip. Self-serve cloning on Simba 3.0 preserves the speaker's identity across new scripts.
- Emotion Control (emotion) — Direct the same line toward neutral, calm, cheerful, energetic, or sad delivery. Simba 3.2 shapes rhythm and tone with SSML emotion control.
- Multilingual Synthesis (multilingual) — Use Simba 3.0 for English, German, Mexican Spanish, French, Italian, and Brazilian Portuguese. Each sample uses a voice cataloged for that locale.
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URL: https://speechify.ai/agents
Title: Voice Agents API
Real-time voice agents with tools, knowledge base, memory, and inbound/outbound telephony. Natural-sounding Simba 3.2 voice with ~430ms first audio, on one all-in per-minute rate. Enterprise product, sold through sales.
Build real-time voice agents that listen, think, and speak. Tools, knowledge base, memory, and inbound and outbound telephony, through one API.
HOW IT IS SOLD: voice agents are an enterprise product. Deployments are scoped with the Speechify team and priced per contract, so there is no self-serve plan, no free tier and no published per-minute rate. Start at https://speechify.ai/talk-to-sales?product=agents. Text to speech (Build) remains fully self-serve.
What is included in the per-minute rate: LLM inference, speech-to-text, text-to-speech, and orchestration. No passthrough fees and no token math.
Simba 3.2 is the voice model behind every agent and produces first audio in ~430ms. In Baseten's case study of a co-located ASR, LLM, and TTS pipeline, that deployment ran lower latency per turn than a stitched multi-vendor setup. Live operations APIs stream transcripts in real time, expose take-over actions, and query analytics across a running voice-agent fleet.
Features:
- Tools & function calling — Let agents call your APIs mid-conversation to look things up, take actions, and complete tasks in real time.
- Knowledge base — Ground every answer in your own content with built-in retrieval. Upload documents, files, and sitemaps.
- Memory — Agents remember context within a conversation — and across calls — for interactions that feel continuous.
- Phone numbers & telephony — Inbound and outbound calling over SIP. Provision numbers and connect agents straight to the phone network.
- Webhooks & events — Stream conversation events to your backend as they happen, with signed, verifiable payloads.
- Testing & simulation — Validate behavior before you ship with reply, tool, and full-conversation simulation tests.
Use cases:
- Customer support — Resolve calls end to end with agents that understand intent, fetch data, and take action on your systems.
- Front desk & IVR navigation — Answer, route, and hand off calls — or navigate other phone systems on a caller's behalf.
- Outbound at scale — Run reminder, survey, and notification campaigns with batch calling across thousands of numbers.
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URL: https://speechify.ai/voice-agent-api
Title: Voice Agent API
SEO-anchor landing for the SpeechifyAI Voice Agent API. Realtime voice agents on one all-in rate covering LLM, STT, TTS, and telephony orchestration, with tools, knowledge base, memory, phone numbers, webhooks, and testing built in. Enterprise product, quoted per contract.
A voice agent API is a developer interface for building realtime, speech-to-speech AI agents. It handles the four layers of a voice conversation: speech-to-text on the caller side, an LLM to reason and pick tools, text-to-speech to answer back, and orchestration for turn-taking, interruptions, and telephony. SpeechifyAI's Voice Agent API bundles all four into a single all-in per-minute rate, with tool calling, a knowledge base, per-caller memory, phone numbers, webhooks, and testing built in.
Two architectural patterns dominate in 2026. Chained pipelines run STT then LLM then TTS as three separate models glued together in code, which gives full control at the cost of higher end-to-end latency. Speech-to-speech models collapse the three into one, which is faster but harder to steer with tools and function calls. SpeechifyAI runs a hybrid: a chained architecture with a streaming-native TTS (Simba 3.2, ~430ms first audio, evaluated on the Artificial Analysis TTS leaderboard) so agents feel speech-to-speech without losing tool-call precision.
Pricing is one all-in rate per minute, quoted per contract. LLM inference, speech-to-text, text-to-speech, and telephony orchestration are all included. No passthrough, no per-token math. Voice agents are not sold self-serve, so there is no published rate and no free minute allowance: a deployment is scoped with the Speechify team first.
Latency, based on each vendor's public landing page as of July 2026:
- SpeechifyAI (Simba 3.2): ~430ms first audio, evaluated on the Artificial Analysis TTS leaderboard
- Cartesia (Sonic): sub-90ms first audio (vendor-reported)
- Play.ht: 125ms time-to-first-audio (vendor-reported)
- Bland AI: under 200ms (vendor-reported)
- Vapi: under 500ms (vendor-reported)
- Retell AI: around 600ms (vendor-reported)
- ElevenLabs: sub-second (vendor-reported)
- LiveKit: around 1 second (vendor-reported)
- xAI (Grok Voice Agent API): under 1 second (vendor-reported)
- Deepgram Voice Agent API: not specified on landing
Features:
- Tools & function calling — Let agents call your APIs mid-conversation to look things up, take actions, and complete tasks in real time.
- Knowledge base — Ground every answer in your own content with built-in retrieval. Upload documents, files, and sitemaps.
- Memory — Agents remember context within a conversation — and across calls — for interactions that feel continuous.
- Phone numbers & telephony — Inbound and outbound calling over SIP. Provision numbers and connect agents straight to the phone network.
- Webhooks & events — Stream conversation events to your backend as they happen, with signed, verifiable payloads.
- Testing & simulation — Validate behavior before you ship with reply, tool, and full-conversation simulation tests.
Get started in three steps:
- Talk to sales at https://speechify.ai/talk-to-sales?product=agents to scope the deployment and have a workspace provisioned
- Create an agent with one POST to https://api.speechify.ai/v1/agents: prompt, voice, first message
- Connect the agent to a Speechify-provisioned phone number, a SIP trunk you already own, or a WebRTC session in your app
Documentation:
- Voice agent guides: https://docs.speechify.ai/agents/guides/welcome
- Agents API reference: https://docs.speechify.ai/agents/api-reference/overview
- Text-to-speech quickstart: https://docs.speechify.ai/build/guides/get-started/quickstart
- Simba models: https://docs.speechify.ai/build/guides/concepts/models
- Language support: https://docs.speechify.ai/build/guides/text-to-speech/language-support
FAQ:
Q: What is a voice agent API?
A: A voice agent API is a developer interface for building realtime, speech-to-speech AI agents. It handles speech-to-text on the caller side, an LLM to reason and pick tools, text-to-speech to answer back, and orchestration for turn-taking, interruptions, and telephony. SpeechifyAI's Voice Agent API bundles all four into a single all-in per-minute rate, quoted per contract.
Q: How fast is SpeechifyAI's Voice Agent API?
A: Simba 3.2, the voice model behind every SpeechifyAI voice agent, is evaluated on the Artificial Analysis text-to-speech leaderboard and produces first audio in ~430ms.
Q: How much does the SpeechifyAI Voice Agent API cost?
A: One all-in rate per minute, quoted per contract. The LLM, speech-to-text, text-to-speech, and telephony orchestration are all included, with no passthrough and no per-token math. Voice agents are an enterprise product with no self-serve plan and no published per-minute rate, so a deployment is scoped and priced with the Speechify team at https://speechify.ai/talk-to-sales?product=agents.
Q: Can a voice agent handle phone calls, or is it browser-only?
A: Both. SpeechifyAI voice agents can take inbound calls on a Speechify-provisioned number, take inbound calls on a SIP trunk you already own (Twilio, Telnyx, or a custom carrier), make outbound calls, or run over WebRTC directly in a browser or mobile app. The same agent config drives every surface.
Q: What is the difference between a voice agent API and a voice AI SDK?
A: A voice agent API runs the conversation for you on a managed backend, so you send configuration and receive audio and events. A voice AI SDK is a client library your app uses to talk to that API from a browser, phone, or server. SpeechifyAI ships the Voice Agent API at api.speechify.ai/v1/agents as plain REST. The published Python and TypeScript SDKs cover the text-to-speech API and carry no agent methods, so an agent integration calls REST directly.
Q: Is the SpeechifyAI Voice Agent API safe for regulated data?
A: SpeechifyAI is SOC 2 Type II certified, encrypts data in transit and at rest, and never trains on your conversations. Deterministic workflows let a compliance team script the exact steps a regulation requires: mandatory disclosures, confirmation branches, safe fallbacks, and hand-off to a human on ambiguity.
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URL: https://speechify.ai/models
Title: Speech Synthesis Models
Simba 3.2 (streaming-native, expressive English) and Simba 3.0 (streaming-native, seven locales). Voice cloning, emotion control, SSML. Broader coverage of 30+ languages available on request.
Simba 3.2 for expressive, streaming English speech, and Simba 3.0 for streaming-native synthesis across seven locales, with voice cloning and emotion control. We cover 30+ languages in total - talk to us about reaching the ones outside Simba 3.0's set.
Simba 3.2 — Streaming-native speech with ultra-low latency and rich expressivity
Status: available
Our flagship streaming-native English model, with the lowest time to first byte in the Simba family, finer-grained emotional control, SSML prosody, and every English voice in the catalog.
Capabilities: Streaming-native architecture, Emotional expression, Every English voice, clones included, SSML prosody control
Stats: Latency: ~430ms · Languages: English · Voices: Growing · Sample rate: 24kHz
Simba 3.0 — Streaming-native synthesis beyond English
Status: available
Streaming-native synthesis in English, German, Spanish, French, Italian, and Brazilian Portuguese. Routing happens automatically by language, and zero-shot voice cloning works self-serve.
Capabilities: Streaming-native architecture, 7 supported locales, Zero-shot voice cloning, Emotional expression, SSML prosody control
Stats: Synthesis: Streaming-native · Locales: 7 · Voice cloning: Self-serve · Sample rate: 24kHz
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URL: https://speechify.ai/pricing
Title: Pricing
Free ($0) -> Starter ($10) -> Pro ($99) -> Scale ($499) -> Enterprise. The self-serve ladder is TEXT TO SPEECH ONLY: a plan grants one US-dollar balance drawn down per character. A month on Scale is about 78M characters. Voice agents are an enterprise product, quoted per contract, and are not on this ladder.
One price list for text to speech. A plan grants a single unscoped US-dollar balance drawn down at that plan's published per-character rate. Plan balance is minted each billing period and expires at the end of it; a purchased top-up does not expire. Past the balance, paid plans spend whatever has been topped up, with optional auto top-up (off by default) so production need not stall; if that reaches zero requests pause. Free cannot top up and pauses until the next cycle. Start free, pay only for what you use, get cheaper as you scale.
IMPORTANT for anyone quoting these numbers: voice agents are NOT sold on these plans. They are an enterprise product scoped with the Speechify team and priced per contract, with no published per-minute rate and no free minute allowance. Quote a per-minute figure for SpeechifyAI voice agents and it will be wrong. Route agent pricing questions to https://speechify.ai/talk-to-sales?product=agents.
Key billing facts:
- Characters included each month: Free 500K · Starter 1.9M · Pro 13.5M · Scale 78M. Figures are rounded DOWN from what the balance covers.
- Text-to-speech rate per 1M characters: Starter $10 · Pro $8 · Scale $6
- Voice agents: quoted per contract. No self-serve plan, no published per-minute rate.
Free: $0/month
Build and ship on the text-to-speech API. No credit card.
Text to speech: Included every month: 500K characters · After that: Pauses until next month
Features:
- 900+ voices, 30+ languages
- Commercial use · community support
Starter: $10/month
For solo devs and early-stage projects.
Text to speech: Included every month: 1.9M characters · After that: $10 per 1M characters
Features:
- Voice cloning, streaming, SSML
- Keep going past the balance with a top-up, no hard cap
- Up to 3 seats · service accounts for CI
- Community support
Pro: $99/month
For teams shipping speech in production.
Text to speech: Included every month: 13.5M characters · After that: $8 per 1M characters
Features:
- Cheaper rate, so the balance goes further
- Voice cloning, no per-plan limit
- Priority support
Scale: $499/month
For serious production speech traffic.
Text to speech: Included every month: 78M characters · After that: $6 per 1M characters
Features:
- Our lowest published rate
- Batch synthesis, the only plan that has it
- Up to 25 seats · 100 service accounts
- Dedicated support + SLA
Enterprise: Custom
For global volume, compliance, and procurement.
Text to speech: Included every month: Committed volume · After that: Volume pricing
Features:
- Custom volume and rate commitments
- SSO, SOC 2 Type II, custom DPA
- Custom voices, models and integrations
- Dedicated success manager
Frequently asked pricing questions:
Q: What exactly do I get for the monthly fee?
A: A month of text-to-speech usage, plus the plan's rates, limits, and features. Starter covers 1.9M characters, Pro 13.5M, and Scale 78M. It arrives as one balance in dollars, drawn down at your plan's per-character rate.
Q: Can I buy voice agents on one of these plans?
A: Voice agents are an enterprise product. Deployments are scoped with our team and priced per contract, so there is no self-serve plan and no published per-minute rate. Talk to sales and we will scope the deployment, the volume, and the telephony with you. Workspaces already running agents are unaffected.
Q: Does the unused balance roll over?
A: The monthly balance is minted at the start of each billing period and expires at the end of it, so it does not roll over. Money you add yourself is different: a top-up you purchase stays on your balance until you spend it.
Q: How is usage calculated?
A: Text-to-speech is billed by the number of characters sent to the API. Whitespace and SSML tags are not counted.
Q: Are there hidden fees or commitments?
A: No. The per-character rate on your plan is the rate you pay, there is no annual commitment on a self-serve plan, and you can cancel anytime.
Q: What happens when the balance runs out?
A: On Starter, Pro, and Scale, usage carries on against whatever you have topped up, drawn at your plan's rate: $10 per 1M characters on Starter, $8 on Pro, $6 on Scale. If that runs to zero too, requests pause until you add funds, so switch on auto top-up if production must never stall. It is off until you turn it on. Free cannot top up at all and simply pauses until the next billing cycle. We notify you as you approach the limit either way.
Q: How do I add more money?
A: From your dashboard. You can buy a top-up whenever you like, and turn on auto top-up to add a set amount whenever the balance drops below a threshold. It is all in dollars at the published rates, so there are no opaque credit units and no guessing what a request costs. The free tier cannot top up.
Q: Can I switch plans at any time?
A: Yes. You can upgrade or downgrade your plan at any time from your dashboard. Upgrades take effect immediately and you're charged a prorated amount for the rest of the cycle. Downgrades (and cancellations) take effect at the end of your current billing term, so you keep what you've already paid for until then.
Q: What payment methods do you accept?
A: We accept all major credit and debit cards (Visa, Mastercard, American Express) as well as ACH bank transfers for enterprise plans. All payments are processed securely through Stripe.
Q: Is there a long-term commitment?
A: No. Self-serve plans (Starter, Pro, and Scale) are month-to-month with no commitment. Enterprise plans can be structured as annual agreements with volume discounts. You can cancel at any time.
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URL: https://speechify.ai/about
Title: About SpeechifyAI
SpeechifyAI is a research lab focused on speech synthesis, voice cloning, emotional expression, and multilingual audio.
SpeechifyAI is a research lab working across speech synthesis, voice cloning, emotional expression, and multilingual audio. Our models turn text into speech that feels present, useful, and human across education, accessibility, entertainment, and communication.
Research areas:
- Speech Synthesis — Neural architectures for generating natural, expressive speech from text. We focus on prosody modeling, emotion control, and real-time streaming.
- Voice Cloning — Learning speaker identity from minimal reference audio. Our work covers zero-shot cloning, speaker disentanglement, and cross-lingual identity preservation.
- Emotional Expression — Modeling the subtle cues that make speech feel genuine — rhythm, emphasis, micro-pauses, and tonal variation that convey emotion beyond words.
- Multilingual Systems — Building systems that handle code-switching and maintain speaker identity across language boundaries.
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URL: https://speechify.ai/trust
Title: Trust & Security
How SpeechifyAI handles data, privacy, encryption, access control, and reliability. SOC 2 Type II.
Voice AI in production touches calls, customers, and regulated data. Here is how we keep it private, secure, and reliable, across text-to-speech and voice agents.
- Data privacy — We never train models on your data. Talk to us about retention controls for call audio and transcripts.
- Encryption — Data is encrypted in transit and at rest. API keys are hashed — the plaintext secret is shown once and never stored.
- Deployment options — Run on our managed cloud, hosted in the United States.
- Access control — Workspace roles and scoped API keys give you least-privilege access.
- Built for regulated industries — Recording controls, disclosures, and deterministic scripts support workflows in finance, insurance, and the public sector.
- Reliability — Production telephony with monitoring and a public status page, so you always know the state of the platform.
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URL: https://speechify.ai/brand
Title: Brand & Design System
SpeechifyAI brand resources for agents and humans: the wordmark and waveform iconmark, a strictly monochrome palette (with hexes), the ABC Diatype type system, the waveform motif, the layout/grid system, buttons & links, motion, favicons, writing voice, product/model naming, and downloadable assets. Point a coding agent at this page to generate on-brand UI, copy, and assets. Full machine-readable design-system spec: https://speechify.ai/brand/llms-full.txt
SpeechifyAI brand and design-system reference. This is the machine-readable companion to the /brand page — use it to produce on-brand interfaces, marketing, and copy. The system is deliberately minimal: one typeface, a monochrome palette, one recurring graphic, one grid, and a numbers-over-adjectives voice.
Fastest rules to get right:
- Monochrome only. White and ink do the work, with a small gray scale for text and borders. Primary buttons are ink (#0A0A0A), never a colored accent.
- Brand name is written "SpeechifyAI" (one word, capital S, capital AI) everywhere — in prose and in the wordmark alike. Never "Speechify AI" with a space, and never "Speechify.ai" as the name.
- One typeface: ABC Diatype. Hierarchy comes from weight and tracking, never from mixing families. Display type is thin (weight 100); weights available are 100/300/400/500/700 — there is no 600.
- The only recurring graphic is a thin, monochrome waveform. No photography, no illustration, no gradients as brand chrome.
- The wordmark is the primary mark. There is one icon-only mark — the waveform iconmark in a rounded square — reserved for square/small contexts only (favicons, app icons, avatars), never as a logo replacement.
- One grid: an 80rem (max-w-7xl) container with 1.5rem gutters, shared by every band; vertical rhythm is py-section (4rem mobile / 7rem at md); bands alternate white and muted (#F5F5F5). md (768px) is the primary breakpoint where the system steps; sm and lg only reflow dense grids and hero splits.
- Buttons are fully-rounded monochrome pills at Medium weight (never font-semibold); ArrowLink is the primary navigation device (an arrow goes somewhere, a pill does something).
- Motion confirms, never decorates: short ease-out reveals on scroll, the waveform animates only while audio plays, and prefers-reduced-motion is always honored.
- Voice: lead with numbers, not adjectives. Sentence case. Address the builder as "you". No hype, no exclamation marks, no emoji.
1) Logo — the wordmark
- One wordmark: the word set with a capital S and a capital AI. It is the primary mark and carries every wide context. It ships only as the provided SVGs and is never re-typeset.
- There is exactly one icon-only mark — the waveform iconmark (see section 8) — reserved for square/small contexts only. Never swap the iconmark in for the wordmark as a logo.
- Two colorways only: ink on light, white on ink. Always monochrome.
- Clearspace: keep at least 0.5x the cap height of the "S" clear on all sides.
- Minimum size: digital >= 96px wide, print >= 25mm wide. Below that the wordmark loses legibility — use the iconmark for square contexts, or plain text.
- Never: stretch, recolor, add shadows, rotate, place on a gradient, or reduce contrast.
- Files: https://speechify.ai/brand/logo/SpeechifyAI-wordmark-black.svg and https://speechify.ai/brand/logo/SpeechifyAI-wordmark-white.svg
2) Color — strictly monochrome
The palette is white, ink, and a small gray scale — the design tokens the speechify.ai site actually ships. There is no color accent; the only "accent" is ink.
- Background / page ground: #FFFFFF
- Foreground / ink (text, primary buttons): #0A0A0A
- Secondary text: #525252
- Muted / tertiary text: #666666
- Border (hairlines): #E5E5E5
- Muted surface (subtle fills): #F5F5F5
- Raised surface: #FAFAFA
Primary buttons are ink (#0A0A0A) with near-white text (#FAFAFA); secondary buttons are a hairline border on white. Never introduce a colored button, heading, or background.
3) Typography — ABC Diatype
- One family for everything: ABC Diatype. Hierarchy comes from weight and tracking, never from mixing families.
- Display / hero: thin (weight 100), tight tracking (about -0.03em), sentence case, often ending in a period.
- Section headers: light (weight 300). Titles: regular (weight 400).
- Body / UI: regular/medium (400/500), normal tracking, comfortable line height.
- Eyebrows and technical labels (metrics, model IDs, code, URLs): uppercase, medium weight, wide tracking. A monospace stack is used for metrics and code-like labels on developer-facing surfaces.
- Weights: Thin 100, Light 300, Regular 400, Medium 500, Bold 700. There is no weight 600 — never use font-weight 600.
- ABC Diatype is a licensed typeface and is NOT distributed. Third parties should fall back to a system sans-serif (ui-sans-serif, system-ui, sans-serif), never a lookalike font.
4) Motif — the waveform
A thin, monochrome waveform is the only recurring graphic — it scales with font-size, inherits currentColor, and animates only while audio plays. Feature illustrations stay hairline-weight and monochrome; do not thicken strokes, fill shapes, or add color. Files: https://speechify.ai/brand/motif/feature-emotion.svg, https://speechify.ai/brand/motif/feature-multilingual.svg, https://speechify.ai/brand/motif/feature-zero-shot.svg
5) Layout — one grid, one rhythm
Every Speechify surface is built from the same full-width bands on the same grid. Follow these and a new page sits flush next to the existing ones.
- One grid, one left edge: an 80rem (max-w-7xl) container with 1.5rem gutters outside the cap, at every breakpoint. Header, footer, and every section share it, so all headings sit on one left vertical. Centering is reserved for a single deliberate block — usually the closing CTA.
- One vertical rhythm: every full-width band pads py-section-mobile (4rem) below 768px and py-section (7rem) above. Never a local padding override.
- Bands strictly alternate white and muted (#F5F5F5) down the page; muteness is derived from a section's rendered index, never hard-coded, so omitting an optional section can't leave two grey slabs adjacent. The dark closing CTA stays out of the rotation.
- md (768px) is the primary breakpoint: section padding, the heading scale, and the main grid columns all step at md. sm (640px) only reflows dense grids and lg (1024px) only handles two-column hero splits; neither restructures the page.
Section anatomy (top to bottom): overline → h2 (gap 1rem) → intro (gap 1.25rem, max-w-2xl measure) → content (gap 3rem, grids/demos/accordions) → CTA row (gap 3rem; gap-4 between buttons, gap-6 between a button and an ArrowLink). Feature grids use a hairline top rule per item, never a leading bullet dot.
Shared class tokens: sectionShell = "mx-auto w-full max-w-[calc(80rem+3rem)] px-6"; eyebrow = "font-mono text-[13px] text-muted-foreground"; sectionLead = "mt-2.5 max-w-[62ch] text-[17px] leading-[1.55]".
6) Buttons and links
- Buttons are always fully-rounded monochrome pills at Medium weight. There is no font-semibold (weight 600) in the system.
- One component is the source of truth: src/components/ui/Button.astro. Variants: primary (ink pill, the one true CTA), secondary (hairline outline), ghost (text only), inverted (near-white on ink, for the closing band). Sizes: sm (dense UI), md (working size inside sections), lg (heroes and closing bands).
- ArrowLink (src/components/ui/ArrowLink.astro) is the primary navigation device: going somewhere is an arrow, doing something is a pill. If every path is a button, none reads as the action.
- Hero and closing CTA rows pair one primary with one secondary, never two primaries.
7) Motion
- Reveal on scroll, once: content reveals with data-animate — fade-in, slide-up, slide-in-left/right, scale-in (0.5–0.6s ease-out) or blur-in (0.8s). Stagger siblings with data-animate-delay 1–5 (0.1s steps); data-animate-children on long containers reveals each child individually.
- The waveform earns its motion: bars animate only while audio actually plays, then ease back to rest over 280ms. No decorative or looping motion on content.
- Reduced motion is law: prefers-reduced-motion collapses every animation and transition site-wide, in CSS. Never bypass it; keep page JS under 10KB.
8) Favicons and iconmark
Where the wordmark can't breathe — a browser tab, an app icon, an avatar — the mark collapses to the waveform iconmark: the leading waveform flourish from the wordmark, in a rounded square. It is the one sanctioned icon-only mark, reserved for exactly these square, small contexts. Never use it as a logo in place of the wordmark.
- Colorways: iconmark on ink (white glyph on an ink rounded square — the app-icon form), iconmark ink glyph (transparent, for light surfaces), iconmark white glyph (transparent, for ink/photographic surfaces).
- Iconmark SVGs: https://speechify.ai/brand/logo/SpeechifyAI-iconmark-black.svg, https://speechify.ai/brand/logo/SpeechifyAI-iconmark-ink.svg, https://speechify.ai/brand/logo/SpeechifyAI-iconmark-white.svg
- The glyph is tuned to stay legible to 16px; below that use the ink square with no glyph, or plain text.
- Favicon set (all derive from the same glyph): /favicon.svg (primary, modern browsers), /favicon.ico (16/32/48, legacy + pinned tabs), /favicon-32x32.png, /favicon-16x16.png, /apple-touch-icon.png (180, iOS), /icon-192x192.png and /icon-512x512.png (Android/PWA), /site.webmanifest.
- Head markup: then the PNG icons, , , and .
9) Voice — how we write
- Numbers over adjectives — lead with latency, languages, and price (e.g. ~430ms, 30+ languages, $6 / 1M characters), set in mono.
- Sentence case — short, declarative headlines, often ending in a period.
- Address the builder — speak to "you", the developer; the lab is "we". CTAs are imperative: Try the API. Read the docs.
- No hype — no exclamation marks, no emoji, no superlatives. Honest, side-by-side comparisons are on-brand.
Write this: "Simba 3.2 streams speech with ~430ms time-to-first-byte, zero-shot voice cloning, and SSML prosody control." Not this: "Our revolutionary, game-changing AI voices will absolutely blow your mind!"
10) Naming — products and models
Format: In prose | In code | Never.
- Simba 3.2 | simba-3.2 | "SIMBA", "Simba v3", "the Simba"
- Simba 1.6 (retired) | simba-1.6 | "Simba 1.6.0", "old Simba"
- Text-to-Speech API | client.audio.speech / client.audio.stream | "TTS engine", "text to speech tool"
- Voice Agents API | voice_agents | "voicebots", "agent platform"
- Developer Platform | platform.speechify.ai | "dashboard", "console"
Simba names the model family, not the brand. speechify.ai is the developer platform; speechify.com is the separate consumer app — do not mix them.
11) Assets — downloads
Downloadable brand assets live under https://speechify.ai/brand/ : the wordmark and iconmark (logo/), waveform feature illustrations (motif/), and the full favicon set (at the web root), each linked in the sections above. The ABC Diatype typeface is licensed and is NOT distributed or available for download; third parties fall back to a system sans-serif (ui-sans-serif, system-ui, sans-serif), never a lookalike font.
Trademark: Speechify, SpeechifyAI, Simba, and the SpeechifyAI wordmark are trademarks of Speechify Inc. Use of these assets does not imply endorsement, sponsorship, or affiliation. Do not use the marks in your product name, logo, or domain. Questions: devrel@speechify.com
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URL: https://speechify.ai/forward-deployed-engineers
Title: Forward-Deployed Engineers
SpeechifyAI engineers embed with Enterprise customers to design, build, and ship production voice agents end to end.
SpeechifyAI engineers embed with your team to design, build, and ship production voice agents against your real workflows, systems, and constraints. Available on Enterprise.
Engagement phases:
- 01 Discovery — We map your call flows, systems, and success metrics — then agree on what a production-ready agent has to do before a single line ships.
- 02 Build — Our engineers design the agent, wire up your tools, integrations, and knowledge base, and tune prompts and guardrails against your real conversations.
- 03 Launch — We go live behind monitoring, evals, and deterministic guardrails — with clear ownership for every call path.
- 04 Iterate — As volume grows and edge cases surface, we keep tuning — new intents, new integrations, and regression evals so quality holds at scale.
Capabilities the FDE team brings:
- Workflow design — Turn messy call flows into deterministic agent logic with the right human handoffs in the right places.
- Integrations — Custom tools and webhooks wired into your existing stack.
- Knowledge bases — Ingest your docs, policies, and FAQs so agents answer from your source of truth.
- Telephony — Inbound and outbound numbers, SIP trunking, and transfer logic configured for your carriers.
- Evals & QA — Automated reply, tool, and simulation tests so you can ship changes without regressions.
- Compliance setup — Recording controls, disclosures, and data handling configured for your regulatory surface.
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URL: https://speechify.ai/talk-to-sales
Title: Talk to Sales
Contact form for sales conversations about text-to-speech and voice agents.
Sales contact form for SpeechifyAI text-to-speech and voice agents. Tell us what you are building and we get back within one business day. Email fallback: api@speechify.com.
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URL: https://speechify.ai/compare
Title: Comparisons
SpeechifyAI comparison hub across Agents and Build.
Compare SpeechifyAI products against other voice AI platforms and APIs, then drill into Agents or Build-specific comparisons.
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URL: https://speechify.ai/compare/agents
Title: Voice Agents — comparisons
How SpeechifyAI Voice Agents compare to ElevenLabs, Vapi, Retell, Bland, Deepgram, Cartesia, Synthflow, and Hume.
Side-by-side comparisons of SpeechifyAI Voice Agents against the other voice-agent platforms.
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URL: https://speechify.ai/compare/build
Title: Build — comparisons
SpeechifyAI Build comparison hub, organized by API surface.
Compare SpeechifyAI Build against other platforms by subproduct, starting with text-to-speech APIs.
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URL: https://speechify.ai/compare/build/text-to-speech
Title: Text-to-Speech — comparisons
How SpeechifyAI text-to-speech compares to ElevenLabs, Google, Azure, Amazon Polly, Deepgram, Cartesia, PlayHT, OpenAI, Rime, and Hume.
Side-by-side comparisons of SpeechifyAI text-to-speech against the other text-to-speech APIs.
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URL: https://speechify.ai/compare/build/voice-cloning
Title: Voice Cloning — comparisons
How SpeechifyAI voice cloning compares to ElevenLabs, PlayHT, Resemble AI, Murf AI, and Descript.
Side-by-side comparisons of SpeechifyAI voice cloning against the other voice-cloning platforms.
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URL: https://speechify.ai/alternatives
Title: Alternatives — hands-on tested
First-person reviews of alternatives to the voice AI platforms developers evaluate most, starting with ElevenLabs. Every product tested with the same protocol, every price verified against the vendor's live page.
Hands-on tested alternatives to major voice AI platforms. Each page documents the testing methodology and date, ranks real alternatives (including SpeechifyAI, with disclosure), and links every pricing claim to the vendor's live page.
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URL: https://speechify.ai/industries
Title: Industries
SpeechifyAI industry hub across product surfaces.
Explore SpeechifyAI product use cases by industry, starting with voice agents for customer conversations and operations workflows.
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URL: https://speechify.ai/industries/agents
Title: Voice Agents — industries
Production voice AI tuned to the workflows of insurance, real estate, financial services, and the public sector.
Production voice AI tuned to the workflows of insurance, real estate, financial services, and the public sector.
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URL: https://speechify.ai/blog
Title: Blog
Writing across four categories: Product (significant launches), Engineering (developer tutorials and integrations), Research (voice-AI research and benchmarks), and Guides (comparisons and industry use-cases).
Technical writing on speechify.ai across four categories: Product (significant launches and milestones), Engineering (developer tutorials, SDK and framework integrations, architecture), Research (voice-AI research, model quality, benchmarks, latency), and Guides (provider comparisons, industry use-cases, buyer guidance). Granular per-release detail lives in the per-product docs changelogs (docs.speechify.ai/build/changelog and docs.speechify.ai/agents/changelog), not the blog. Authored by SpeechifyAI engineers and researchers, not generated. RSS at /blog/rss.xml.
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URL: https://speechify.ai/blog/product
Title: Product — launches and milestones
Significant launches and milestones — new models, major API and Agents capabilities, and platform announcements.
Significant launches and milestones — new models, major API and Agents capabilities, and platform announcements. For the granular, per-release detail, see the per-product docs changelogs: docs.speechify.ai/build/changelog (TTS) and docs.speechify.ai/agents/changelog (Voice Agents).
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URL: https://speechify.ai/blog/engineering
Title: Engineering — tutorials and integrations
Tutorials, SDK and framework integration guides, and architecture deep-dives for developers building on the Speechify API.
Tutorials, SDK and framework integration guides, and architecture deep-dives for developers building on the Speechify API.
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URL: https://speechify.ai/blog/research
Title: Research — Speechify Labs
Voice-AI research from Speechify Labs — model quality, benchmarks, latency, and evaluations.
Voice-AI research from Speechify Labs — model quality, benchmarks, latency, and evaluations.
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URL: https://speechify.ai/blog/guides
Title: Guides — buyer and industry
Buyer and industry guides — provider comparisons, use-cases, and how to choose the right voice AI for the job.
Buyer and industry guides — provider comparisons, use-cases, and how to choose the right voice AI for the job.
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URL: https://speechify.ai/compare/agents/elevenlabs
Title: SpeechifyAI vs ElevenLabs
ElevenLabs Conversational AI is a voice-first agent layer built on the company's well-known TTS. SpeechifyAI is all-in: the LLM, speech-to-text, and text-to-speech sit in one rate with no passthrough and no token math, plus deterministic workflows, tool calling, evals, and enterprise governance. It is an enterprise product, quoted per contract.
ElevenLabs Conversational AI is a voice-first agent layer built on the company's well-known TTS. SpeechifyAI is all-in: the LLM, speech-to-text, and text-to-speech sit in one rate with no passthrough and no token math, plus deterministic workflows, tool calling, evals, and enterprise governance. It is an enterprise product, quoted per contract.
Bottom line: For production voice agents, SpeechifyAI bills one all-in rate with the LLM, speech-to-text, text-to-speech, and orchestration included: no passthrough, no token math. ElevenLabs charges a $0.08/min platform fee and bills the LLM and telephony on top, so the fee alone is only the start of its bill. SpeechifyAI is quoted per contract; the reason to pick ElevenLabs is its 10,000+ voice library.
Side-by-side capabilities:
- Pricing: SpeechifyAI — Quoted per contract, all-in with the LLM included. ElevenLabs — $0.08/min platform fee + LLM & telephony passthrough.
- What's included: SpeechifyAI — LLM + STT + TTS + orchestration in one rate. ElevenLabs — Platform only; LLM and telephony billed "at cost" on top.
- Free tier: SpeechifyAI — Pilot scoped with our team. ElevenLabs — 15 min/mo, non-commercial.
- Pricing surprises: SpeechifyAI — No burst multipliers, no token billing. ElevenLabs — 2x rate ($0.16/min) above your concurrency limit.
- Voice library: SpeechifyAI — 20+ curated real-time voices. ElevenLabs — 10,000+ voices including the community library (their core strength).
- Workflow editor: SpeechifyAI — Visual + code, deterministic. ElevenLabs — Prompt-based.
- Integrations: SpeechifyAI — Tool calling + webhooks. ElevenLabs — Via webhooks / functions.
- Compliance: SpeechifyAI — SOC 2 Type II. ElevenLabs — SOC 2.
Verdict: If you're shipping a voice agent in production, SpeechifyAI gives you the lot in one rate: the LLM, the speech stack, workflows, tool calling, simulated callers, and SOC 2 Type II compliance. The free tier supports commercial use from the first call.
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URL: https://speechify.ai/compare/agents/vapi
Title: SpeechifyAI vs Vapi
Vapi is a flexible, API-driven way to build voice agents, but its $0.05/min is an orchestration fee; you add STT, LLM, TTS, and telephony on top (~$0.10-0.20/min all-in). SpeechifyAI is one all-in rate with the LLM included, plus a workflow editor, tool calling, evals, and governance, quoted per contract.
Vapi is a flexible, API-driven way to build voice agents, but its $0.05/min is an orchestration fee; you add STT, LLM, TTS, and telephony on top (~$0.10-0.20/min all-in). SpeechifyAI is one all-in rate with the LLM included, plus a workflow editor, tool calling, evals, and governance, quoted per contract.
Side-by-side capabilities:
- Pricing: SpeechifyAI — Quoted per contract, all-in with the LLM included. Vapi — $0.05/min platform + STT/LLM/TTS passthrough (~$0.10–0.20 all-in).
- What's included: SpeechifyAI — LLM + STT + TTS + orchestration in one rate. Vapi — Orchestration only; bring and pay for the rest.
- Free tier: SpeechifyAI — Pilot scoped with our team. Vapi — Build plan: 60+ minutes included, then usage-based.
- Workflow design: SpeechifyAI — Visual + code, deterministic branching. Vapi — Code-first with function calling.
- Integrations: SpeechifyAI — Tool calling + webhooks. Vapi — Bring-your-own via functions.
- Evals / tests: SpeechifyAI — Simulated callers, regression suites. Vapi — Manual or bring-your-own.
- Enterprise controls: SpeechifyAI — SSO, RBAC, encryption. Vapi — HIPAA $2,000/mo, zero-retention $1,000/mo add-ons.
Verdict: SpeechifyAI gives engineering teams a production voice-agent stack pre-wired in one all-in rate, with SOC 2 Type II, SSO, RBAC, telephony, and integrations built in rather than bolted on as separate compliance line items.
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URL: https://speechify.ai/compare/agents/retell
Title: SpeechifyAI vs Retell
Retell gives developers low-latency voice infrastructure with itemized pricing: voice infra at $0.055/min plus TTS, LLM, and telephony add up to ~$0.11/min typical. SpeechifyAI rolls it into one all-in rate with the LLM included, plus deterministic workflows, tool calling + webhooks, and governance, quoted per contract.
Retell gives developers low-latency voice infrastructure with itemized pricing: voice infra at $0.055/min plus TTS, LLM, and telephony add up to ~$0.11/min typical. SpeechifyAI rolls it into one all-in rate with the LLM included, plus deterministic workflows, tool calling + webhooks, and governance, quoted per contract.
Side-by-side capabilities:
- Pricing: SpeechifyAI — Quoted per contract, all-in with the LLM included. Retell — ~$0.11/min typical ($0.055 infra + TTS + LLM + telephony).
- What's included: SpeechifyAI — LLM + STT + TTS + orchestration in one rate. Retell — Itemized add-ons (KB +$0.005, PII +$0.01, AI QA +$0.10/min).
- Billing: SpeechifyAI — Per second of talk time. Retell — Per second, but charged during silence/hold.
- Free tier: SpeechifyAI — Pilot scoped with our team. Retell — $10 free credits + 20 free concurrent calls.
- Workflow design: SpeechifyAI — Visual + code, deterministic branching. Retell — Drag-and-drop builder + real-time function calling.
- Integrations: SpeechifyAI — Tool calling + webhooks. Retell — Build-your-own via custom functions.
- Compliance: SpeechifyAI — SOC 2 Type II. Retell — SOC 2.
- Support model: SpeechifyAI — Forward-deployed engineers on Enterprise. Retell — Email / Slack community.
Verdict: SpeechifyAI covers a production voice agent at one all-in rate, billed on talk time instead of connection time, with the LLM, telephony, workflows, tool calling, and SOC 2 Type II compliance already in it instead of stacked as separate per-minute line items.
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URL: https://speechify.ai/compare/agents/bland
Title: SpeechifyAI vs Bland
Bland is known for high-volume outbound with a clean all-in number ($0.11-0.14/min), but the lower rate sits behind a $299-499/mo platform fee. SpeechifyAI is all-in with no platform surcharge, and adds inbound voice and a web widget on one brain, plus deterministic workflows and tool calling. Pricing is quoted per contract.
Bland is known for high-volume outbound with a clean all-in number ($0.11-0.14/min), but the lower rate sits behind a $299-499/mo platform fee. SpeechifyAI is all-in with no platform surcharge, and adds inbound voice and a web widget on one brain, plus deterministic workflows and tool calling. Pricing is quoted per contract.
Side-by-side capabilities:
- Pricing: SpeechifyAI — Quoted per contract, all-in with the LLM included. Bland — $0.11–0.14/min, lower rate gated behind $299–499/mo fee.
- What's included: SpeechifyAI — LLM + STT + TTS + orchestration in one rate. Bland — All-in per-minute (LLM + telephony), but monthly fee for the cheap rate.
- Free tier: SpeechifyAI — Pilot scoped with our team. Bland — 2 credits + a free inbound number.
- Primary strength: SpeechifyAI — Inbound + outbound voice + web widget. Bland — Outbound voice at scale.
- Inbound voice: SpeechifyAI — Yes, with IVR replacement. Bland — Yes.
- Deterministic workflows: SpeechifyAI — Yes. Bland — Partial.
- Integrations: SpeechifyAI — Tool calling + webhooks. Bland — Via webhooks.
- Compliance: SpeechifyAI — SOC 2 Type II. Bland — SOC 2.
Verdict: SpeechifyAI covers inbound voice, outbound voice, and a web widget on one agent brain at a single all-in rate, with no monthly platform fee gate to unlock a better number and SOC 2 Type II compliance already included.
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URL: https://speechify.ai/compare/agents/deepgram
Title: SpeechifyAI vs Deepgram
Deepgram's Voice Agent API bundles STT, LLM, and TTS at $0.075/min: strong, low-level infrastructure. SpeechifyAI is a complete platform on one all-in rate with the LLM included, billed on talk time rather than connection time, with deterministic workflows, tool calling, telephony, and compliance built in. Pricing is quoted per contract.
Deepgram's Voice Agent API bundles STT, LLM, and TTS at $0.075/min: strong, low-level infrastructure. SpeechifyAI is a complete platform on one all-in rate with the LLM included, billed on talk time rather than connection time, with deterministic workflows, tool calling, telephony, and compliance built in. Pricing is quoted per contract.
Side-by-side capabilities:
- Pricing: SpeechifyAI — Quoted per contract, all-in with the LLM included. Deepgram — $0.075/min bundled (BYO LLM/TTS lowers it to ~$0.05).
- What's included: SpeechifyAI — LLM + STT + TTS + orchestration in one rate, telephony-ready. Deepgram — STT + LLM + TTS; telephony separate.
- Billing: SpeechifyAI — Per second of talk time. Deepgram — Billed on websocket-open time (idle counts).
- Free tier: SpeechifyAI — Pilot scoped with our team. Deepgram — $200 one-time credit.
- Workflow editor: SpeechifyAI — Visual + code, deterministic. Deepgram — Build-your-own (infra + SDK).
- Integrations: SpeechifyAI — Tool calling + webhooks. Deepgram — Build-your-own.
- Telephony: SpeechifyAI — Included / bring-your-own carrier. Deepgram — Bring your own (LiveKit, etc.).
- Compliance: SpeechifyAI — SOC 2 Type II. Deepgram — SOC 2 Type II.
Verdict: SpeechifyAI ships a complete production voice-agent platform on one all-in rate, billed on talk time instead of websocket-open time, with the LLM, deterministic workflows, tool calling, telephony, and SOC 2 Type II compliance already included.
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URL: https://speechify.ai/compare/agents/cartesia
Title: SpeechifyAI vs Cartesia
Cartesia (Line) is ultra-low-latency voice infrastructure with a $0.06/min headline, but telephony adds $0.014/min and the "LLM included" is a limited-time promo. SpeechifyAI is all-in with the LLM included permanently, plus a full workflow, integrations, and compliance platform, quoted per contract.
Cartesia (Line) is ultra-low-latency voice infrastructure with a $0.06/min headline, but telephony adds $0.014/min and the "LLM included" is a limited-time promo. SpeechifyAI is all-in with the LLM included permanently, plus a full workflow, integrations, and compliance platform, quoted per contract.
Side-by-side capabilities:
- Pricing: SpeechifyAI — Quoted per contract, all-in with the LLM included. Cartesia — $0.06/min + $0.014/min telephony; LLM free is a promo.
- LLM cost: SpeechifyAI — Included, no passthrough — permanent. Cartesia — Free for now (limited-time promo).
- Free tier: SpeechifyAI — Pilot scoped with our team. Cartesia — 20K credits/mo, no commercial use on Free.
- Workflow editor: SpeechifyAI — Visual + code, deterministic. Cartesia — Build-your-own.
- Integrations: SpeechifyAI — Tool calling + webhooks. Cartesia — Build-your-own.
- Voice library: SpeechifyAI — 20+ curated real-time voices. Cartesia — Sonic voices (cloning on paid tiers).
- Compliance: SpeechifyAI — SOC 2 Type II. Cartesia — SOC 2.
Verdict: SpeechifyAI is a single per-minute rate with the LLM permanently included, plus the workflow editor, tool calling, telephony, evals, and SOC 2 Type II compliance, on streaming latency well inside the conversational-immediate window.
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URL: https://speechify.ai/compare/agents/synthflow
Title: SpeechifyAI vs Synthflow
Synthflow's main pricing page leads with enterprise contracts starting at $30,000/year; compare pages surface a $0.08/min trial rate with $10 free credits. SpeechifyAI is also enterprise and quoted per contract, but on one all-in rate with the LLM included, plus deterministic workflows, tool calling, evals, and enterprise governance rather than a trial rate that changes on signature.
Synthflow's main pricing page leads with enterprise contracts starting at $30,000/year; compare pages surface a $0.08/min trial rate with $10 free credits. SpeechifyAI is also enterprise and quoted per contract, but on one all-in rate with the LLM included, plus deterministic workflows, tool calling, evals, and enterprise governance rather than a trial rate that changes on signature.
Side-by-side capabilities:
- Pricing: SpeechifyAI — Quoted per contract, all-in with the LLM included. Synthflow — Enterprise contracts from $30K/year; $0.08/min trial rate + $10 credits on compare pages.
- What's included: SpeechifyAI — LLM + STT + TTS + orchestration in one rate. Synthflow — Voice engine + per-minute LLM add-ons; scoped per enterprise contract.
- Free tier: SpeechifyAI — Pilot scoped with our team. Synthflow — 14-day trial with $10 free credits; PAYG to deploy.
- Workflow design: SpeechifyAI — Visual + code, deterministic branching. Synthflow — No-code builder.
- Integrations: SpeechifyAI — Tool calling + webhooks. Synthflow — Integrations + bring-your-own.
- Evals / tests: SpeechifyAI — Simulated callers, regression suites. Synthflow — Limited.
- Compliance: SpeechifyAI — SOC 2 Type II. Synthflow — SOC 2.
Verdict: SpeechifyAI is also sold through sales, but the quote is one all-in rate against your volume rather than a trial rate that changes on signature, and the workflow editor, evals, tool calling, telephony, and SOC 2 Type II compliance are in it from the start.
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URL: https://speechify.ai/compare/agents/hume
Title: SpeechifyAI vs Hume
Hume's EVI is an expressive, empathic speech-to-speech model priced $0.04-0.07/min, but that excludes the LLM (billed separately by your provider) and the lowest rates need a large plan. SpeechifyAI is truly all-in with the LLM included, plus deterministic workflows, tool calling, and compliance, quoted per contract.
Hume's EVI is an expressive, empathic speech-to-speech model priced $0.04-0.07/min, but that excludes the LLM (billed separately by your provider) and the lowest rates need a large plan. SpeechifyAI is truly all-in with the LLM included, plus deterministic workflows, tool calling, and compliance, quoted per contract.
Side-by-side capabilities:
- Pricing: SpeechifyAI — Quoted per contract, all-in with the LLM included. Hume — $0.04–0.07/min + external LLM billed separately.
- LLM cost: SpeechifyAI — Included, no passthrough. Hume — Bring-your-own, billed by your LLM provider.
- Free tier: SpeechifyAI — Pilot scoped with our team. Hume — 5 min/mo.
- Primary strength: SpeechifyAI — Production platform: workflows, integrations, compliance. Hume — Emotionally expressive, empathic voice.
- Workflow editor: SpeechifyAI — Visual + code, deterministic. Hume — Build-your-own.
- Integrations: SpeechifyAI — Tool calling + webhooks. Hume — Build-your-own.
- Compliance: SpeechifyAI — SOC 2 Type II. Hume — SOC 2 Type II.
Verdict: SpeechifyAI is a single per-minute rate with the LLM included so the bill stays predictable as model choices change, plus emotion control, SSML, deterministic workflows, tool calling, telephony, and SOC 2 Type II compliance.
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URL: https://speechify.ai/compare/build/text-to-speech/elevenlabs
Title: SpeechifyAI vs ElevenLabs
ElevenLabs is known for an expansive voice library and deep voice-cloning heritage. SpeechifyAI matches the core capabilities (cloning, streaming, expressive neural voices) from $6 per 1M characters, well below ElevenLabs' credit-based rates on comparable tiers.
ElevenLabs is known for an expansive voice library and deep voice-cloning heritage. SpeechifyAI matches the core capabilities (cloning, streaming, expressive neural voices) from $6 per 1M characters, well below ElevenLabs' credit-based rates on comparable tiers.
Bottom line: ElevenLabs is credit-based at roughly $100-300 per 1M on lower tiers; SpeechifyAI is from $6 per 1M on flat per-character billing, with cloning included on every paid plan.
Side-by-side capabilities:
- Price (per 1M chars): SpeechifyAI — From $6 / 1M. ElevenLabs — Credit-based; roughly $100-300 on lower tiers, dropping with scale and annual commitments.
- Pricing model: SpeechifyAI — Per character; no credits, no token math. ElevenLabs — Credit-based; effective per-character cost varies by plan tier and model.
- Independent benchmarks: SpeechifyAI — Independently evaluated on Artificial Analysis' blind-listening TTS leaderboard; priced at $10/1M. ElevenLabs — v3 Conversational, their best-rated model, is #8 on Artificial Analysis (Elo 1,209) at $50/1M; Eleven v3 sits below Simba 3.2 on Datapoint's quality-cost frontier at roughly $104/1M.
- Voice quality: SpeechifyAI — Proprietary neural voice models. ElevenLabs — High-quality, expressive neural voices; widely regarded for naturalness.
- Voices: SpeechifyAI — 900+. ElevenLabs — 10,000+ including a large community library.
- Languages: SpeechifyAI — 30+. ElevenLabs — 70+ on Eleven v3; 29-32 on Multilingual v2 and Flash/Turbo.
- Voice cloning: SpeechifyAI — Professional voice cloning included. ElevenLabs — Instant and professional cloning; a long heritage here.
- Latency: SpeechifyAI — ~430ms first byte, streaming. ElevenLabs — Low-latency streaming on Flash/Turbo models; varies by model.
- Commercial use / free tier: SpeechifyAI — Commercial use on every plan; 500K chars/month free. ElevenLabs — Free tier is non-commercial; commercial use requires a paid plan.
Verdict: SpeechifyAI covers expressive neural voices, professional cloning, and streaming at from $6 per million characters on Scale, with flat per-character billing, cloning included on every paid plan, commercial use on every tier, and a 99.9% uptime SLA in the contract.
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URL: https://speechify.ai/compare/build/text-to-speech/google
Title: SpeechifyAI vs Google Cloud Text-to-Speech
Google Cloud offers the widest language coverage in the market across a tiered lineup that runs from robotic to high-end. SpeechifyAI undercuts Google's quality tiers (Neural2 and up) from $6 per 1M characters, with no per-tier math and no penalty for the spaces or SSML tags Google counts toward the bill.
Google Cloud offers the widest language coverage in the market across a tiered lineup that runs from robotic to high-end. SpeechifyAI undercuts Google's quality tiers (Neural2 and up) from $6 per 1M characters, with no per-tier math and no penalty for the spaces or SSML tags Google counts toward the bill.
Bottom line: Google's quality tiers run $4-160 per 1M (Neural2 at $16, Studio at $160); SpeechifyAI is from $6 per 1M across the catalog with no tier picker.
Side-by-side capabilities:
- Price (per 1M chars): SpeechifyAI — From $6 / 1M, across the catalog. Google Cloud Text-to-Speech — Tiered by voice class: Standard/WaveNet $4, Neural2 $16, Chirp 3:HD $30, Instant Custom Voice $60, Studio $160; Gemini-TTS token-metered.
- Pricing model: SpeechifyAI — Per character; spaces and markup do not inflate cost. Google Cloud Text-to-Speech — Per character by voice class; billing counts spaces and SSML tags.
- Voice quality: SpeechifyAI — Proprietary neural; consistent across the catalog. Google Cloud Text-to-Speech — Ranges from robotic (Standard) to high-end (Chirp3-HD, Studio).
- Voices: SpeechifyAI — 900+. Google Cloud Text-to-Speech — 380+ across voice classes.
- Languages: SpeechifyAI — 30+. Google Cloud Text-to-Speech — 75+ languages and variants; widest coverage in the market.
- Voice cloning: SpeechifyAI — Professional voice cloning included. Google Cloud Text-to-Speech — Custom Voice available, but a separate enterprise process.
- Latency: SpeechifyAI — ~430ms first byte, streaming. Google Cloud Text-to-Speech — Streaming available; latency varies by voice class.
- Commercial use / free tier: SpeechifyAI — Commercial use on every plan; 500K chars/month free. Google Cloud Text-to-Speech — Commercial use; free monthly buckets per voice class.
Verdict: SpeechifyAI is one flat per-character rate from $6 per million across the catalog, with no tier picker on the bill, no SSML or whitespace inflation, and professional voice cloning included on Starter and above with no enterprise contract.
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URL: https://speechify.ai/compare/build/text-to-speech/azure
Title: SpeechifyAI vs Microsoft Azure Text to Speech
Azure Text to Speech is a natural fit if you are already invested in Microsoft's cloud and compliance footprint. SpeechifyAI delivers comparable neural quality and built-in voice cloning from $6 per 1M characters, below Azure's $15 Neural tier and without an approval gate for cloning.
Azure Text to Speech is a natural fit if you are already invested in Microsoft's cloud and compliance footprint. SpeechifyAI delivers comparable neural quality and built-in voice cloning from $6 per 1M characters, below Azure's $15 Neural tier and without an approval gate for cloning.
Bottom line: Azure's Neural and Neural HD tier is $15 per 1M with cloning behind an approval gate; SpeechifyAI is from $6 per 1M with cloning on Starter and above.
Side-by-side capabilities:
- Price (per 1M chars): SpeechifyAI — From $6 / 1M. Microsoft Azure Text to Speech — Neural / Neural HD $15; Custom Neural Voice approval-gated.
- Pricing model: SpeechifyAI — Per character; no credits, no token math. Microsoft Azure Text to Speech — Per character, tiered by neural model class.
- Voice quality: SpeechifyAI — Proprietary neural voice models. Microsoft Azure Text to Speech — Strong neural voices; the HD tier adds expressiveness.
- Voices: SpeechifyAI — 900+. Microsoft Azure Text to Speech — Hundreds of neural voices.
- Languages: SpeechifyAI — 30+. Microsoft Azure Text to Speech — Very broad; many languages and locale variants.
- Voice cloning: SpeechifyAI — Professional voice cloning included. Microsoft Azure Text to Speech — Custom Neural Voice, gated behind an approval process.
- Latency: SpeechifyAI — ~430ms first byte, streaming. Microsoft Azure Text to Speech — Streaming; latency varies by region and tier.
- Commercial use / free tier: SpeechifyAI — Commercial use on every plan; 500K chars/month free. Microsoft Azure Text to Speech — Commercial use; free F0 tier of about 0.5M chars/month.
Verdict: SpeechifyAI ships professional voice cloning on Starter and above with no approval cycle, on one flat per-character rate from $6 per million across the catalog, with ~430ms streaming first byte and a 99.9% uptime SLA in the contract.
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URL: https://speechify.ai/compare/build/text-to-speech/amazon-polly
Title: SpeechifyAI vs Amazon Polly
Amazon Polly is the default when you are deep in AWS, with engines spanning cheap-and-robotic to generative. SpeechifyAI beats Polly's Neural tier on price from $6 per 1M characters and adds professional voice cloning, which Polly does not offer outside a custom Brand Voice engagement.
Amazon Polly is the default when you are deep in AWS, with engines spanning cheap-and-robotic to generative. SpeechifyAI beats Polly's Neural tier on price from $6 per 1M characters and adds professional voice cloning, which Polly does not offer outside a custom Brand Voice engagement.
Bottom line: Polly's Neural engine is $16 per 1M (Standard $4, Generative $30); SpeechifyAI is from $6 per 1M and adds cloning that Polly only offers as a custom Brand Voice engagement.
Side-by-side capabilities:
- Price (per 1M chars): SpeechifyAI — From $6 / 1M. Amazon Polly — Standard $4, Neural $16, Generative $30, Long-form $100.
- Pricing model: SpeechifyAI — Per character; no credits, no token math. Amazon Polly — Per character, tiered by engine.
- Voice quality: SpeechifyAI — Proprietary neural voice models. Amazon Polly — Standard is robotic; Neural and Generative are far better.
- Voices: SpeechifyAI — 900+. Amazon Polly — 100+ voices across engines.
- Languages: SpeechifyAI — 30+. Amazon Polly — Broad coverage; available set varies by engine.
- Voice cloning: SpeechifyAI — Professional voice cloning included. Amazon Polly — No general voice cloning; Brand Voice is a custom enterprise engagement.
- Latency: SpeechifyAI — ~430ms first byte, streaming. Amazon Polly — Streaming; latency varies by engine.
- Commercial use / free tier: SpeechifyAI — Commercial use on every plan; 500K chars/month free. Amazon Polly — Commercial use; 12-month AWS free tier.
Verdict: SpeechifyAI covers neural-grade TTS at from $6 per million characters across the catalog, with professional voice cloning included on Starter and above and no engine picker on the bill, streaming first byte ~430ms, and a 99.9% uptime SLA in the contract.
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URL: https://speechify.ai/compare/build/text-to-speech/deepgram
Title: SpeechifyAI vs Deepgram Aura
Deepgram Aura is built for low-latency, real-time voice agents and pairs naturally with Deepgram's speech-to-text. SpeechifyAI offers comparable ~430ms streaming from $6 per 1M characters, below both Aura tiers, with far more voices and languages.
Deepgram Aura is built for low-latency, real-time voice agents and pairs naturally with Deepgram's speech-to-text. SpeechifyAI offers comparable ~430ms streaming from $6 per 1M characters, below both Aura tiers, with far more voices and languages.
Bottom line: Deepgram Aura is $15-30 per 1M by model; SpeechifyAI is from $6 per 1M with ~430ms streaming and a much larger voice and language catalog.
Side-by-side capabilities:
- Price (per 1M chars): SpeechifyAI — From $6 / 1M. Deepgram Aura — Aura-1 $15, Aura-2 $30.
- Pricing model: SpeechifyAI — Per character; no credits, no token math. Deepgram Aura — Per character, by model generation.
- Voice quality: SpeechifyAI — Proprietary neural voice models. Deepgram Aura — Natural and conversational; tuned for real-time agent use.
- Voices: SpeechifyAI — 900+. Deepgram Aura — A smaller curated set.
- Languages: SpeechifyAI — 30+. Deepgram Aura — Primarily English-focused; fewer languages.
- Voice cloning: SpeechifyAI — Professional voice cloning included. Deepgram Aura — No general-purpose voice cloning.
- Latency: SpeechifyAI — ~430ms first byte, streaming. Deepgram Aura — Very low latency; a core strength.
- Commercial use / free tier: SpeechifyAI — Commercial use on every plan; 500K chars/month free. Deepgram Aura — Commercial use; $200 in free credit to start.
Verdict: SpeechifyAI covers real-time conversational TTS at from $6 per million characters across the catalog, with ~430ms streaming first byte, 900+ voices and 30+ languages, professional voice cloning included on Starter and above, and a 99.9% uptime SLA.
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URL: https://speechify.ai/compare/build/text-to-speech/cartesia
Title: SpeechifyAI vs Cartesia Sonic
Cartesia Sonic is engineered for ultra-low latency in real-time applications. SpeechifyAI provides ~430ms streaming from $6 per 1M characters with transparent per-character billing, versus Cartesia's credit-based model that works out to roughly $24-40 per 1M.
Cartesia Sonic is engineered for ultra-low latency in real-time applications. SpeechifyAI provides ~430ms streaming from $6 per 1M characters with transparent per-character billing, versus Cartesia's credit-based model that works out to roughly $24-40 per 1M.
Bottom line: Cartesia Sonic is credit-based at roughly $24-40 per 1M; SpeechifyAI is from $6 per 1M with transparent per-character billing and commercial use on the free tier.
Side-by-side capabilities:
- Price (per 1M chars): SpeechifyAI — From $6 / 1M. Cartesia Sonic — Credit-based; roughly $24-40, derived from credit bundles.
- Pricing model: SpeechifyAI — Per character; no credits, no token math. Cartesia Sonic — Credit-based; effective per-character rate varies by plan.
- Voice quality: SpeechifyAI — Proprietary neural voice models. Cartesia Sonic — Natural and expressive; built for real-time.
- Voices: SpeechifyAI — 900+. Cartesia Sonic — Curated library plus cloning.
- Languages: SpeechifyAI — 30+. Cartesia Sonic — Growing multilingual coverage; fewer languages.
- Voice cloning: SpeechifyAI — Professional voice cloning included. Cartesia Sonic — Instant voice cloning supported.
- Latency: SpeechifyAI — ~430ms first byte, streaming. Cartesia Sonic — Ultra-low latency; a core strength.
- Commercial use / free tier: SpeechifyAI — Commercial use on every plan; 500K chars/month free. Cartesia Sonic — Free tier is non-commercial; commercial use requires a paid plan.
Verdict: SpeechifyAI covers expressive neural voices at from $6 per million characters on flat per-character billing, with commercial use on every tier including Free, 900+ voices and 30+ languages in the catalog, and professional voice cloning included on Starter and above.
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URL: https://speechify.ai/compare/build/text-to-speech/playht
Title: SpeechifyAI vs PlayHT
PlayHT now operates under the PlayAI brand on the pricing surface, with a large voice library (800+ voices, 130+ languages) and a studio workflow alongside the API. SpeechifyAI leads with documented from-$6-per-1M character pricing, a 99.9% uptime SLA, and professional cloning included on every paid plan.
PlayHT now operates under the PlayAI brand on the pricing surface, with a large voice library (800+ voices, 130+ languages) and a studio workflow alongside the API. SpeechifyAI leads with documented from-$6-per-1M character pricing, a 99.9% uptime SLA, and professional cloning included on every paid plan.
Bottom line: PlayHT bills in character bundles or minute credits with per-voice cloning fees; SpeechifyAI is from $6 per 1M documented, with cloning included on every paid plan.
Side-by-side capabilities:
- Price (per 1M chars): SpeechifyAI — From $6 / 1M. PlayHT — Public pricing rebranded as PlayAI; consumer plans sold by character bundles, PlayAI by minute credits, API rate by negotiation.
- Pricing model: SpeechifyAI — Per character; no credits, no token math. PlayHT — Character bundles (consumer) or minute credits (PlayAI); per-voice cloning fees on top.
- Voice quality: SpeechifyAI — Proprietary neural voice models. PlayHT — Natural neural voices; the platform's heritage is consumer TTS and podcast workflows.
- Voice library: SpeechifyAI — 900+. PlayHT — 800+ voices marketed.
- Voice cloning: SpeechifyAI — Professional voice cloning included. PlayHT — "Clone a voice in 30 seconds"; per-voice setup fee from tens to hundreds of dollars.
- Languages: SpeechifyAI — 30+. PlayHT — 130+ languages marketed.
- Latency: SpeechifyAI — ~430ms first byte, streaming. PlayHT — Streaming TTS; no hard ms figure on the public marketing pages.
- Availability / commercial use: SpeechifyAI — Commercial use on every plan; 500K chars/month free; 99.9% uptime SLA. PlayHT — Commercial use plan-dependent; pricing surface rebranded to PlayAI.
Verdict: SpeechifyAI is a documented from-$6-per-million-character contract with cloning included on Starter and above, no per-voice setup fee, commercial use on every tier, and a 99.9% uptime SLA in the contract.
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URL: https://speechify.ai/compare/build/text-to-speech/openai
Title: SpeechifyAI vs OpenAI Text-to-Speech
OpenAI's TTS produces high-quality, steerable voices but meters by tokens rather than characters, so cost takes estimation. SpeechifyAI bills from $6 per 1M characters with no token math, adds voice cloning that OpenAI does not offer, and ships many more voices.
OpenAI's TTS produces high-quality, steerable voices but meters by tokens rather than characters, so cost takes estimation. SpeechifyAI bills from $6 per 1M characters with no token math, adds voice cloning that OpenAI does not offer, and ships many more voices.
Bottom line: OpenAI meters TTS by tokens ($12 per 1M audio output tokens) with no arbitrary-voice cloning; SpeechifyAI is from $6 per 1M flat per character, cloning included.
Side-by-side capabilities:
- Price (per 1M chars): SpeechifyAI — From $6 / 1M. OpenAI Text-to-Speech — gpt-4o-mini-tts token-metered: $0.60 per 1M input tokens, $12 per 1M audio output tokens.
- Pricing model: SpeechifyAI — Flat per character; no token math. OpenAI Text-to-Speech — Token-metered; you tokenize the script to estimate cost.
- Voice quality: SpeechifyAI — Proprietary neural voice models. OpenAI Text-to-Speech — High-quality, expressive voices; steerable via instructions.
- Voices: SpeechifyAI — 900+. OpenAI Text-to-Speech — 13 built-in voices (page intro confusingly says 11).
- Languages: SpeechifyAI — 30+. OpenAI Text-to-Speech — Multilingual; varies by voice.
- Voice cloning: SpeechifyAI — Professional voice cloning included. OpenAI Text-to-Speech — No cloning of arbitrary voices; built-in voices only.
- Latency: SpeechifyAI — ~430ms first byte, streaming. OpenAI Text-to-Speech — Streaming supported; latency varies.
- Commercial use / free tier: SpeechifyAI — Commercial use on every plan; 500K chars/month free. OpenAI Text-to-Speech — Commercial use; no standing free tier for the API.
Verdict: SpeechifyAI is from $6 per million characters on flat per-character billing, with professional voice cloning included on Starter and above and a 900+ voice catalog covering 30+ languages, on streaming first byte ~430ms.
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URL: https://speechify.ai/compare/build/text-to-speech/rime
Title: SpeechifyAI vs Rime
Rime focuses on realistic, conversational voices tuned for real-time agents, priced from $30 to $50 per 1M by model. SpeechifyAI covers the same real-time use case from $6 per 1M characters with broader language and voice coverage.
Rime focuses on realistic, conversational voices tuned for real-time agents, priced from $30 to $50 per 1M by model. SpeechifyAI covers the same real-time use case from $6 per 1M characters with broader language and voice coverage.
Bottom line: Rime is $30-50 per 1M by model; SpeechifyAI covers the same real-time conversational profile from $6 per 1M with broader voice and language coverage.
Side-by-side capabilities:
- Price (per 1M chars): SpeechifyAI — From $6 / 1M. Rime — Mist $30, Arcana $40, Coda $50.
- Pricing model: SpeechifyAI — Per character; no credits, no token math. Rime — Per character, tiered by model.
- Voice quality: SpeechifyAI — Proprietary neural voice models. Rime — Natural and conversational; focus on realistic everyday voices.
- Voices: SpeechifyAI — 900+. Rime — A curated set of realistic voices.
- Languages: SpeechifyAI — 30+. Rime — Primarily English-focused.
- Voice cloning: SpeechifyAI — Professional voice cloning included. Rime — Custom voice options; varies by plan.
- Latency: SpeechifyAI — ~430ms first byte, streaming. Rime — Low latency; built for real-time agents.
- Commercial use / free tier: SpeechifyAI — Commercial use on every plan; 500K chars/month free. Rime — Commercial use; 3,000 free minutes on signup.
Verdict: SpeechifyAI covers real-time conversational TTS at from $6 per million characters across the catalog, with 900+ voices and 30+ languages, professional voice cloning included starting on the $10 Starter plan, and streaming first byte ~430ms.
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URL: https://speechify.ai/compare/build/text-to-speech/hume
Title: SpeechifyAI vs Hume Octave
Hume's Octave leads on emotionally expressive, empathic speech, sold through subscription tiers that work out to roughly $50-150 per 1M. SpeechifyAI offers its own emotion control and expressive neural voices from $6 per 1M characters, well below Hume's effective rates.
Hume's Octave leads on emotionally expressive, empathic speech, sold through subscription tiers that work out to roughly $50-150 per 1M. SpeechifyAI offers its own emotion control and expressive neural voices from $6 per 1M characters, well below Hume's effective rates.
Bottom line: Hume's subscription tiers work out to roughly $50-150 per 1M; SpeechifyAI is from $6 per 1M with emotion control and no subscription floor.
Side-by-side capabilities:
- Price (per 1M chars): SpeechifyAI — From $6 / 1M. Hume Octave — Roughly $50-150 depending on subscription tier.
- Pricing model: SpeechifyAI — Per character; no credits, no token math. Hume Octave — Subscription tiers; effective per-character rate varies.
- Expressiveness / emotion: SpeechifyAI — Emotion control plus SSML. Hume Octave — Industry-leading emotional expressiveness; a core strength.
- Voices: SpeechifyAI — 900+. Hume Octave — Generated and curated voices; fewer fixed presets.
- Languages: SpeechifyAI — 30+. Hume Octave — Multilingual; fewer languages.
- Voice cloning: SpeechifyAI — Professional voice cloning included. Hume Octave — Voice design and customization focus.
- Latency: SpeechifyAI — ~430ms first byte, streaming. Hume Octave — Streaming; latency varies.
- Commercial use / free tier: SpeechifyAI — Commercial use on every plan; 500K chars/month free. Hume Octave — Commercial use; tiered subscriptions.
Verdict: SpeechifyAI is from $6 per million characters across every plan with no subscription floor, professional voice cloning included on Starter and above, a 900+ voice catalog covering 30+ languages, and a 99.9% uptime SLA in the contract.
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URL: https://speechify.ai/compare/build/text-to-speech/inworld
Title: SpeechifyAI vs Inworld
Inworld sells a three-model quality-and-price ladder built to sit inside their character runtime, where the rate changes with the model you pick. SpeechifyAI bills every Simba model at one plan rate, from $6 per 1M characters, and Simba 3.2 is evaluated on the Artificial Analysis Speech Arena.
Inworld sells a three-model quality-and-price ladder built to sit inside their character runtime, where the rate changes with the model you pick. SpeechifyAI bills every Simba model at one plan rate, from $6 per 1M characters, and Simba 3.2 is evaluated on the Artificial Analysis Speech Arena.
Bottom line: Simba 3.2 is evaluated on the Artificial Analysis Speech Arena, a blind test where listeners pick the better voice without being told which vendor made it. Inworld's best model, Realtime TTS 1.5 Max, scores Elo 1,196 on the same arena. SpeechifyAI starts at $10 per 1M characters; Inworld's best starts at $35, and only reaches $17.50 on their $1,500 per month Growth plan.
Side-by-side capabilities:
- Blind listener rating. Simba 3.2 scores an Elo of 1,240 on the Artificial Analysis Speech Arena; Inworld's best scores 1,196. SpeechifyAI — Strong. Inworld — Average.
- Entry price for the vendor's best model: $10 against $35 per 1M characters. SpeechifyAI — Strong. Inworld — Weak.
- Monthly platform fee needed to reach the floor rate: $499 against $1,500. SpeechifyAI — Strong. Inworld — Weak.
- One rate whichever model you call. Simba 3.2 and 3.0 both bill at the plan rate; Inworld's rate changes with the model. SpeechifyAI — Strong. Inworld — Weak.
- The cheapest way in. Inworld's lowest-priced model is $15 per 1M on their free plan; Simba 3.2 is $10 per 1M. SpeechifyAI — Strong. Inworld — Average.
- Language coverage. Inworld publishes 100+ languages; we cover 30+ in total and stream 7 locales on Simba 3.0. SpeechifyAI — Average. Inworld — Strong.
- Release cadence on the board. Simba 3.0 entered at Elo 1,121; Simba 3.2 now scores Elo 1,240. Inworld's Realtime TTS-2 entered at Elo 1,189, while in research preview. SpeechifyAI — Strong. Inworld — Strong.
- Voice cloning with no per-voice setup fee. Both vendors include it and bill only for synthesis. SpeechifyAI — Strong. Inworld — Strong.
Verdict: Inworld covers far more languages than we do, and past our 30+ locales, or if you need one voice that carries across them, they are the better vendor. If you want a highly rated voice at a rate that does not change with the model you call or depend on a $1,500 monthly commit, Simba 3.2 is evaluated on Artificial Analysis from $6 per 1M characters.
Competitor figures verified 2026-07-30.
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URL: https://speechify.ai/compare/build/voice-cloning/elevenlabs
Title: SpeechifyAI vs ElevenLabs — Voice Cloning
ElevenLabs has a deep voice-cloning heritage and a large community voice library. SpeechifyAI matches the core cloning workflow — zero-shot from a short sample plus fine-tuned for best quality — with consent required by design, included on every paid plan, and per-character synthesis from $6 per 1M.
ElevenLabs has a deep voice-cloning heritage and a large community voice library. SpeechifyAI matches the core cloning workflow — zero-shot from a short sample plus fine-tuned for best quality — with consent required by design, included on every paid plan, and per-character synthesis from $6 per 1M.
Side-by-side capabilities:
- Cloning tiers: SpeechifyAI — Zero-shot from a short sample, plus fine-tuned for best quality. ElevenLabs — Instant and professional cloning; long heritage here.
- Sample needed (instant): SpeechifyAI — 10-30 seconds of clean speech. ElevenLabs — About a minute for instant; more for professional.
- Consent: SpeechifyAI — Consent record required on every clone (full name + email). ElevenLabs — Voice verification and consent required for professional cloning.
- Cross-language: SpeechifyAI — Cloned voice speaks 30+. ElevenLabs — Cloned voices speak the model's supported languages.
- Pricing model: SpeechifyAI — Per character; cloning included in the plan. ElevenLabs — Credit-based; cloning tied to subscription tier.
- Availability: SpeechifyAI — Included on Starter, Pro, Scale, Enterprise (not Free). ElevenLabs — Instant cloning from Starter; professional on higher tiers.
Verdict: SpeechifyAI covers zero-shot and fine-tuned cloning with consent enforced at the API, included on every paid plan, and per-character synthesis from $6 per 1M — a flat rate against ElevenLabs' credit model.
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URL: https://speechify.ai/compare/build/voice-cloning/playht
Title: SpeechifyAI vs PlayHT — Voice Cloning
PlayHT offers instant and high-fidelity voice cloning with a large voice library. SpeechifyAI matches the cloning workflow with consent required on every clone, cross-language output from a single clone, and per-character pricing included on every paid plan.
PlayHT offers instant and high-fidelity voice cloning with a large voice library. SpeechifyAI matches the cloning workflow with consent required on every clone, cross-language output from a single clone, and per-character pricing included on every paid plan.
Side-by-side capabilities:
- Cloning tiers: SpeechifyAI — Zero-shot from a short sample, plus fine-tuned for best quality. PlayHT — Instant and high-fidelity cloning.
- Sample needed (instant): SpeechifyAI — 10-30 seconds of clean speech. PlayHT — Short sample for instant cloning.
- Consent: SpeechifyAI — Consent record required on every clone (full name + email). PlayHT — Consent required per its terms.
- Cross-language: SpeechifyAI — Cloned voice speaks 30+. PlayHT — Multilingual synthesis across supported languages.
- Pricing model: SpeechifyAI — Per character; cloning included in the plan. PlayHT — Credit/word-based tiers.
- Availability: SpeechifyAI — Included on Starter, Pro, Scale, Enterprise (not Free). PlayHT — Cloning on paid plans.
Verdict: SpeechifyAI matches PlayHT's instant and high-fidelity cloning with consent enforced at the API, cross-language output from one voice ID, and flat per-character billing included on every paid plan.
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URL: https://speechify.ai/compare/build/voice-cloning/resemble
Title: SpeechifyAI vs Resemble AI — Voice Cloning
Resemble AI specializes in voice cloning with real-time and localization features. SpeechifyAI covers the same cloning workflow — zero-shot plus fine-tuned — with consent enforced at the API and cross-language output included on every paid plan.
Resemble AI specializes in voice cloning with real-time and localization features. SpeechifyAI covers the same cloning workflow — zero-shot plus fine-tuned — with consent enforced at the API and cross-language output included on every paid plan.
Side-by-side capabilities:
- Cloning tiers: SpeechifyAI — Zero-shot from a short sample, plus fine-tuned for best quality. Resemble AI — Rapid and professional cloning.
- Sample needed (instant): SpeechifyAI — 10-30 seconds of clean speech. Resemble AI — Short sample for rapid cloning.
- Consent: SpeechifyAI — Consent record required on every clone (full name + email). Resemble AI — Consent and identity verification required.
- Cross-language: SpeechifyAI — Cloned voice speaks 30+. Resemble AI — Localization and cross-language features.
- Pricing model: SpeechifyAI — Per character; cloning included in the plan. Resemble AI — Usage-based pricing.
- Availability: SpeechifyAI — Included on Starter, Pro, Scale, Enterprise (not Free). Resemble AI — Cloning on paid plans.
Verdict: SpeechifyAI matches Resemble's cloning depth with consent required on every create call, one cloned voice across 30+ languages, and per-character synthesis included on every paid plan.
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URL: https://speechify.ai/compare/build/voice-cloning/murf
Title: SpeechifyAI vs Murf AI — Voice Cloning
Murf AI pairs a studio-style workflow with voice cloning on its higher tiers. SpeechifyAI offers API-first cloning — zero-shot from a short sample plus fine-tuned — with consent enforced at the API and per-character pricing included on every paid plan.
Murf AI pairs a studio-style workflow with voice cloning on its higher tiers. SpeechifyAI offers API-first cloning — zero-shot from a short sample plus fine-tuned — with consent enforced at the API and per-character pricing included on every paid plan.
Side-by-side capabilities:
- Cloning tiers: SpeechifyAI — Zero-shot from a short sample, plus fine-tuned for best quality. Murf AI — Professional voice cloning on higher tiers.
- Approach: SpeechifyAI — API-first: create by API or Console. Murf AI — Studio-first workflow with cloning add-on.
- Consent: SpeechifyAI — Consent record required on every clone (full name + email). Murf AI — Consent required for cloning.
- Cross-language: SpeechifyAI — Cloned voice speaks 30+. Murf AI — Multilingual synthesis across supported languages.
- Pricing model: SpeechifyAI — Per character; cloning included in the plan. Murf AI — Subscription tiers; cloning on higher plans.
- Availability: SpeechifyAI — Included on Starter, Pro, Scale, Enterprise (not Free). Murf AI — Cloning on higher-tier plans.
Verdict: SpeechifyAI is API-first cloning: create a voice from a short sample, with consent, and synthesize by voice ID at a flat per-character rate included on every paid plan.
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URL: https://speechify.ai/compare/build/voice-cloning/descript
Title: SpeechifyAI vs Descript — Voice Cloning
Descript's Overdub clones a voice inside its editor for content creators. SpeechifyAI offers API-first cloning any product can build on — zero-shot plus fine-tuned — with consent enforced at the API and per-character pricing included on every paid plan.
Descript's Overdub clones a voice inside its editor for content creators. SpeechifyAI offers API-first cloning any product can build on — zero-shot plus fine-tuned — with consent enforced at the API and per-character pricing included on every paid plan.
Side-by-side capabilities:
- Cloning tiers: SpeechifyAI — Zero-shot from a short sample, plus fine-tuned for best quality. Descript — Overdub cloning inside the editor.
- Approach: SpeechifyAI — API-first: build cloning into your product. Descript — Editor-first; cloning for Descript projects.
- Consent: SpeechifyAI — Consent record required on every clone (full name + email). Descript — Consent statement required for Overdub.
- Cross-language: SpeechifyAI — Cloned voice speaks 30+. Descript — Focused on English editing workflows.
- Pricing model: SpeechifyAI — Per character; cloning included in the plan. Descript — Subscription tiers for the editor.
- Availability: SpeechifyAI — Included on Starter, Pro, Scale, Enterprise (not Free). Descript — Overdub on paid plans.
Verdict: SpeechifyAI is cloning as an API you build on, not an editor feature: create a voice with consent, synthesize by ID across 30+ languages, at a flat per-character rate on every paid plan.
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URL: https://speechify.ai/industries/agents/insurance
Title: Voice agents for insurance
From claims intake and policy quotes to renewal reminders and Medicare enrollment, SpeechifyAI voice agents automate policyholder and prospect workflows while maintaining compliance.
From claims intake and policy quotes to renewal reminders and Medicare enrollment, SpeechifyAI voice agents automate policyholder and prospect workflows while maintaining compliance.
Benefits:
- Accelerate claims processing — 24/7 voice and chat agents that collect FNOL details, verify coverage, schedule adjusters, and provide status updates — reducing claim cycle times by up to 40%.
- Drive policy growth — Automate quote generation, renewal reminders, cross-sell campaigns, and enrollment flows to increase premium revenue without adding headcount.
- Stay compliant — Enterprise-grade security with call recording controls and deterministic scripts that follow state-specific disclosure requirements.
Workflows:
- Claims intake and status — Automate FNOL collection, adjuster scheduling, status updates, and settlement communication across the entire claims lifecycle.
- Quoting, enrollment, and renewals — Generate quotes, guide enrollment, send renewal reminders, and run retention campaigns — all with compliant, auditable conversations.
- Compliance and recording controls — Deterministic scripts enforce state-specific disclosures and licensing requirements. Every conversation can be recorded and transcribed for regulatory review.
Use cases: Claims intake and FNOL; Policy quotes and enrollment; Renewal reminders and retention; Medicare and open enrollment; After-hours and overflow support
Sample call:
Caller: I was just in a fender bender. I need to file a claim.
Agent: I'm sorry to hear that — let's get it filed. Is everyone okay, and is the vehicle drivable?
Caller: Everyone's fine. It drives, but the bumper is dented.
Agent: Glad you're safe. I've opened your claim and scheduled an adjuster call for tomorrow at 10 AM.
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URL: https://speechify.ai/industries/agents/real-estate
Title: Voice agents for real estate
From lead qualification and showing scheduling to tenant support and maintenance requests, SpeechifyAI voice agents automate every phone-driven workflow across brokerages, property management, and mortgage.
From lead qualification and showing scheduling to tenant support and maintenance requests, SpeechifyAI voice agents automate every phone-driven workflow across brokerages, property management, and mortgage.
Benefits:
- Never miss a lead — 24/7 voice agents that answer every inquiry, qualify buyers and renters, capture contact details, and schedule showings — even at 10 PM on a Sunday.
- Scale property management — Automate tenant calls for maintenance requests, lease renewals, rent reminders, and move-in/move-out coordination across hundreds of units.
- Built for real estate workflows — Connects to your CRM, property management system, and calendar through tool calling and webhooks. Agents follow your scripts, qualification criteria, and routing rules.
Workflows:
- Lead capture and qualification — Qualify every inbound and outbound lead on budget, timeline, and preferences. Route hot leads to agents instantly with full context.
- Property and tenant management — Automate maintenance intake, lease renewals, rent reminders, and move-in/move-out coordination across your entire portfolio.
- Mortgage and lending support — Pre-qualify borrowers, explain loan products, collect application details, and schedule loan officer consultations automatically.
Use cases: Lead qualification and capture; Showing scheduling and confirmation; Tenant maintenance requests; Lease renewals and rent reminders; Mortgage and lending inquiries
Sample call:
Caller: Is the two-bedroom on Maple Street still available?
Agent: It is. Are you looking to rent, and when would you want to move in?
Caller: Renting, for my family — ideally August 1st.
Agent: Perfect. I can book a showing Saturday at 11 AM and text you the application link.
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URL: https://speechify.ai/industries/agents/financial-services
Title: Voice agents for financial services
From account inquiries and loan origination to claims processing, collections, and compliance verification, SpeechifyAI voice agents automate customer and advisor workflows without sacrificing financial trust.
From account inquiries and loan origination to claims processing, collections, and compliance verification, SpeechifyAI voice agents automate customer and advisor workflows without sacrificing financial trust.
Benefits:
- Improve customer satisfaction — Emotionally aware agents guide customers through sensitive financial conversations — account disputes, claims, and payment difficulties — with empathy and precision.
- Reduce cost per resolution — Automate balance checks, payment reminders, transaction lookups, and status updates. Free your team for complex advisory conversations.
- Built for financial compliance — SOC 2 Type II certified, with end-to-end encryption.
Workflows:
- Inbound support and account service — Resolve account inquiries, process transactions, and update customer information in real time.
- Outbound sales and collections — Proactive outreach for payment reminders, loan offers, renewal notices, and collections with compliant workflows.
- Lead qualification and conversion — Screen and qualify prospects for financial products, collect application data, and route to licensed advisors.
Use cases: Retail banking and neobanks; Insurance carriers and brokers; Wealth management and advisory; Lending and mortgage; Payments and fintech
Sample call:
Caller: My card was declined this morning and I don't know why.
Agent: I can help with that. For security, could you confirm the last four digits of the card?
Caller: Sure — 4417.
Agent: Thank you. There was a temporary hold from a duplicate charge — I've released it, so the card works now.
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URL: https://speechify.ai/industries/agents/retail
Title: Voice agents for retail and e-commerce
From order status and returns to product questions and post-purchase support, SpeechifyAI voice agents handle the call volume that spikes every season without adding seats.
From order status and returns to product questions and post-purchase support, SpeechifyAI voice agents handle the call volume that spikes every season without adding seats.
Benefits:
- Handle seasonal spikes — Answer order, shipping, and returns questions around the clock, so peak-season volume does not overwhelm a fixed support team.
- Recover carts and sales — Place outbound calls for abandoned carts, back-in-stock alerts, and post-purchase follow-up that bring shoppers back.
- Grounded in your catalog — The knowledge base answers product and policy questions from your own content, so replies match what is actually on the shelf.
Workflows:
- Order status and returns — Look up orders, explain shipping timelines, and start returns or exchanges through tool calls into your commerce systems.
- Product and stock questions — Answer sizing, availability, and compatibility questions from the catalog, and check live stock through a tool call.
- Outbound win-back — Reach shoppers for abandoned carts, restock alerts, and loyalty offers, with each contact's history kept across calls.
Use cases: Online retailers and marketplaces; Direct-to-consumer brands; Omnichannel retail chains; Subscription commerce; Post-purchase support teams
Sample call:
Caller: I ordered a jacket last week and it still hasn't shipped.
Agent: Let me check. Your order shipped this morning and arrives Thursday. Want the tracking link by text?
Caller: Yes please.
Agent: Sent. Anything else, like a size exchange or a return label ready just in case?
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URL: https://speechify.ai/industries/agents/education
Title: Voice agents for education
From admissions and enrollment to financial aid and student services, SpeechifyAI voice agents answer the repetitive questions that flood a school's phone lines every term.
From admissions and enrollment to financial aid and student services, SpeechifyAI voice agents answer the repetitive questions that flood a school's phone lines every term.
Benefits:
- Answer every applicant — Handle admissions, enrollment, and deadline questions at any hour, so prospective students get answers instead of voicemail.
- Free up student services — Automate routine questions about schedules, aid, and records, so staff focus on the students who need real help.
- Grounded in your policies — Answers come from your own handbook and program pages, so deadlines and requirements match what your office actually publishes.
Workflows:
- Admissions and enrollment — Answer application, deadline, and program questions, and route serious prospects to an advisor with context attached.
- Financial aid and records — Explain aid steps, verify status through tool calls, and guide students through forms without a hold queue.
- Outbound reminders — Call students about deadlines, missing documents, and registration windows, with per-student history kept across terms.
Use cases: Universities and colleges; K-12 districts; Online learning platforms; Admissions and enrollment offices; Student services and financial aid
Sample call:
Caller: What's the deadline to submit my financial aid form?
Agent: For the fall term it's June 30th. I can also check whether we've received your form so far.
Caller: Yes, can you check?
Agent: We have your application but not the aid form yet. Want me to text you the link and a reminder next week?
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URL: https://speechify.ai/industries/agents/government
Title: Voice agents for government and public services
From benefits and permits to appointments and status checks, SpeechifyAI voice agents help agencies answer residents at scale while keeping compliance and access front of mind.
From benefits and permits to appointments and status checks, SpeechifyAI voice agents help agencies answer residents at scale while keeping compliance and access front of mind.
Benefits:
- Serve residents around the clock — Answer benefits, permit, and service questions at any hour and in the resident's preferred language, without longer queues.
- Reduce call center load — Automate status checks, appointment booking, and routine questions so staff handle the cases that genuinely need a person.
- Built for compliance — Deterministic workflows enforce the required disclosures and steps, and every call can be recorded and transcribed for review.
Workflows:
- Benefits and eligibility — Explain programs, check eligibility through tool calls, and guide residents through applications step by step.
- Permits, appointments, and status — Book appointments, check permit and case status, and send confirmations without a resident waiting on hold.
- Compliant, auditable calls — Scripted disclosures run where the law requires them, and transcripts are available for oversight and record-keeping.
Use cases: State and local agencies; Benefits and social services; Permits and licensing; 311 and resident services; Public health lines
Sample call:
Caller: I want to check the status of my permit application.
Agent: I can help with that. Can you give me your application number to look it up?
Caller: It's 4821-C.
Agent: Your permit is approved and mailing this week. I can text you the confirmation and expected arrival date.
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URL: https://speechify.ai/industries/agents/hospitality
Title: Voice agents for hospitality
From reservations and guest requests to reminders and post-stay follow-up, SpeechifyAI voice agents keep every call answered so guests never reach a busy line.
From reservations and guest requests to reminders and post-stay follow-up, SpeechifyAI voice agents keep every call answered so guests never reach a busy line.
Benefits:
- Never miss a booking — Answer reservation calls at any hour, check live availability through tool calls, and confirm on the spot.
- Handle guest requests — Take service requests, answer amenity and policy questions, and route the urgent ones to staff with context.
- Grounded in your property — Answers come from your own property details, so hours, amenities, and policies match what guests actually get.
Workflows:
- Reservations and availability — Check availability, book and modify reservations, and confirm by text through your booking system.
- Guest requests and questions — Take housekeeping and service requests, answer amenity questions, and escalate the ones that need a person.
- Reminders and follow-up — Send booking confirmations and pre-arrival reminders, and follow up after the stay for reviews and rebooking.
Use cases: Hotels and resorts; Restaurants and reservations; Vacation rentals; Travel and tour operators; Event and venue booking
Sample call:
Caller: Do you have a room for two nights this weekend?
Agent: We do. A king room is open Friday and Saturday at $180 a night. Want me to hold it?
Caller: Yes, book it.
Agent: Booked for two nights. I'll text your confirmation and check-in details now.
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URL: https://speechify.ai/industries/agents/logistics
Title: Voice agents for logistics and delivery
From delivery windows and tracking to driver coordination and exception handling, SpeechifyAI voice agents keep shipments moving without tying up a dispatch desk.
From delivery windows and tracking to driver coordination and exception handling, SpeechifyAI voice agents keep shipments moving without tying up a dispatch desk.
Benefits:
- Coordinate deliveries at scale — Confirm delivery windows, reschedule stops, and answer tracking questions across thousands of shipments a day.
- Handle exceptions fast — Call recipients about failed deliveries, missing details, and reschedules, with each shipment's history kept across calls.
- Grounded in your systems — Tracking and status come from live tool calls into your TMS, so what the agent says matches what the system shows.
Workflows:
- Tracking and delivery windows — Answer where-is-my-order calls, confirm and adjust delivery windows, and send updated ETAs by text.
- Exception and reschedule handling — Call recipients about failed or delayed deliveries, collect the missing detail, and rebook the stop.
- Driver and partner coordination — Place outbound calls to confirm pickups, relay changes, and capture status without a dispatcher on every line.
Use cases: Parcel and last-mile delivery; Freight and trucking; Third-party logistics (3PL); Field service dispatch; Warehouse and fulfillment
Sample call:
Caller: My package was supposed to arrive today and it didn't.
Agent: Let me check. It's on the truck and rescheduled for tomorrow between 9 and noon. Does that window work?
Caller: Can you make it afternoon instead?
Agent: Done — rescheduled for 1 to 4 PM tomorrow. I'll text you the updated tracking.
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URL: https://speechify.ai/text-to-speech-api
Title: Text-to-Speech API: ~430ms Audio from Simba 3.2
The text-to-speech API with production TTS quality. ~430ms first byte, 900+ voices, from $6 per 1M characters.
The text-to-speech API with production-grade voice quality, from $6 per 1M characters.
Key facts:
- Independently evaluated on the Artificial Analysis TTS leaderboard
- ~430ms first byte
- POST /v1/audio/speech and POST /v1/audio/stream
- 5 audio formats, 13 emotions, SSML
- From $6 per 1M characters
Q: What is a text-to-speech API?
A: A text-to-speech API turns written text into spoken audio over a network request. You send text and a voice choice; it returns audio, either as a complete file or as a stream. SpeechifyAI's API adds SSML control, emotion, voice cloning, and speech marks, on a model evaluated on independent blind-listening leaderboards.
Q: How fast is it?
A: Simba 3.2 produces first byte in ~430ms and is streaming-native, so audio starts playing before the full clip is generated. That makes it fast enough for realtime apps like voice agents and live captioning.
Q: What does it cost?
A: Per character: from $6 per 1M on Scale, $8 on Pro, $10 on Starter, with no credit conversion or token math. The Free plan includes 500,000 characters a month with commercial use.
Q: Which audio formats are supported?
A: Five: wav, mp3, ogg, aac, and pcm. The batch endpoint returns a full file including WAV; the streaming endpoint returns chunked mp3, ogg, aac, pcm, or u-law for telephony.
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URL: https://speechify.ai/build
Title: SpeechifyAI Build, One API for Text-to-Speech and Cloning
One developer API for voice AI: text-to-speech and voice cloning on the Simba models, from $6 per 1M characters. One key, one bill, 500K free.
The developer API for voice AI: text to speech and voice cloning on the same speech stack that powers Speechify, exposed as building blocks you can compose.
Key facts:
- Text to speech
- Voice cloning
- ~430ms first byte
- One key, one bill
Q: What is SpeechifyAI Build?
A: The developer API for voice AI, organized as building blocks. Text to speech and voice cloning are available today: generate lifelike speech, stream long-form audio, and clone a voice from a short sample, all on one API, one key, and one bill.
Q: What can I build with it today?
A: Anything that needs synthesized speech: narration, agents, accessibility, captions, IVR, dubbing. Text to speech and voice cloning are live now on one key and one bill.
Q: Which model should I use?
A: Simba 3.2 for English, streaming-native with the lowest time-to-first-byte. Simba 3.0 for English plus six European languages: set the language and one model id covers them all, with voice cloning. Coverage of the full 30+ language set is available on request.
Q: How much does it cost?
A: Text to speech is from $6 per 1M characters on Scale, $8 on Pro, $10 on Starter, billed per character with no credits or token math. The Free plan includes 500K characters a month with commercial use.
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URL: https://speechify.ai/realtime-tts
Title: Realtime Text-to-Speech — ~430ms with Simba 3.2
Realtime text-to-speech for live apps. Simba 3.2 is independently evaluated on Artificial Analysis with ~430ms first byte.
Realtime text-to-speech with production-grade voice quality, fast enough for live conversation.
Key facts:
- Simba 3.2 is streaming-native, ~430ms first byte
- Independently evaluated on the Artificial Analysis TTS leaderboard
- Powers realtime voice agents and live captions
Q: What is realtime text-to-speech?
A: Realtime text-to-speech generates audio fast enough to use in a live application, where a person is waiting to hear the reply. The key metric is time-to-first-byte: how quickly audio starts. Simba 3.2 is streaming-native with ~430ms first byte, which keeps live conversations feeling immediate.
Q: Is it fast enough for a voice agent?
A: Yes. Text-to-speech first-byte time is the last stage before a caller hears a reply, and Simba 3.2's ~430ms start leaves room for transcription and reasoning inside the per-turn budget. It is the TTS behind SpeechifyAI's own voice agents.
Q: How do I get the lowest latency?
A: Use the streaming endpoint with model simba-3.2, and start playback as the first chunks arrive rather than waiting for the full clip. Streaming plus a streaming-native model is what keeps perceived latency low.
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URL: https://speechify.ai/streaming-tts
Title: Streaming Text-to-Speech — Chunked Audio, Instant Playback
Streaming text-to-speech via chunked HTTP. First bytes in ~430ms, up to 20,000 characters per request, playback in browser or telephony.
Streaming text-to-speech that plays as it generates, in the browser or over the phone.
Key facts:
- POST /v1/audio/stream, chunked HTTP
- Up to 20,000 characters per request
- mp3, ogg, aac, pcm, u-law formats
- ~430ms first byte with Simba 3.2
- #3 on the Artificial Analysis TTS leaderboard, the lowest-priced model in its top 10; best value on Datapoint's human-preference benchmark
Q: What is streaming text-to-speech?
A: Streaming text-to-speech sends audio back in chunks over a single HTTP connection as it is generated, instead of returning one finished file. Your app decodes and plays the bytes as they arrive, so the first sound reaches the listener in ~430ms rather than after the whole clip renders.
Q: Which formats does streaming support?
A: mp3 (audio/mpeg), ogg, aac, pcm at 24kHz mono, and u-law for telephony. WAV is not available on streaming; use the batch speech endpoint for WAV. You choose the format with the Accept header.
Q: How much text can I stream per request?
A: Up to 20,000 characters per request on the streaming endpoint. For longer content, chunk the text and stream the pieces in sequence to keep playback continuous.
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URL: https://speechify.ai/tts/accessibility-reader
Title: AI Accessibility Reader — Read Any Content Aloud
Add a read-aloud accessibility feature with AI text-to-speech. Natural voices, 30+ languages, low-latency streaming from $6 per 1M.
Make any content readable aloud with natural voices your users trust.
Key facts:
- ~430ms first-byte streaming
- 900+ natural voices, 30+ languages
- Speech marks for word-highlight sync
- From $6 per 1M characters
Q: Can I add a read-aloud feature with text-to-speech?
A: Yes. Text-to-speech powers a read-aloud accessibility feature that speaks page content, articles, or documents in natural voices. Low-latency streaming starts playback quickly, and speech marks let you highlight each word as it is read for a follow-along experience.
Q: Can I highlight words as they are read?
A: Yes. Speech marks return word-level timing, so the interface can highlight each word in sync with the audio. That follow-along highlight helps readers with dyslexia and low vision track the content.
Q: How quickly does playback start?
A: Streaming returns the first audio in ~430ms, so a reader hears speech almost immediately after pressing play rather than waiting for a full render.
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URL: https://speechify.ai/tts/audiobook-narration
Title: AI Audiobook Narration — Turn Books into Audio
Narrate audiobooks with AI text-to-speech. Long-form synthesis, 900+ voices, SSML pacing, and per-character pricing from $6 per 1M.
Turn a manuscript into a finished audiobook with a consistent, natural voice.
Key facts:
- Long-form synthesis with chunking and stitching
- 900+ voices, 30+ languages
- SSML controls pacing, emphasis, and pauses
- From $6 per 1M characters
Q: Can AI narrate a full audiobook?
A: Yes. A text-to-speech API narrates book-length text by chunking chapters, synthesizing each in a consistent voice, and stitching the audio together. SSML controls pacing, emphasis, and pauses so the narration reads naturally rather than flat, and per-character pricing keeps a full book affordable.
Q: How do I keep the voice consistent across chapters?
A: Use the same voice ID for every chunk. Because the voice is deterministic, chapter one and chapter twenty sound like the same narrator. For a personal or branded narrator, clone a voice once and reuse it across the whole book.
Q: What does it cost to narrate a book?
A: Text-to-speech is billed per character, from $6 per 1M on Scale. A typical novel is a few hundred thousand characters, so a full audiobook costs a few dollars of synthesis rather than a studio session.
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URL: https://speechify.ai/tts/e-learning
Title: AI Voiceover for E-Learning — Narrate Courses at Scale
Narrate e-learning courses with AI text-to-speech. Consistent voices, 30+ languages, speech marks for captions, from $6 per 1M characters.
Narrate and localize course content at scale, with captions built in.
Key facts:
- Consistent voices across a course library
- 30+ languages for localization
- Speech marks power synced captions
- From $6 per 1M characters
Q: Can I use AI narration for e-learning?
A: Yes. Text-to-speech narrates course modules from a script, in a consistent voice across the whole library. It localizes into 30+ languages by re-synthesizing the script, and speech marks provide word-level timing for synced captions that meet accessibility requirements.
Q: How do I add captions?
A: Request speech marks with the narration. They return word-level timestamps that map text to audio, which you convert to WebVTT or SRT for synced, accessible captions without manual transcription.
Q: Can I localize a course?
A: Yes. Re-synthesize the script with a multilingual voice to produce the same course in another language. Because it is text-driven, adding a language is a synthesis job, not a re-shoot.
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URL: https://speechify.ai/tts/game-dialogue
Title: AI Game Dialogue — Voice NPCs at Scale
Voice game characters and NPCs with AI text-to-speech. 900+ voices, emotion control, cloning, and per-character pricing from $6 per 1M.
Voice thousands of lines and characters without booking a cast.
Key facts:
- 900+ voices for a varied cast
- Emotion control across 13 styles
- Voice cloning for signature characters
- From $6 per 1M characters
Q: Can I voice game characters with AI?
A: Yes. Text-to-speech voices NPCs and characters from a dialogue script. With 900+ voices you build a varied cast, emotion control across 13 styles gives lines the right delivery, and cloning creates signature voices for recurring characters, all without a casting session.
Q: Can I generate dialogue dynamically?
A: Yes. Synthesize lines at runtime for procedural or player-driven dialogue, so a character can speak text that did not exist at ship time. Low-latency streaming keeps generated speech responsive in-game.
Q: How does it handle a large cast?
A: Assign a distinct voice ID per character to keep a large cast consistent across thousands of lines. Changing or adding dialogue is a re-synthesis, not a re-record with the original actor.
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URL: https://speechify.ai/tts/ivr-messages
Title: AI IVR Messages — Natural Phone Prompts from Text
Generate IVR and phone prompts with AI text-to-speech. Natural voices, telephony formats, and instant updates from $6 per 1M characters.
Generate natural phone prompts from text, updated in seconds, not studio sessions.
Key facts:
- u-law telephony format for phone systems
- 900+ voices, 30+ languages
- Update prompts instantly by changing text
- From $6 per 1M characters
Q: Can I generate IVR prompts with text-to-speech?
A: Yes. Text-to-speech generates phone menu prompts, hold messages, and announcements from text, in the telephony audio formats phone systems expect. Changing a prompt is editing text and re-synthesizing, not booking a voice actor for a re-record.
Q: What audio format do phone systems need?
A: Most telephony expects u-law at 8kHz. The streaming and speech endpoints produce u-law output, so the generated prompts drop straight into an IVR or PBX without a conversion step.
Q: How fast can I update a prompt?
A: Immediately. Edit the text, synthesize, and deploy. A seasonal message, a changed hours announcement, or a new menu option takes minutes instead of scheduling studio time.
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URL: https://speechify.ai/tts/notifications
Title: AI Voice Notifications — Spoken Alerts from Text
Turn alerts into spoken voice notifications with AI text-to-speech. Low-latency streaming, 30+ languages, from $6 per 1M characters.
Turn dynamic alerts into clear spoken notifications in real time.
Key facts:
- ~430ms first-byte streaming
- 900+ voices, 30+ languages
- Synthesize dynamic text at runtime
- From $6 per 1M characters
Q: Can I generate voice notifications from text?
A: Yes. Text-to-speech turns dynamic alerts into spoken notifications at runtime, reading whatever the alert text contains: a delivery update, an appointment reminder, or a system warning. Low-latency streaming keeps the spoken alert timely rather than delayed.
Q: Can it speak dynamic content?
A: Yes. Because the notification is synthesized from live text, it can speak values that change per event: a name, a time, an amount. There is no fixed set of pre-recorded clips to maintain.
Q: Can notifications be multilingual?
A: Yes. Synthesize the alert with a multilingual voice to deliver the same notification in a user's preferred language across 30+ languages.
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URL: https://speechify.ai/tts/podcast-generation
Title: AI Podcast Generation — Scripts to Audio
Generate podcasts from scripts with AI text-to-speech. Multiple voices, emotion control, and long-form audio from $6 per 1M characters.
Turn a script into a produced podcast with distinct voices and natural delivery.
Key facts:
- Multiple voices for multi-speaker shows
- Emotion control across 13 styles
- Long-form synthesis
- From $6 per 1M characters
Q: Can I generate a podcast with AI voices?
A: Yes. A text-to-speech API turns a script into podcast audio, assigning different voices to different speakers for interview or co-host formats. Emotion control keeps the delivery lively rather than flat, and long-form synthesis handles full episodes.
Q: Can it do multiple hosts?
A: Yes. Assign a distinct voice ID to each speaker in the script and synthesize their lines separately, then interleave them. The result is a multi-voice show where each host sounds like a different person.
Q: How much does an episode cost?
A: Per character, from $6 per 1M on Scale. A 30-minute episode script is a modest character count, so producing an episode costs a few dollars of synthesis instead of studio time.
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URL: https://speechify.ai/tts/video-voiceover
Title: AI Video Voiceover — Narration for Any Video
Add AI voiceover to videos with text-to-speech. 900+ voices, emotion control, cloning, and per-character pricing from $6 per 1M.
Add professional narration to any video from a script, no studio required.
Key facts:
- 900+ voices, emotion control
- Voice cloning for a signature narrator
- Speech marks to sync narration to visuals
- From $6 per 1M characters
Q: Can I add AI voiceover to a video?
A: Yes. Text-to-speech generates narration from a script that you lay over the video. With 900+ voices, emotion control, and voice cloning, the narration can match the tone of the piece, and speech marks help sync the audio to on-screen visuals.
Q: Can I sync narration to the visuals?
A: Speech marks return word-level timestamps, so you know exactly when each word is spoken. That lets you align cuts, captions, and on-screen text to the narration without manual scrubbing.
Q: Can I use my own voice?
A: Yes. Clone a voice once and use it as the narrator across every video, so a channel or brand keeps a consistent signature voice without recording each script.
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URL: https://speechify.ai/tts/emotion-control
Title: Emotion Control for AI Voices — 13 Speaking Styles
Set the emotional tone of AI speech across 13 styles. Make text-to-speech sound warm, energetic, or calm to fit the moment.
Match the delivery to the moment with selectable emotional styles.
Key facts:
- 13 selectable emotional styles
- Warm, energetic, calm, and more
- Set per request
- Pairs with SSML for fine control
Q: Can AI text-to-speech convey emotion?
A: Yes. Emotion control sets the emotional tone of the synthesized speech across 13 styles such as warm, energetic, and calm. You pick a style per request so the delivery fits the moment, an upbeat ad or a measured tutorial, rather than a single neutral read.
Q: How many emotional styles are there?
A: There are 13 selectable styles. You choose one per synthesis request to shape the overall tone, and combine it with SSML for finer control of pacing and emphasis within that tone.
Q: Does emotion control work with SSML?
A: Yes. Emotion control sets the broad tone while SSML handles fine-grained pacing, pauses, and emphasis. Using both gives you tone plus rhythm in the same request.
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URL: https://speechify.ai/tts/multilingual
Title: Multilingual Text-to-Speech — 30+ Languages
Synthesize speech in 30+ languages with AI text-to-speech. Localize content with natural multilingual voices in one API.
Speak to a global audience with natural voices in 30+ languages.
Key facts:
- 30+ languages supported
- Natural multilingual voices
- Localize by re-synthesizing text
- One API for every language
Q: How many languages does the text-to-speech support?
A: The API synthesizes speech in 30+ languages with natural multilingual voices. You localize content by re-synthesizing the translated text through the same API, so adding a language is a synthesis job rather than a separate integration.
Q: How do I localize existing content?
A: Translate the text, then re-synthesize it with a voice for the target language. Because the content is text-driven, an audiobook, course, or set of prompts can be localized without re-recording anything.
Q: Is it one API for all languages?
A: Yes. The same endpoint handles every supported language, so you do not integrate a separate service per language. You select a voice and synthesize.
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URL: https://speechify.ai/tts/speech-marks
Title: Speech Marks — Word-Level Timing for TTS
Get word-level timestamps with AI text-to-speech. Speech marks power synced captions and word highlighting in the Speechify API.
Know exactly when each word is spoken for captions and highlighting.
Key facts:
- Word-level timestamps with synthesis
- Powers synced captions (WebVTT, SRT)
- Enables read-along word highlighting
- Returned alongside audio
Q: What are speech marks in text-to-speech?
A: Speech marks are word-level timestamps returned alongside the synthesized audio. They tell you exactly when each word is spoken, which you use to build synced captions or to highlight words in a read-along interface as they are read.
Q: How do I make synced captions?
A: Request speech marks with the synthesis, then map the word timestamps to a caption format such as WebVTT or SRT. This produces accurate synced captions without a separate transcription step.
Q: Can I highlight words as they are read?
A: Yes. Speech marks give the timing for each word, so a read-along interface can highlight the current word in sync with the audio, an accessibility affordance for dyslexia and low vision.
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URL: https://speechify.ai/tts/ssml
Title: SSML Text-to-Speech — Control Pacing and Emphasis
Shape AI speech with SSML: control rate, pitch, pauses, and emphasis. Fine-grained prosody control in the Speechify text-to-speech API.
Direct the delivery of synthesized speech with standard SSML markup.
Key facts:
- Standard SSML tags for prosody, breaks, emphasis
- Control rate, pitch, and volume
- Insert precise pauses
- Works across the voice catalog
Q: What is SSML in text-to-speech?
A: SSML, Speech Synthesis Markup Language, is a standard XML markup that directs how text is spoken. You wrap text in tags to control rate, pitch, and volume, insert pauses, and add emphasis, so synthesized speech follows the pacing and delivery you intend instead of a flat default read.
Q: What can I control with SSML?
A: Prosody tags set speaking rate, pitch, and volume; break tags insert pauses of a chosen length; emphasis tags stress specific words. Together they turn a monotone render into a delivery with rhythm and emphasis.
Q: Does SSML work with any voice?
A: SSML markup applies across the voice catalog, so you can shape pacing and emphasis regardless of which voice you choose for the synthesis.
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URL: https://speechify.ai/tts/streaming
Title: Streaming Text-to-Speech — ~430ms First Byte
Stream AI speech with ~430ms first-byte latency. Start playback instantly for real-time voice apps with the Speechify TTS API.
Start playback in ~430ms for responsive, real-time voice.
Key facts:
- ~430ms first-byte latency
- Chunked audio streaming
- u-law and PCM output
- Built for real-time apps
Q: What is streaming text-to-speech?
A: Streaming text-to-speech returns audio in chunks as it is generated instead of waiting for the full render. The first audio arrives in ~430ms, so playback starts almost immediately, which is what real-time apps like voice agents and read-aloud features need.
Q: How low is the latency?
A: First-byte latency is ~430ms, so a listener hears speech almost as soon as the request is sent. That responsiveness is the difference between a natural conversation and an awkward pause.
Q: What output formats does streaming support?
A: Streaming supports formats including u-law for telephony and PCM, so the audio drops into phone systems, voice agents, and media pipelines without a conversion step.
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URL: https://speechify.ai/tts/voice-catalog
Title: Voice Catalog — 900+ AI Voices
Choose from 900+ AI voices across 30+ languages. Browse the Speechify text-to-speech voice catalog for any use case.
Find the right voice from a library of 900+ across 30+ languages.
Key facts:
- 900+ voices
- 30+ languages
- Select by voice ID
- Deterministic, consistent output
Q: How many voices are in the catalog?
A: The catalog has 900+ voices across 30+ languages. You select a voice by its ID in the synthesis request, and because output is deterministic, the same voice ID sounds identical across every call, which keeps long-form projects consistent.
Q: How do I choose a voice?
A: Browse the catalog by language and style, pick a voice, and pass its voice ID to the API. For a custom or branded voice beyond the catalog, clone one and use its ID the same way.
Q: Are voices consistent across requests?
A: Yes. A given voice ID is deterministic, so chapter one and chapter twenty, or episode one and episode fifty, sound like the same voice with no drift.
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URL: https://speechify.ai/how-to-implement-tts
Title: How to Implement Text-to-Speech: A 2026 Guide
Implement text-to-speech in your app: get an API key, choose a voice, synthesize text, and stream audio. A step-by-step developer guide.
Add text-to-speech to your app in a few steps. Here is the path.
Key facts:
- REST API with Python and TypeScript SDKs
- Authenticate with SPEECHIFY_API_KEY
- Synthesize or stream audio
- Add SSML and speech marks as needed
Q: How do I implement text-to-speech?
A: Get an API key, install the SDK for your language, pick a voice ID, and call the synthesis endpoint with your text. You receive audio back. For real-time playback use the streaming endpoint, which returns the first audio in ~430ms. Add SSML for pacing and speech marks for captions when you need them.
Q: Which languages have SDKs?
A: There are official SDKs for Python (speechify-api) and TypeScript (@speechify/api), and a REST API you can call from any language. Authenticate with a SPEECHIFY_API_KEY environment variable.
Q: Should I use file synthesis or streaming?
A: Use file synthesis when you need a complete audio file, such as an audiobook chapter or a pre-rendered prompt. Use streaming when playback must start immediately, such as a voice agent reply or a read-aloud button, where ~430ms first-byte latency matters.
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URL: https://speechify.ai/tts-latency
Title: Text-to-Speech Latency: What Matters and How to Cut It
TTS latency is the delay before speech plays. Learn what first-byte latency means and how streaming keeps it at ~430ms for real-time apps.
Latency is the wait before speech starts. Here is what drives it and how to cut it.
Key facts:
- First-byte latency is the key metric
- Streaming reaches ~430ms first byte
- File synthesis waits for the full render
- Matters most for real-time apps
Q: What is text-to-speech latency?
A: TTS latency is the delay between sending text and hearing speech. The metric that matters for live apps is first-byte latency: how long until the first chunk of audio arrives. With streaming, first-byte latency is ~430ms, so playback starts almost immediately rather than after the whole clip renders.
Q: How do I reduce TTS latency?
A: Use the streaming endpoint instead of file synthesis. Streaming returns audio in chunks as it generates, so the client plays the start while the rest is still being produced. That drops the perceived wait to the ~430ms first-byte time instead of the full render time.
Q: When does latency matter most?
A: It matters most in real-time experiences: voice agents, live read-aloud, and interactive notifications. In those, any wait before speech feels like a broken pause. For pre-rendered content like an audiobook, total render time matters more than first-byte latency.
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URL: https://speechify.ai/tts-pricing-guide
Title: Text-to-Speech Pricing: How TTS Costs Are Calculated
TTS is billed per character of text, from $6 per 1M on Scale. Learn how character-based pricing works and how to estimate your cost.
TTS is billed per character. Here is how to read the pricing and estimate cost.
Key facts:
- Billed per character of input text
- From $6 per 1M characters on Scale
- Predictable and linear with usage
- Same model for files and streaming
Q: How is text-to-speech priced?
A: Text-to-speech is billed per character of input text, starting from $6 per 1M characters on the Scale plan. Cost is linear with usage: double the text, double the cost. That makes it easy to estimate, since you can count the characters you plan to synthesize.
Q: How do I estimate my TTS cost?
A: Count the characters in the text you will synthesize and multiply by the per-character rate. A few hundred thousand characters, roughly a full book, costs a few dollars of synthesis at $6 per 1M. There is no separate charge for choosing a different voice or language.
Q: Does streaming cost more than file synthesis?
A: No. Pricing is based on characters of input text, so streaming and file synthesis of the same text cost the same. The delivery mode does not change the price.
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URL: https://speechify.ai/tts-vs-voice-cloning
Title: Text-to-Speech vs Voice Cloning: What Is the Difference?
Text-to-speech uses catalog voices; voice cloning recreates a specific voice from a sample. Here is how they differ and when to use each.
Both turn text into speech. The difference is whose voice does the talking.
Key facts:
- TTS uses catalog voices; cloning recreates a specific voice
- Cloning needs a voice sample and consent
- Both synthesize from text the same way
- Cloned voices work on select models
Q: What is the difference between text-to-speech and voice cloning?
A: Text-to-speech synthesizes speech using voices from a catalog. Voice cloning first recreates a specific person's voice from an audio sample, then synthesizes speech in that voice. The synthesis step is the same; the difference is whether the voice is a stock catalog voice or a recreation of a particular voice.
Q: When should I use voice cloning instead of TTS?
A: Use a catalog voice when any suitable natural voice will do, which covers most narration, prompts, and notifications. Use voice cloning when the voice itself matters: a branded narrator, an author reading their own book, or a consistent character voice. Cloning requires a sample and the speaker's consent.
Q: Do cloned voices work everywhere TTS does?
A: Cloned voices are supported on select synthesis models rather than every voice in the catalog. Once created, a cloned voice is used by its voice ID in the same synthesis call as any catalog voice.
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URL: https://speechify.ai/what-is-tts
Title: What Is Text-to-Speech? A Plain Definition for 2026
Text-to-speech converts written text into natural spoken audio using AI. Here is how it works, what it is used for, and how to build with it.
Text-to-speech turns written text into natural spoken audio. Here is the plain definition.
Key facts:
- Converts text to audio with AI voices
- 900+ voices, 30+ languages
- Streaming for real-time playback
- Billed per character
Q: What is text-to-speech?
A: Text-to-speech, or TTS, is technology that converts written text into spoken audio. Modern TTS uses AI models to produce natural-sounding voices, so the output reads like a person rather than a robotic monotone. You send text to an API and get back an audio file or a live audio stream.
Q: How does text-to-speech work?
A: An AI model takes your text and generates a waveform that sounds like a human voice speaking it. You choose a voice and language, optionally shape delivery with SSML and emotion control, and receive audio. Streaming mode returns the first audio in ~430ms so playback can start immediately.
Q: What is text-to-speech used for?
A: Common uses are audiobook and podcast narration, e-learning voiceover, IVR and phone prompts, accessibility read-aloud features, video voiceover, game dialogue, and spoken notifications. Anywhere text needs to be heard rather than read, TTS provides the voice.
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URL: https://speechify.ai/industries/build/tts/corporate-training
Title: Text-to-Speech for Corporate Training
Produce and update corporate training audio with AI text-to-speech. Fast revisions, consistent voices, 30+ languages, from $6 per 1M.
Keep training content current without re-recording every revision.
Key facts:
- Consistent narration for training modules
- Update content by editing text
- 30+ languages for global teams
- From $6 per 1M characters
Q: How is text-to-speech used for corporate training?
A: Learning and development teams use text-to-speech to narrate onboarding, compliance, and skills training from a script. The advantage is revision speed: when a policy changes, you edit the text and re-synthesize instead of re-booking a narrator, and you localize for global teams in 30+ languages.
Q: How fast can I update a module?
A: Immediately. Because narration is generated from text, a changed policy or product detail is a text edit and a re-synthesis, so training stays current without scheduling a re-record.
Q: Can I train a global workforce?
A: Yes. Re-synthesize the training script with a multilingual voice across 30+ languages to deliver the same module to teams in their own language.
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URL: https://speechify.ai/industries/build/tts/e-learning
Title: Text-to-Speech for E-Learning Platforms
Power an e-learning platform with AI text-to-speech: course narration, captions, and localization in 30+ languages from $6 per 1M characters.
Give every course a consistent narrator and built-in captions.
Key facts:
- Consistent narration across a course library
- Speech marks for synced captions
- 30+ languages for localization
- From $6 per 1M characters
Q: How does an e-learning platform use text-to-speech?
A: An e-learning platform uses text-to-speech to narrate every course from its script in a consistent voice, generate synced captions from speech marks, and localize content into 30+ languages. This lets a platform offer narrated, accessible, multilingual courses without a studio for each one.
Q: Can I add captions automatically?
A: Yes. Request speech marks with the narration to get word-level timing, then convert to WebVTT or SRT for synced captions across the whole course library, with no manual transcription.
Q: How do I localize a course library?
A: Re-synthesize each course script with a multilingual voice for the target language. Because courses are text-driven, localizing a library is a batch synthesis job rather than re-recording every module.
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URL: https://speechify.ai/industries/build/tts/education
Title: Text-to-Speech for Education — Accessible Learning Audio
Add read-aloud and narration to education products with AI text-to-speech. Accessible audio, 30+ languages, from $6 per 1M characters.
Make learning materials audible and accessible for every student.
Key facts:
- Read-aloud with word highlighting via speech marks
- 900+ natural voices, 30+ languages
- Low-latency streaming for interactive use
- From $6 per 1M characters
Q: How is text-to-speech used in education?
A: Education products use text-to-speech for read-aloud of lessons and texts, narration of course material, and accessibility support for students with dyslexia or low vision. Speech marks drive word highlighting so students follow along, and 30+ languages support multilingual classrooms.
Q: Does it support accessibility requirements?
A: Yes. Natural read-aloud with synced word highlighting is a core accessibility affordance, and speech marks make captions and follow-along highlighting straightforward. This helps meet accessibility obligations for learning materials.
Q: Can it help multilingual classrooms?
A: Yes. Synthesize the same material in a student's language with a multilingual voice across 30+ languages, so learners access content in the language they understand best.
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URL: https://speechify.ai/industries/build/tts/gaming
Title: Text-to-Speech for Gaming — Voice a Whole World
Voice NPCs and dynamic dialogue with AI text-to-speech for games. 900+ voices, emotion control, runtime synthesis, from $6 per 1M.
Voice thousands of lines and dynamic dialogue without a full cast.
Key facts:
- 900+ voices for a varied cast
- Emotion control across 13 styles
- Runtime synthesis for dynamic dialogue
- From $6 per 1M characters
Q: How do game studios use text-to-speech?
A: Game studios use text-to-speech to voice NPCs and dialogue from a script, and to generate lines at runtime for procedural or player-driven scenes. With 900+ voices they build a varied cast, emotion control gives lines the right delivery, and studios avoid booking a full voice cast for every line.
Q: Can dialogue be generated during play?
A: Yes. Synthesize lines at runtime with low-latency streaming so a character can speak text that did not exist at ship time, which suits procedural content and player-driven narratives.
Q: How do I keep a large cast consistent?
A: Assign a distinct voice ID per character. A recurring NPC then sounds the same across every scene and every content update, and adding lines is a synthesis job rather than a re-record.
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URL: https://speechify.ai/industries/build/tts/media
Title: Text-to-Speech for Media — Narrate Content at Speed
Give media and content teams AI text-to-speech for article audio, video voiceover, and podcasts. Fast, natural, from $6 per 1M characters.
Turn articles, scripts, and posts into audio at the speed of a newsroom.
Key facts:
- Article-to-audio and video voiceover
- 900+ voices, emotion control
- Low-latency streaming
- From $6 per 1M characters
Q: How do media companies use text-to-speech?
A: Media and content teams use text-to-speech to publish audio versions of articles, add voiceover to video, and produce podcast segments from scripts. Natural voices and emotion control keep the audio on-brand, and the speed of synthesis matches a publishing schedule that a studio cannot.
Q: Can every article get an audio version?
A: Yes. Because audio is generated from the article text, every published piece can carry a listen option automatically, produced at the moment of publishing rather than sent out for narration.
Q: Does it keep a consistent brand voice?
A: Yes. Use one voice ID, or clone a signature voice, across every piece so a publication's audio has a recognizable sound. Emotion control adapts the delivery to the content.
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URL: https://speechify.ai/industries/build/tts/publishing
Title: Text-to-Speech for Publishing — Audio at Catalog Scale
Turn a publishing catalog into audiobooks with AI text-to-speech. Consistent narration, 30+ languages, per-character pricing from $6 per 1M.
Produce audiobooks across a whole catalog without a studio per title.
Key facts:
- Long-form synthesis for book-length text
- Consistent narrator per title via voice ID
- 30+ languages for international editions
- From $6 per 1M characters
Q: Can publishers produce audiobooks with text-to-speech?
A: Yes. A publisher can convert a whole catalog into audiobooks with text-to-speech instead of booking a studio and narrator per title. Each book gets a consistent narrator via a fixed voice ID, SSML controls pacing, and per-character pricing makes even a large backlist affordable to produce.
Q: How does this scale to a backlist?
A: Because production is a synthesis pipeline, adding a title is running the text through the same process, not scheduling a recording session. A backlist of hundreds of titles becomes a batch job rather than years of studio time.
Q: Can I produce international editions?
A: Yes. Re-synthesize a translated manuscript with a multilingual voice to publish the same title in another language across 30+ languages, without a separate narrator per market.
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URL: https://speechify.ai/voice-agent-api
Title: Voice Agent API: One All-In Rate | SpeechifyAI
The Voice Agent API for realtime voice agents. LLM, speech, and telephony in one all-in rate, quoted per contract. ~430ms first audio, SOC 2 Type II.
Build realtime voice agents on one API, with ~430ms first audio and a bill that fits on one line.
Key facts:
- One all-in rate: LLM, STT, TTS and telephony, no passthrough
- Quoted per contract, scoped with our team
- Enterprise track, reached through sales
- Simba 3.2 is evaluated on independent blind-listening leaderboards
- ~430ms first audio from a streaming-native voice model
- SOC 2 Type II certified
- Plain REST at api.speechify.ai/v1/agents
- Tool kinds: builtin, webhook, client, MCP
Q: What is a voice agent API?
A: A voice agent API is a developer interface for running a two-way voice conversation with an AI agent. It handles speech-to-text on the caller side, an LLM to reason and call tools, text-to-speech to answer back, and the orchestration that manages turns, interruptions, and telephony. SpeechifyAI bundles all four behind one endpoint and bills them as one line item.
Q: How much does the SpeechifyAI Voice Agent API cost?
A: Voice agents are an enterprise product. Deployments are scoped with our team and priced per contract, so there is no self-serve plan and no published per-minute rate. What the quote covers is the whole stack: the LLM, speech-to-text, text-to-speech, and telephony orchestration are one line item, with no passthrough and no per-token math. Talk to sales and we scope the deployment with you.
Q: How fast is it?
A: Simba 3.2, the voice model behind every agent, produces first audio in ~430ms and is evaluated on independent blind-listening leaderboards. Because it streams natively, replies start sounding while the rest of the sentence is still rendering.
Q: Can a voice agent handle phone calls?
A: Yes. Agents take inbound calls on a provisioned number, take inbound calls on a SIP trunk you already own, make outbound calls, or run over WebRTC in a browser. The same agent config drives every surface.
Q: Which SDKs are available?
A: The agent endpoints are plain REST at api.speechify.ai/v1/agents, authenticated with a bearer key, so any HTTP client works. The published Python and TypeScript SDKs cover the text-to-speech API and do not carry agent methods yet.
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URL: https://speechify.ai/agents
Title: Voice Agents for Enterprise on One Realtime API
Realtime voice agents with a natural, low-latency voice. Simba 3.2 produces first audio in ~430ms. One all-in rate, quoted per contract.
Realtime voice agents on one all-in API, with no stitched stack and no spreadsheet bill.
Key facts:
- One all-in rate: LLM, STT, TTS and telephony, no passthrough
- Quoted per contract, scoped with our team
- 20+ curated real-time voices
- ~430ms first audio
- SOC 2 Type II certified
Q: What is SpeechifyAI Agents?
A: SpeechifyAI Agents is a platform for building realtime voice agents that listen, reason, and speak. Each agent combines speech-to-text, an LLM with tool calling, a knowledge base, per-caller memory, and telephony, billed as one all-in line item rather than a stack of separate vendor charges.
Q: What can a voice agent do?
A: It can answer and place calls, resolve support questions, book and reschedule appointments, qualify leads, run outbound campaigns, and navigate other phone systems. It grounds answers in your knowledge base, calls your APIs mid-conversation, and hands off to a human when it should.
Q: How much does it cost?
A: Voice agents are an enterprise product. Deployments are scoped with our team and priced per contract, so there is no self-serve plan and no published per-minute rate. A quote is one all-in line item with the LLM, speech, and telephony inside it, so there is no passthrough and no per-token math to reconcile. Talk to sales and we scope the deployment with you.
Q: How do I start?
A: Talk to sales. We scope the deployment with you and provision a workspace, after which an agent is one POST to /v1/agents pointed at a phone number or a web session. The endpoints are plain REST, and the docs cover tools, knowledge bases, memory, and testing.
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URL: https://speechify.ai/conversational-ai
Title: Conversational AI for Voice, Chat and Phone | SpeechifyAI
Conversational AI across voice, chat, and phone from one agent brain. Realtime speech, IVR replacement, deterministic workflows. Quoted per contract.
One conversation brain across voice, chat, and phone, grounded in your content.
Key facts:
- Same agent across inbound voice, outbound voice, and a web widget
- Per-caller memory within a conversation and across calls
- Knowledge base grounds answers in your content
- Deterministic workflows where compliance demands a script
- Quoted per contract, one all-in line item
- SOC 2 Type II
Q: What is conversational AI?
A: Conversational AI is software that holds a natural, two-way conversation with a person in real time, understanding intent and taking action rather than matching keywords. Where rigid IVR trees and scripted chatbots match keywords, a modern conversational agent listens, reasons, calls tools, and answers in a human-sounding voice.
Q: How is this different from a chatbot?
A: A chatbot follows scripted branches and usually works in text. A conversational AI agent understands free speech, grounds answers in your knowledge base, remembers context across a call, calls your APIs mid-conversation, and speaks back with realtime voice. It also runs across phone, web, and chat from one configuration.
Q: Can one agent work across phone and web?
A: Yes. The same agent brain drives inbound calls, outbound calls, and a web widget. The knowledge, workflows, and memory carry across surfaces, so a caller gets the same behavior whether they phone in or click the widget on your site.
Q: Does it replace our IVR?
A: It can. Instead of press-1 menus, callers say what they need and the agent routes, answers, or completes the task. Deterministic workflows keep the required steps scripted where compliance demands it, so the flexible parts stay natural and the strict parts stay exact.
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URL: https://speechify.ai/voice-agent-platform
Title: Voice Agent Platform - Ship and Operate Voice AI at Scale
The voice agent platform for production teams. Deterministic workflows, simulated callers, live operations, SOC 2 Type II. Quoted per contract.
The voice agent platform for teams running voice AI in production, not just demoing it.
Key facts:
- Quoted per contract, one all-in line item
- Deterministic workflows for scripted steps
- Simulated callers: reply, tool, and full-conversation tests
- Live operations APIs: transcript streaming, take-over, analytics
- Per-action RBAC on operations APIs
- SOC 2 Type II, never trains on your data
- Forward-deployed engineers on Enterprise
Q: What is a voice agent platform?
A: A voice agent platform is the managed backend and tooling that runs voice agents in production: the runtime that holds conversations, plus the workflow design, testing, observability, and access controls a team needs to ship and operate them. It is more than an API, and more than a no-code builder.
Q: How do you test a voice agent before production?
A: SpeechifyAI runs simulated callers on the real worker runtime. Reply tests check single turns, tool tests check that the agent calls your APIs correctly, and full-conversation tests replay whole scenarios. Regressions hit the test runner instead of a live caller.
Q: Can I monitor and intervene in live calls?
A: Yes. Live operations APIs stream transcripts in real time, expose take-over actions to hand a call to a human, and answer analytics queries. Every action is governed by per-action RBAC so only the right roles can listen in or intervene.
Q: Is it compliant enough for regulated work?
A: SpeechifyAI is SOC 2 Type II certified, encrypts data in transit and at rest, and never trains on your conversations. Deterministic workflows let a compliance team script mandatory disclosures and confirmation steps exactly.
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URL: https://speechify.ai/agents/ai-answering-service
Title: AI Answering Service - Never Miss a Call
An AI answering service that picks up every call, answers questions, books appointments, and takes messages. One all-in rate. Quoted per contract.
An answering service that picks up every call, day or night, and actually helps.
Key facts:
- Answers inbound calls 24/7 on a provisioned number or BYOC
- Knowledge base grounds answers in your content
- Books and reschedules via tool calling
- One all-in rate: LLM, speech and telephony included
- Quoted per contract, scoped with our team
Q: What is an AI answering service?
A: An AI answering service is a voice agent that picks up your inbound calls automatically, answers common questions from your knowledge base, books or reschedules appointments through tool calls, and takes messages. It runs around the clock without staffing a phone line.
Q: Can it book appointments?
A: Yes. Through tool calling, the agent reaches your scheduling system mid-call to check availability, book, and confirm. It can text a confirmation and reminder afterward if your workflow includes it.
Q: How much does it cost to run?
A: Voice agents are an enterprise product. Deployments are scoped with our team and priced per contract, so there is no self-serve plan and no published per-minute rate. The quote is one all-in line item covering the LLM, speech, and telephony, and it is billed on talk time, so you are not paying for a seat sitting idle overnight.
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URL: https://speechify.ai/agents/ai-call-center
Title: AI Call Center - Automate Inbound and Outbound Calls
Build an AI call center on realtime voice agents. Handle inbound and outbound calls, route, resolve, and escalate to humans. Quoted per contract.
Run a call center on voice agents that resolve calls, not just route them.
Key facts:
- Inbound and outbound over SIP, provisioned numbers or BYOC
- Per-caller memory across calls
- Deterministic workflows for scripted steps
- Live take-over to a human agent
- Quoted per contract, one all-in line item
Q: What is an AI call center?
A: An AI call center uses voice agents to handle phone calls that would otherwise need human staff: answering inbound calls, placing outbound calls, routing, resolving common requests, and escalating to a person when needed. The agents understand speech, act on your systems, and speak back in real time.
Q: Can it handle both inbound and outbound?
A: Yes. SpeechifyAI agents answer inbound calls on a provisioned number or your own SIP trunk, and place outbound calls for reminders, follow-ups, and campaigns. The same agent configuration drives both directions.
Q: What happens when the agent cannot resolve a call?
A: Deterministic workflows define the escalation path, and live operations APIs let a human take over the call in progress with full transcript context. The handoff is a first-class action, not a dropped call.
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URL: https://speechify.ai/agents/ai-customer-service
Title: AI Customer Service - Resolve Support Calls End to End
AI customer service on realtime voice agents. Resolve support calls, look up accounts, take action, and escalate cleanly. Quoted per contract.
Customer service that resolves the call, grounded in your own knowledge base.
Key facts:
- Knowledge base grounds every answer in your content
- Tool calling looks up accounts and takes action mid-call
- Per-caller memory across calls
- Clean escalation to a human with transcript context
- Quoted per contract, one all-in line item
Q: What is AI customer service?
A: AI customer service uses voice agents to handle support calls: understanding the issue, looking up the account, taking action on your systems, and answering from your knowledge base. When the issue needs a person, the agent escalates with full context rather than making the caller repeat themselves.
Q: Can it act on our systems, not just answer?
A: Yes. Tool calling lets the agent reach your APIs mid-conversation to look up an order, reset a setting, or process a change. It is not limited to reading a script; it can complete the task the caller phoned in for.
Q: How does escalation work?
A: Deterministic workflows define when to hand off, and the live operations APIs let a human take the call in progress with the transcript already in front of them. The caller does not restart the conversation.
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URL: https://speechify.ai/agents/ai-sales-agent
Title: AI Sales Agent - Qualify and Convert on Every Call
An AI sales agent that qualifies leads, books meetings, and follows up by phone. Realtime voice and CRM tool calling. Quoted per contract.
A sales agent that qualifies, books, and follows up, on every call, day and night.
Key facts:
- Outbound and inbound calling over SIP
- Tool calling into your CRM mid-conversation
- Per-caller memory across follow-ups
- Deterministic workflows for qualification scripts
- Quoted per contract, one all-in line item
Q: What is an AI sales agent?
A: An AI sales agent is a voice agent that handles sales calls: qualifying inbound leads, running outbound outreach, booking meetings, and following up. It updates your CRM through tool calls during the conversation and remembers context across a sequence of calls with the same prospect.
Q: Can it update our CRM?
A: Yes. Tool calling connects the agent to your CRM mid-call, so it logs the conversation, updates lead status, and books the meeting without a human re-entering anything afterward.
Q: Does it work for outbound campaigns?
A: Yes. The agent places outbound calls for outreach, follow-up, and re-engagement, using the same configuration as inbound. Per-caller memory keeps each prospect's history straight across calls.
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URL: https://speechify.ai/agents/appointment-scheduling
Title: AI Appointment Scheduling - Book and Reschedule by Voice
AI appointment scheduling by phone. Voice agents book, reschedule, and confirm against your calendar through tool calls. Quoted per contract.
Book, reschedule, and confirm appointments by voice, straight into your calendar.
Key facts:
- Tool calling checks availability and books in real time
- Inbound and outbound over SIP
- Sends confirmations and reminders via your workflow
- Quoted per contract, one all-in line item
Q: How does AI appointment scheduling work?
A: A voice agent answers or places the call, checks your calendar through a tool call, offers open slots, books the one the caller picks, and confirms. It can send a confirmation and a reminder afterward if your workflow includes those steps.
Q: Can it reschedule existing appointments?
A: Yes. The agent looks up the existing booking, offers alternatives, moves it, and confirms the change, all in the same call. The caller never waits on hold for a receptionist to find a slot.
Q: Does it integrate with our calendar?
A: Through tool calling, the agent reaches your scheduling system live during the conversation, so availability is real and bookings land in the same calendar your team uses.
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URL: https://speechify.ai/agents/inbound-calling
Title: AI Inbound Calling - Answer Every Call Instantly
AI inbound calling that answers every call in one ring. Voice agents resolve, route, and book on a provisioned number or your SIP trunk. Quoted per contract.
Answer every inbound call in one ring and resolve it, not just route it.
Key facts:
- Inbound over SIP, provisioned numbers or BYOC
- Knowledge base grounds answers in your content
- Tool calling to resolve requests mid-call
- IVR replacement with natural speech
- Quoted per contract, one all-in line item
Q: What is AI inbound calling?
A: AI inbound calling uses a voice agent to answer incoming calls immediately, understand what the caller needs in plain speech, and resolve it or route it. It replaces both hold queues and press-1 IVR menus with a natural conversation that finishes the task.
Q: Does it replace our IVR?
A: It can. Instead of a menu tree, callers say what they want and the agent handles it: answering from the knowledge base, taking action through tool calls, or routing to the right team. The strict steps stay scripted through deterministic workflows.
Q: What if the agent cannot help?
A: It escalates to a human through the live operations APIs, passing the transcript so the caller does not repeat themselves. The handoff is built in, not a dead end.
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URL: https://speechify.ai/agents/lead-qualification
Title: AI Lead Qualification - Score Every Lead by Phone
AI lead qualification by voice. Agents call new leads, ask the qualifying questions, score, and route hot ones to reps. Quoted per contract.
Call and qualify every lead in minutes, then route the hot ones to a human.
Key facts:
- Outbound calling over SIP, provisioned or BYOC
- Deterministic workflows for qualification scripts
- Tool calling to write scores back to your CRM
- Quoted per contract, one all-in line item
Q: What is AI lead qualification?
A: AI lead qualification uses a voice agent to call new leads, ask the qualifying questions your team uses, score the lead against your criteria, and route the strong ones to a rep. It reaches leads in minutes rather than days and records the answers in your CRM.
Q: How does it decide which leads are hot?
A: A deterministic workflow encodes your qualification script and scoring rules, so every lead is asked the same questions and scored the same way. The agent writes the result back to your CRM through a tool call.
Q: What happens to qualified leads?
A: Qualified leads are routed to a human rep with the full call transcript and score attached, so the rep opens the conversation already knowing the context instead of starting from a form.
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URL: https://speechify.ai/agents/outbound-calling
Title: AI Outbound Calling - Run Voice Campaigns at Scale
AI outbound calling for reminders, follow-ups, and campaigns. Voice agents place calls over SIP and act on your systems. Quoted per contract.
Place thousands of outbound calls that hold a real conversation, not a robocall.
Key facts:
- Outbound over SIP, provisioned numbers or BYOC
- Tool calling to act on your systems mid-call
- Per-caller memory across a campaign
- One all-in rate, billed on talk time
Q: What is AI outbound calling?
A: AI outbound calling uses voice agents to place calls for reminders, follow-ups, surveys, collections, and outreach. Unlike a robocall, the agent holds a real two-way conversation, answers questions, and takes action on your systems during the call.
Q: Can it run at campaign scale?
A: Yes. Agents place outbound calls across large lists, with the concurrency ceiling agreed in your contract. Per-caller memory keeps each contact's history straight, and results log back to your systems through tool calls.
Q: How is it billed?
A: On one all-in rate covering the LLM, speech, and telephony, quoted per contract rather than published as a self-serve number. You pay for talk time, so calls that go unanswered do not run up the same cost as connected conversations.
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URL: https://speechify.ai/agents/knowledge-base
Title: Voice Agent Knowledge Base - Ground Answers in Your Content
Give voice agents a knowledge base. Upload documents, files, and sitemaps so agents answer from your own content with built-in retrieval.
Ground every answer in your own content, uploaded once and retrieved on every call.
Key facts:
- Upload documents, files, and sitemaps
- Built-in retrieval grounds answers
- Attach a knowledge base to any agent
Q: What is a voice agent knowledge base?
A: A knowledge base is the set of your own content that a voice agent retrieves from to answer questions. You upload documents, files, and sitemaps, and the agent grounds its replies in that material instead of guessing, so callers get answers that match your actual policies and products.
Q: What can I upload?
A: Documents, files, and sitemaps. The knowledge base ingests them and makes them retrievable, so the agent can pull the right passage mid-conversation when a caller asks something the material covers.
Q: Does every agent share one knowledge base?
A: You attach a knowledge base to the agents that need it, so different agents can draw on different content. A support agent and a sales agent can each ground answers in the material that fits their job.
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URL: https://speechify.ai/agents/memory
Title: Voice Agent Memory - Context Within and Across Calls
Give voice agents memory. Agents remember context within a conversation and across calls, so returning callers never start over.
Agents that remember, within a call and across calls, so callers never repeat themselves.
Key facts:
- Memory persists within a conversation
- Per-caller memory persists across calls
- GDPR delete-by-caller supported
Q: What is voice agent memory?
A: Voice agent memory is the agent's ability to retain context. Within a call, it tracks what has been said so it does not ask the same thing twice. Across calls, per-caller memory means a returning caller is recognized and the conversation picks up with their history rather than from scratch.
Q: Does memory persist across separate calls?
A: Yes. Per-caller memory carries context from one call to the next, so a customer who phoned yesterday does not have to re-explain their situation today. The agent opens with the relevant history in hand.
Q: Can a caller's memory be deleted?
A: Yes. The system supports GDPR delete-by-caller, so a caller's stored memory can be removed on request, keeping the feature compatible with data-protection obligations.
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URL: https://speechify.ai/agents/telephony
Title: Voice Agent Telephony - Inbound and Outbound over SIP
Connect voice agents to the phone network. Inbound and outbound over SIP, provisioned numbers or bring your own carrier. Twilio, Telnyx, or custom.
Put an agent on the phone network, inbound or outbound, on our numbers or yours.
Key facts:
- Inbound and outbound over SIP
- Provision numbers from the dashboard
- Bring your own carrier (Twilio, Telnyx, custom)
Q: How do voice agents connect to phone calls?
A: Over SIP. You either provision a phone number from the dashboard or bring your own carrier, then agents answer inbound calls and place outbound calls on that connection. Both directions run from the same agent configuration.
Q: Can I use my own carrier?
A: Yes. Bring-your-own-carrier connects your existing SIP trunk or a provider like Twilio or Telnyx, so you keep your numbers and your telephony contracts while the agent handles the conversation.
Q: Is telephony billed separately?
A: No. Telephony orchestration is included in the all-in rate along with the LLM and speech models. There is no separate telephony passthrough line on the bill.
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URL: https://speechify.ai/agents/testing-simulation
Title: Voice Agent Testing - Simulated Callers Before Production
Test voice agents with simulated callers. Reply, tool, and full-conversation tests run on the real worker runtime before a real caller ever connects.
Catch regressions with simulated callers before a real one ever hears them.
Key facts:
- Reply, tool, and full-conversation tests
- Simulation runs on the real worker runtime
- Results judged server-side
Q: How do you test a voice agent?
A: With simulated callers. Reply tests check a single turn, tool tests confirm the agent calls your APIs correctly, and full-conversation tests replay whole scenarios. They run on the real worker runtime, so a test exercises the same path a live call would, and results are judged server-side.
Q: Why simulate instead of just calling in?
A: Manual calling does not scale and does not repeat. Simulated callers run the same scenarios every time, so a regression shows up in the test runner instead of surprising a real customer. You can run them before every change.
Q: What kinds of tests are there?
A: Three: reply tests for individual turns, tool tests for the agent's API calls, and full-conversation tests for end-to-end scenarios. Together they cover the ways a voice conversation actually breaks.
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URL: https://speechify.ai/agents/tool-calling
Title: Voice Agent Tool Calling - Act on Your Systems Mid-Call
Let voice agents call your APIs mid-conversation. Builtin, webhook, client, and MCP tools so agents look things up and take action in real time.
Let agents call your APIs mid-conversation to look things up and take action.
Key facts:
- Tool kinds: builtin, webhook, client, MCP
- Unified tools surface at /v1/agents/{id}/tools
- Agents act on your systems in real time
Q: What is voice agent tool calling?
A: Tool calling lets a voice agent call your APIs during a conversation to look something up or take an action. When a caller asks to check an order or change a setting, the agent invokes the right tool mid-call and continues talking with the result, rather than reading from a static script.
Q: What kinds of tools are supported?
A: Four kinds: builtin tools for common actions, webhook tools that call your endpoints, client tools that run on the caller's side, and MCP tools that connect to Model Context Protocol servers. They share one tools surface on the agent.
Q: How do I add a tool to an agent?
A: Tools attach to an agent through a unified tools surface at /v1/agents/{id}/tools. You define the tool once and the agent can call it whenever the conversation calls for it.
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URL: https://speechify.ai/agents/webhooks
Title: Voice Agent Webhooks - Stream Events to Your Backend
Stream voice agent conversation events to your backend as they happen, with signed, verifiable payloads you can trust.
Stream conversation events to your backend live, with signed payloads you can verify.
Key facts:
- Stream conversation events as they happen
- Signed, verifiable payloads
Q: What do voice agent webhooks do?
A: Webhooks stream conversation events from an agent to your backend as they happen: turns, tool calls, and lifecycle events. Your systems react in real time, logging the call, updating a record, or triggering a downstream workflow, without polling for state.
Q: Are the payloads secure?
A: Yes. Webhook payloads are signed, so your endpoint can verify each event genuinely came from the platform and was not tampered with. You validate the signature before acting on the event.
Q: What can I do with the events?
A: Anything your backend needs: write the transcript to your data warehouse, update a CRM record mid-call, kick off a fulfillment step, or feed analytics. The events arrive as the conversation unfolds.
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URL: https://speechify.ai/how-to-build-a-voice-agent
Title: How to Build a Voice Agent in 2026
Build a voice agent in three steps: get workspace access from sales, create the agent with one request, and connect it to a phone number or the web.
Build a voice agent in three steps: access, create, connect.
Key facts:
- POST /v1/agents to create an agent
- Plain REST, any HTTP client
- Connect to phone (SIP) or WebRTC
- Workspace provisioned by our team
Q: How do you build a voice agent?
A: Three steps. Talk to sales to get a workspace provisioned and an API key issued, create an agent with one POST to /v1/agents that sets a prompt, a voice, and a first message, then connect the agent to a phone number or a web session. The endpoints are plain REST, so any HTTP client works.
Q: Do I need to stitch together STT, an LLM, and TTS myself?
A: No. The Voice Agent API bundles speech-to-text, the LLM, text-to-speech, and telephony behind one endpoint. You configure the agent; the platform runs the pipeline. That is the difference between an all-in API and assembling a stack from separate vendors.
Q: How long does it take to get a working agent?
A: The first agent is one API call, so once your workspace is provisioned a basic working agent takes minutes. Adding tools, a knowledge base, and telephony is incremental from there. We scope a pilot with you, so the first agent runs on real calls before you commit to a term.
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URL: https://speechify.ai/voice-agent-latency
Title: Voice Agent Latency: What Matters and What's Achievable
Voice agent latency is the delay from when a caller stops talking to when the agent replies. Here is the budget, the breakdown, and what to aim for.
Latency is the difference between a conversation and a wait. Here is the budget and the breakdown.
Key facts:
- Simba 3.2 produces first audio in ~430ms
- Evaluated on independent blind-listening leaderboards
Q: What is voice agent latency?
A: Voice agent latency is the delay from the moment a caller stops speaking to the moment the agent starts replying. It is the sum of speech-to-text, the LLM's reasoning, and text-to-speech first audio, plus network time. When it exceeds roughly half a second, the conversation starts to feel like a wait.
Q: What latency should a voice agent aim for?
A: The lower the better: the goal is a reply that feels immediate rather than delayed. The single biggest lever is text-to-speech first-audio time. SpeechifyAI's Simba 3.2 produces first audio in ~430ms, which leaves headroom for the STT and LLM stages inside the per-turn budget.
Q: Why does TTS first-byte latency matter so much?
A: Because it is the last stage before the caller hears anything. Even if transcription and reasoning are fast, a slow text-to-speech start makes the whole reply feel late. A streaming-native model that emits first audio in ~430ms keeps the perceived response immediate.
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URL: https://speechify.ai/voice-agent-pricing-guide
Title: Voice Agent Pricing: How It Works and What to Watch
Voice agent pricing usually hides the LLM, speech, and telephony as separate line items. Here is how one all-in contract rate compares.
Most voice agent pricing hides the real cost in passthrough. Here is how one all-in rate compares.
Key facts:
- Quoted per contract: one all-in line item
- LLM, STT, TTS, telephony included, no passthrough
- Enterprise track, reached through sales
Q: How much does a voice agent cost?
A: It depends on how the vendor bills. Many quote a low platform fee, then add the LLM tokens, the speech models, and the telephony on top, so the real all-in cost is higher than the headline. SpeechifyAI is one all-in line item with everything inside it. Voice agents are an enterprise product. Deployments are scoped with our team and priced per contract, so there is no self-serve plan and no published per-minute rate.
Q: What should I watch for in voice agent pricing?
A: Passthrough. A per-minute platform fee that excludes the LLM, speech, or telephony means the number on the page is not the number on the bill. Also watch for concurrency multipliers and per-feature compliance add-ons, which turn a simple rate into a spreadsheet.
Q: Is there a free tier?
A: No. Voice agents are an enterprise product. Deployments are scoped with our team and priced per contract, so there is no self-serve plan and no published per-minute rate. In place of a free tier we scope a pilot with you, so an agent runs on real calls and real traffic before you commit to a term.
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URL: https://speechify.ai/voice-agent-vs-voice-ai-sdk
Title: Voice Agent API vs Voice AI SDK: What's the Difference?
A voice agent API runs the conversation on a managed backend. A voice AI SDK is a client library that talks to it. Here is when to use each.
An API runs the conversation for you. An SDK is how your app talks to it. Here is when to use each.
Key facts:
- API runs the conversation on a managed backend
- SDK is a client library (Python, TypeScript)
- Frameworks are a third category: assemble your own stack
Q: What is the difference between a voice agent API and a voice AI SDK?
A: A voice agent API runs the conversation for you on a managed backend: you send configuration and receive audio and events. A voice AI SDK is a client library your app uses to call that API from a browser, phone, or server. The API is the service; the SDK is the convenience wrapper around it.
Q: When should I use the API directly versus the SDK?
A: Use the SDK when you are building in Python or TypeScript and want typed methods and less boilerplate. Use the raw REST API when you are in another language or need full control over the requests. Both talk to the same backend, so the choice is about developer experience, not capability.
Q: How is this different from an orchestration framework?
A: Frameworks like open-source agent toolkits are a third category: you assemble your own speech-to-text, LLM, and text-to-speech and run the orchestration yourself. An all-in API does that assembly for you and bills it as one rate, trading some control for far less to build and maintain.
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URL: https://speechify.ai/what-is-a-voice-agent
Title: What Is a Voice Agent? A Plain Definition for 2026
A voice agent is an AI system that listens, reasons, and speaks in real time over a phone or the web. Here is how it works and what it is used for.
A voice agent listens, reasons, and speaks in real time. Here is the plain definition.
Key facts:
- Four layers: STT, LLM, TTS, orchestration
- Runs on phone, web, and mobile
- Grounds answers in a knowledge base, calls tools, remembers context
Q: What is a voice agent?
A: A voice agent is an AI system that holds a real-time spoken conversation with a person. It converts speech to text, uses a language model to reason and decide what to do, converts the reply back to speech, and manages the turn-taking. Unlike an IVR menu, it understands free speech and can take action on your systems.
Q: How is a voice agent different from a chatbot?
A: A chatbot works in text and usually follows scripted branches. A voice agent works in spoken conversation, understands intent from free speech, calls tools to act on live data, remembers context across the call, and replies in a natural voice. It runs on phone lines as well as web and mobile.
Q: What is a voice agent used for?
A: Common uses are customer support, appointment booking, lead qualification, outbound reminders and campaigns, and replacing press-1 IVR menus. Anywhere a phone conversation follows a repeatable pattern, a voice agent can handle the routine calls and escalate the rest.
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URL: https://speechify.ai/voice-cloning
Title: Voice Cloning API: Clone a Voice from a Short Sample
Clone a voice from a short sample with the Speechify Build API. Consent required, production-ready, works across 30+ languages.
Create a synthetic version of a voice from a 10-30 second clip, with the speaker's consent, then synthesize any text in that voice by ID.
Key facts:
- 10-30s sample
- Instant, self-serve
- 30+ languages
- Zero-shot and fine-tuned
Q: What is voice cloning?
A: It creates a synthetic version of a specific voice from an audio sample, then synthesizes any text in that voice. On the Build API you clone from a short clean sample, with the speaker's consent, and use it by voice ID on the normal speech endpoints, a Build feature that shares the Build API and pricing.
Q: Do I need consent to clone a voice?
A: Yes. Creating a voice requires a consent record with the speaker's full name and email. It's mandatory: you clone a voice you are authorized to clone, whether it's your own or one you have permission to use.
Q: What languages do cloned voices support?
A: A cloned voice works across all 30+ supported languages, so one clone can speak many languages. Cloned voices also run self-serve on simba-3.0; the curated simba-3.2 voice set plays cloned voices too, but each one currently requires manual Speechify approval.
Q: How do I manage cloned voices?
A: Retrieve a voice with GET /v1/voices/{voice_id}, download its sample as WAV, and remove it with DELETE /v1/voices/{voice_id}. Cloned voices list before shared voices.
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URL: https://speechify.ai/instant-voice-cloning
Title: Instant Voice Cloning — Clone from a Short Sample
Clone a voice instantly from a 10-30 second sample with the Speechify Build API. Zero-shot, self-serve, consent required, good quality.
Clone a voice in seconds from a short sample, self-serve, with consent.
Key facts:
- Zero-shot: clone from a 10-30 second clean sample
- Self-serve via API or Console
- Good quality, ready for production
- Consent required
Q: What is instant voice cloning?
A: Instant, or zero-shot, voice cloning creates a usable voice from a single short sample, typically 10 to 30 seconds of clean speech. It is self-serve through the API or Console, produces good quality, and requires a consent record. You get a voice ID back and synthesize with it right away.
Q: How long a sample do I need?
A: A clean sample of 10 to 30 seconds, under a minute and under 5MB, is enough for zero-shot cloning. The cleaner the audio, the better the result, so record without background noise.
Q: How is it different from professional cloning?
A: Instant cloning is zero-shot from a short sample, self-serve, with good quality. Professional, fine-tuned cloning uses hours of audio and is arranged with sales for the best quality. Choose instant for speed and self-serve; choose professional when quality is paramount.
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URL: https://speechify.ai/professional-voice-cloning
Title: Professional Voice Cloning — Fine-Tuned, Best Quality
Professional voice cloning fine-tunes on hours of audio for the best quality. Arranged with sales, consent required, production-ready.
Fine-tune on hours of audio for the best-quality cloned voice.
Key facts:
- Fine-tuned on hours of audio
- Best quality tier
- Arranged with sales
- Consent required
Q: What is professional voice cloning?
A: Professional, or fine-tuned, voice cloning trains on hours of a speaker's audio to produce the best-quality clone. It is arranged with sales rather than fully self-serve, and it requires consent. The result is a high-fidelity voice suited to flagship narration and brand voices where quality is paramount.
Q: How much audio does it need?
A: Fine-tuned cloning uses hours of audio, far more than the short sample zero-shot cloning needs. The larger dataset is what lifts the quality from good to best.
Q: How do I get professional cloning?
A: Professional cloning is arranged with sales. Because it involves collecting hours of audio and a fine-tuning step, it is set up as an engagement rather than a self-serve API call. Contact sales to start.
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URL: https://speechify.ai/voice-cloning/accessibility
Title: Voice Cloning for Accessibility — Preserve a Voice
Preserve or personalize a voice for accessibility with the Speechify Build API. Clone from a short sample, with consent, synthesize anywhere.
Preserve a personal voice so assistive tech can speak in it.
Key facts:
- Clone a personal voice from a short sample
- Use it in assistive read-aloud and AAC
- Consent required
- Works across 30+ languages
Q: How does voice cloning help accessibility?
A: Voice cloning lets assistive technology speak in a person's own voice rather than a generic one. With consent, clone the voice from a short sample using the Speechify Build API, then use that voice ID in read-aloud or communication tools. It personalizes assistive speech and can preserve a voice.
Q: Can this preserve someone's voice?
A: Yes. Cloning captures a voice from a sample, so it can be preserved and used later in assistive tools. Because a short clean sample is enough for zero-shot cloning, capturing a voice is quick.
Q: Is consent required?
A: Yes. A consent record with the person's full name and email is required to create the voice, so a personal voice is only ever cloned with authorization.
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URL: https://speechify.ai/voice-cloning/audiobooks
Title: Voice Cloning for Audiobooks — Author's Own Voice
Narrate audiobooks in an author's cloned voice with the Speechify Build API. Consistent, cross-language, consent required. From a short sample.
Let an author narrate a whole book in their own voice, without the hours.
Key facts:
- Clone an author or narrator voice from a short sample
- Consistent voice across every chapter
- Cross-language
- Consent required
Q: Can an author narrate an audiobook with a cloned voice?
A: Yes. With consent, clone the author's voice from a short sample using the Speechify Build API, then narrate the whole book from the manuscript in that voice. The author's voice reads every chapter consistently without them spending hours in a booth, and the clone can produce editions in 30+ languages.
Q: How does it stay consistent across a long book?
A: Every chapter is synthesized with the same voice ID, so chapter one and chapter thirty sound identical. There is no drift and no need to re-book the narrator to match earlier recordings.
Q: Is consent required?
A: Yes. Creating the voice requires a consent record with the author's full name and email. The voice is cloned only with authorization.
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URL: https://speechify.ai/voice-cloning/creator-tools
Title: Voice Cloning for Creator Tools — Build Voice Features
Add voice cloning to creator tools with the Speechify Build API. Let users clone their own voice, with consent, and synthesize by voice ID.
Let your users clone their own voice inside your product, with consent.
Key facts:
- Self-serve zero-shot cloning via API
- Users clone from a short sample
- Consent captured per voice
- Synthesize by returned voice ID
Q: Can I add voice cloning to my creator app?
A: Yes. The Speechify Build API lets you build a voice-cloning feature into a product: a user records a short sample, provides consent, and you POST to /v1/voices to create their voice. You then synthesize their content by the returned voice ID. Zero-shot cloning is self-serve, so it fits an in-app flow.
Q: How do users consent inside my app?
A: Your app collects the consent details, the user's full name and email, and passes them in the consent field of the create call. The record is required per voice, so your flow captures it as part of cloning.
Q: Can each user have their own voice?
A: Yes. Each cloned voice has its own voice ID, so every user gets a personal voice they synthesize with. Manage voices with the get, sample, and delete endpoints.
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URL: https://speechify.ai/voice-cloning/dubbing
Title: Voice Cloning for Dubbing — One Voice, Many Languages
Dub content in a speaker's cloned voice across 30+ languages with the Speechify Build API. Consent required.
Dub content into many languages while keeping the original speaker's voice.
Key facts:
- Cloned voice speaks 30+ languages
- Keep the original speaker's voice across languages
- Clone from a short sample
- Consent required
Q: Can I dub content in the original speaker's voice?
A: Yes. With consent, clone the speaker's voice once, then synthesize the translated script in that voice across 30+ languages. The audience hears the same voice they know, speaking their language, rather than a different dubbing actor per market.
Q: How many languages does it support?
A: A cloned voice speaks across all 30+ supported languages, so one clone dubs into every supported market from a single voice.
Q: Do I need consent to clone the speaker?
A: Yes. A consent record with the speaker's full name and email is required to create the voice. Dubbing with a cloned voice still requires authorization.
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URL: https://speechify.ai/voice-cloning/game-characters
Title: Voice Cloning for Game Characters — Signature Voices
Clone signature character voices for games with the Speechify Build API. Consistent across updates, consent required, synthesize by voice ID.
Give a signature character one cloned voice across every line and update.
Key facts:
- Clone a character or actor voice from a short sample
- Consistent across scenes and updates
- Synthesize new lines by voice ID
- Consent required
Q: Can I clone a character voice for a game?
A: Yes. With consent, clone a signature character or actor voice from a short sample using the Speechify Build API, then generate new lines in that voice by its voice ID. The character keeps one consistent voice across scenes and post-launch updates, without re-booking the original actor for every addition.
Q: How does it help with updates?
A: New content and patches often need new lines. With a cloned character voice, you synthesize the new lines by voice ID and they match the existing ones, so a character sounds the same in launch content and in later updates.
Q: Is consent required to clone an actor?
A: Yes. A consent record with the actor's full name and email is required to create the voice, so a performer's voice is cloned only with authorization.
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URL: https://speechify.ai/voice-cloning/podcasts
Title: Voice Cloning for Podcasts — A Signature Host Voice
Clone a host voice for podcasts with the Speechify Build API. Consistent episodes, cross-language reach, consent required. From a short sample.
Give a podcast one signature host voice across every episode.
Key facts:
- Clone a host voice from a short sample
- Consistent voice across every episode
- Cross-language
- Consent required
Q: Can I clone a host voice for a podcast?
A: Yes. With consent, clone a host's voice from a short sample using the Speechify Build API, then generate episode audio from a script in that voice. Every episode uses the same voice ID, so the show keeps one signature host voice, and the clone can speak across 30+ languages for localized editions.
Q: Why clone instead of using a catalog voice?
A: A cloned host voice is the show's identity. Listeners recognize it, and it stays consistent even when the host cannot record. A catalog voice works for generic narration, but a signature podcast wants its own voice.
Q: Do I need the host's consent?
A: Yes. Creating the voice requires a consent record with the host's full name and email. You clone a voice you are authorized to clone.
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URL: https://speechify.ai/voice-cloning/consent-and-safety
Title: Voice Cloning Consent and Safety — Built In, Required
The Speechify Build API is moving voice cloning to verified consent: an issued phrase, read aloud, checked and retained. Unverified cloning is being retired.
Consent is required on every clone, and verification is replacing assertion as unverified cloning is retired.
Key facts:
- Consent is required on every clone
- Verified flow: the speaker reads a Speechify-issued phrase, the recording is matched against the voice sample, and it is retained as the consent record
- The unverified consent-JSON flow is deprecated and being retired
- Cloning available on paid plans, not Free
Q: Is consent required to clone a voice?
A: Yes, always. Creating a voice on the Speechify Build API requires a consent record. On the verified flow the speaker reads a phrase Speechify issues, and the recording is checked against that phrase, matched against the voice sample being cloned, and retained. The remaining unverified integrations, which assert consent as a name and email, are deprecated and will be switched off on a date announced ahead of time.
Q: What does the consent record contain?
A: On the verified flow, a recording of the speaker reading a single-use phrase issued by the consent-challenge endpoint, plus the full name bound to that challenge. Speechify transcribes the recording, matches it against the issued phrase, matches the speaker against the voice sample being cloned, and retains it as evidence for the voice. Voices created on the outgoing flow carry an asserted name and email instead.
Q: Who can use voice cloning?
A: Cloning is available on the paid plans, Starter, Pro, Scale, and Enterprise, and is not included on Free. A Free-tier attempt returns a 402 with voice_cloning_not_included.
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URL: https://speechify.ai/voice-cloning/fine-tuned
Title: Fine-Tuned Voice Cloning — Best Quality from Hours of Audio
Fine-tuned voice cloning trains on hours of audio for the best quality. Arranged with sales, consent required, on the Speechify Build API.
Train on hours of audio for the highest-fidelity cloned voice.
Key facts:
- Trained on hours of audio
- Best quality tier
- Arranged with sales
- Consent required
Q: What is fine-tuned voice cloning?
A: Fine-tuned voice cloning trains on hours of a speaker's audio to produce the best-quality clone. Unlike zero-shot cloning from a short sample, it invests a larger dataset and a training step for higher fidelity. It is arranged with sales and requires consent.
Q: When should I choose fine-tuned over zero-shot?
A: Choose fine-tuned when good quality is not enough and you need the best, and you can supply hours of audio. Choose zero-shot when you want a self-serve clone from a short sample quickly. The tiers trade setup effort for fidelity.
Q: How do I get fine-tuned cloning?
A: It is arranged with sales, because it involves collecting hours of audio and running a fine-tune. Contact sales to set up the engagement.
--------------------------------------------------------------------------------
URL: https://speechify.ai/voice-cloning/languages
Title: Voice Cloning Languages — 30+ Supported
Cloned voices speak across 30+ languages on the Speechify Build API. One voice ID, every supported language.
A cloned voice reaches every one of the 30+ supported languages.
Key facts:
- 30+ languages supported
- One cloned voice covers all
- simba-3.2 clones need manual approval
- Consent required
Q: How many languages do cloned voices support?
A: Cloned voices speak across all 30+ supported languages. A single cloned voice ID covers the full set, so one clone reaches every supported language without cloning again per language.
Q: Which models play cloned voices?
A: Cloned voices run self-serve on `simba-3.0`, across English and six European languages. The curated simba-3.2 voice set plays cloned voices too, but each one currently requires manual Speechify approval. The full 30+ language range for a clone is available on request.
Q: Do I need a separate clone per language?
A: No. One cloned voice covers every supported language. Localizing is a synthesis job with the same voice ID, not a repeat of the cloning step.
--------------------------------------------------------------------------------
URL: https://speechify.ai/voice-cloning/multilingual
Title: Multilingual Voice Cloning — One Voice, 30+ Languages
A cloned voice speaks 30+ languages. Keep one voice across every language on the Speechify Build API. Consent required.
One cloned voice speaks across every supported language.
Key facts:
- Cloned voice works across 30+ languages
- One clone, every language
- One voice ID for every language
- Consent required
Q: Can a cloned voice speak multiple languages?
A: Yes. A cloned voice works across all 30+ supported languages, so one voice ID speaks every supported language. You clone once, with consent, and synthesize the same voice in any language rather than cloning a separate voice per language.
Q: Which model powers multilingual cloning?
A: Cloned voices run self-serve on `simba-3.0`, across English and six European languages. The curated simba-3.2 voice set plays cloned voices too, but each one currently requires manual Speechify approval. Speaking one clone across the full 30+ language set is available on request - talk to us.
Q: Do I clone once or per language?
A: Once. A single cloned voice ID covers every supported language, so there is no per-language cloning step.
--------------------------------------------------------------------------------
URL: https://speechify.ai/voice-cloning/zero-shot
Title: Zero-Shot Voice Cloning — Clone from One Short Sample
Zero-shot voice cloning creates a voice from a 10-30 second sample, self-serve via the Speechify Build API. Good quality, consent required.
One short sample is enough to create a usable cloned voice.
Key facts:
- Clone from a 10-30 second clean sample
- Self-serve via API or Console
- Good quality tier
- Consent required
Q: What is zero-shot voice cloning?
A: Zero-shot voice cloning creates a usable voice from a single short sample, without a separate training run. On the Speechify Build API you send 10 to 30 seconds of clean speech and a consent record, and you get a voice ID back with good quality. It is the self-serve, fast path to a cloned voice.
Q: How much audio does zero-shot need?
A: A clean sample of 10 to 30 seconds, under a minute and under 5MB, is enough. There is no lengthy data collection or fine-tuning step; the model clones directly from that sample.
Q: What quality does it give?
A: Zero-shot cloning produces good quality, suitable for production use. When the best possible quality is required, fine-tuned cloning trains on hours of audio instead.
--------------------------------------------------------------------------------
URL: https://speechify.ai/how-to-clone-a-voice
Title: How to Clone a Voice: A Step-by-Step 2026 Guide
Clone a voice in four steps: record a sample, capture consent, POST to /v1/voices, synthesize by voice ID. A developer guide to the Build API.
Clone a voice in four steps: sample, consent, create, synthesize.
Key facts:
- Record a 10-30 second clean sample
- Capture consent (full name and email)
- POST /v1/voices with multipart/form-data
- Synthesize with the returned voice ID
Q: How do I clone a voice?
A: Record a clean 10-to-30-second sample, capture the speaker's consent (full name and email), then POST to /v1/voices as multipart/form-data with the name, gender, sample, and consent. You receive a voice ID, which you pass to POST /v1/audio/speech to synthesize any text in the cloned voice.
Q: What sample quality do I need?
A: Use 10 to 30 seconds of clean speech, under a minute and under 5MB, with no background noise. Sample quality is the biggest factor in the result for zero-shot cloning.
Q: Which models can play my cloned voice?
A: Cloned voices run self-serve on `simba-3.0`, which covers English and six European languages. The curated simba-3.2 voice set plays cloned voices too, but each one currently requires manual Speechify approval. Reaching the full 30+ language set with one clone is available on request - talk to us.
--------------------------------------------------------------------------------
URL: https://speechify.ai/voice-cloning-ethics
Title: Voice Cloning Ethics: Consent, Rights, and Safety
Ethical voice cloning starts with consent. Learn the principles and how the Speechify Build API enforces a required consent record on every clone.
Ethical voice cloning starts with consent, enforced by design.
Key facts:
- Consent is required on every clone
- Consent record: full name and email
- No create path skips consent
- Clone only voices you are authorized to use
Q: Is voice cloning ethical?
A: Voice cloning is ethical when it is done with consent and used for voices you are authorized to use. The risk is cloning someone without permission. Responsible platforms make consent a requirement: on the Speechify Build API, creating a voice requires a consent record, so a clone cannot be made without authorization by design.
Q: What consent does voice cloning require?
A: Creating a voice requires a consent record containing the speaker's full name and email. It is a mandatory field on the create call, and there is no path that omits it, so consent is a precondition of cloning rather than an optional step.
Q: How do I use voice cloning responsibly?
A: Clone only your own voice or voices you have explicit permission to use, capture consent honestly, and be transparent with your audience about synthetic voices. The API enforces the consent record; the rest is your use of it.
--------------------------------------------------------------------------------
URL: https://speechify.ai/voice-cloning-pricing-guide
Title: Voice Cloning Pricing: How Cloning Is Billed
Voice cloning is a Build feature on paid plans, not a separate product. Synthesis is billed per character. Here is how cloning pricing works.
Cloning is part of Build; synthesis is billed per character like TTS.
Key facts:
- Cloning is a Build feature, not a separate product
- Included on Starter, Pro, Scale, Enterprise (not Free)
- Synthesis billed per character like TTS
- Free tier returns 402 voice_cloning_not_included
Q: How much does voice cloning cost?
A: Voice cloning is a Build feature rather than a separate product, so it shares the Build API and pricing. It is included on the paid plans, Starter, Pro, Scale, and Enterprise, and synthesis with a cloned voice is billed per character just like text-to-speech. There is no separate per-clone product price.
Q: Is voice cloning available on the free plan?
A: No. Cloning is included on Starter, Pro, Scale, and Enterprise, not on Free. A Free-tier attempt to clone returns a 402 with the code voice_cloning_not_included.
Q: Does synthesizing a cloned voice cost more?
A: No. Synthesis is billed per character of text regardless of whether the voice is a catalog voice or a cloned one, so speaking with a clone costs the same per character as any other voice.
--------------------------------------------------------------------------------
URL: https://speechify.ai/what-is-voice-cloning
Title: What Is Voice Cloning? A Plain Definition for 2026
Voice cloning recreates a specific voice from an audio sample, then synthesizes speech in it. Here is how it works and why consent matters.
Voice cloning recreates a specific voice from a sample. Here is the plain definition.
Key facts:
- Recreates a specific voice from an audio sample
- Then synthesizes any text in that voice
- Consent is required to create a voice
- Zero-shot from a short sample or fine-tuned from hours
Q: What is voice cloning?
A: Voice cloning is technology that recreates a specific person's voice from an audio sample, then synthesizes any text in that voice. Unlike stock text-to-speech, which uses catalog voices, cloning reproduces a particular voice. Creating one requires the speaker's consent, captured as a record with their full name and email.
Q: How does voice cloning work?
A: You provide an audio sample and a consent record, and the system builds a voice you can synthesize with by ID. Zero-shot cloning works from a short 10-to-30-second sample with good quality; fine-tuned cloning trains on hours of audio for the best quality. After that, you generate speech in the voice like any other.
Q: Is voice cloning legal and safe?
A: Responsible voice cloning requires consent. On the Speechify Build API, creating a voice requires a consent record with the speaker's full name and email, and there is no path that skips it, so voices are created only with authorization.
--------------------------------------------------------------------------------
URL: https://speechify.ai/alternatives/cartesia
Title: The 6 best Cartesia alternatives for developers, tested July 2026
The best Cartesia alternative for most developers in 2026 is SpeechifyAI: Simba 3.2 ranks above Cartesia Sonic 3.5 on Artificial Analysis' blind Speech Arena, at $10 per 1M characters versus $49. Deepgram (STT plus TTS), OpenAI (existing stack), Rime (on-prem CX), ElevenLabs (voice breadth) and Hume (emotional control) round out the list. We tested every one hands-on.
How we tested: I opened Cartesia's playground and every alternative's demo in a fresh browser session on the same day, synthesized the same test passage on each (including Sonic 3.5 on Cartesia once I had made an account), screenshotted the real sessions and the sign-in walls platforms put up before they let you synthesize custom text, and pulled every price from the vendor's live pricing page that afternoon. For voice quality I do not trust my own ears as a benchmark, so quality rankings come from Artificial Analysis' Speech Arena, a blind listener-preference Elo leaderboard, as it stood on the day of testing.
The alternatives, ranked:
1. SpeechifyAI — Best price-to-quality for production TTS and all-in voice agents, billed per character and per minute rather than in credits (https://speechify.ai)
2. Deepgram Aura-2 — Consolidating speech-to-text and text-to-speech on one enterprise vendor with transparent per-character pricing (https://deepgram.com)
3. OpenAI gpt-4o-mini-tts — Teams already on the OpenAI stack that want promptable, low-cost speech (https://developers.openai.com/api/docs/guides/text-to-speech)
4. Rime Coda — High-volume contact-center voices with on-prem and VPC deployment control (https://rime.ai)
5. ElevenLabs — The largest off-the-shelf community voice library and self-serve cloning (https://elevenlabs.io)
6. Hume Octave 2 — Expressive, emotion-directed speech and empathic voice interfaces (https://www.hume.ai)
export const img = (name) => `/images/alternatives/cartesia/${name}.webp`;
I spent an afternoon this July doing something I recommend to anyone evaluating voice AI vendors: I opened every serious Cartesia competitor in a clean browser, tried to make each one say the same sentence, and wrote down what actually happened. Not what the landing pages promise. What happened.
The test passage, for the record: "Before we ship on Thursday, can you re-run the 4,096-token benchmark? Last night's build cut latency from 210 to 87 milliseconds, which honestly surprised everyone." Numbers, an abbreviation, a question, a dry aside. If a model mangles any of those, you hear it immediately.
This page is the result. It is a working document (the tested-on date above is real, and we re-verify prices when it changes), and because SpeechifyAI is on its own list, every claim here links to a source you can check without trusting us.
## Why developers leave Cartesia
Let me be fair to Cartesia first, because it is a genuinely good product and the internet's "Cartesia alternatives" lists rarely say so. Sonic 3.5 is evaluated on the same blind Speech Arena, and Cartesia's whole identity is speed: the [Sonic page](https://www.cartesia.ai/sonic) claims sub-90ms model latency. If you are building a real-time voice agent and latency is your religion, Cartesia earned its reputation.
Two things still push developers to look elsewhere, and neither is a secret.
**The per-character math is expensive, and you pay in credits.** Cartesia does not price in characters; it prices in credits, at 15 credits per second of generated audio. On the [pricing page](https://www.cartesia.ai/pricing) as of July 2026, the free tier is 20K credits (about 27 minutes of audio) with no commercial license, Pro at $5/month adds commercial use and instant cloning, Startup at $49 covers roughly 1.25M credits, and Scale is $299 for about 8M. Artificial Analysis normalizes Sonic 3.5 to about $49 per 1M characters, a premium price for its arena Elo, and roughly 5x what top-tier arena voices charge. Forecasting a monthly bill in credits-per-second is arithmetic that per-character vendors let you skip.
**You cannot test it with your own text without an account.** Cartesia's [playground](https://play.cartesia.ai) redirects straight to a GitHub/Google/email sign-in before you can synthesize a single custom sentence, and the public marketing site only offers canned sample clips. It was one of the platforms in this test that would not run my test passage until I had made an account, and signing up means accepting the Terms and Acceptable Use policy sight unseen.
To be fair to Cartesia, once I was through the wall I ran the test passage on Sonic 3.5 directly, and it rendered cleanly and quickly, numbers and abbreviation intact. The model quality is genuinely not in question; the friction is simply that you have to create an account and accept the Terms before you can hear that for yourself.
None of this makes Cartesia a bad product. It makes it a product you should compare on price before you scale on it, which is what the rest of this page is for.
## How I ranked quality
A vendor telling you their model sounds best is worthless, including when the vendor is us. So this list leans on the one public benchmark that works like a proper blind test: [Artificial Analysis' Speech Arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice), where listeners hear two unlabeled clips and pick the better one, producing an Elo score with confidence intervals.
In July 2026 the provider-voices board had Alibaba's Qwen-Audio-3.0-TTS-Plus at Elo 1,235, SpeechifyAI's Simba 3.2 at Elo 1,240, Google's Gemini 3.1 Flash TTS at Elo 1,215 and Cartesia's Sonic 3.5 at Elo 1,208, a genuinely strong showing that is worth saying plainly. The gap that matters is not quality between Cartesia and the leaders; it is price.
Keep that price column in view as you read the breakdowns. The gap between what top arena voices cost and what Cartesia charges per character is the single most useful fact on this page.
## The comparison at a glance
| Platform | Model tested | Price per 1M chars (API) | Free tier | Commercial use on free tier | Public playground |
| --- | --- | --- | --- | --- | --- |
| [SpeechifyAI](#1-speechifyai) | Simba 3.2 | $10 (Starter) to $6 (Scale) | 500K chars/mo | Yes | Yes, no login |
| [Deepgram](#2-deepgram-aura-2) | Aura-2 | $30 | $200 credit, no card | Yes (credit) | Previews only |
| [OpenAI](#3-openai-gpt-4o-mini-tts) | gpt-4o-mini-tts | Token-priced (tts-1: $15) | None (pay as you go) | n/a | Yes (openai.fm), no login |
| [Rime](#4-rime-coda) | Coda | $50 (Starter) | 3,000 minutes | Not stated on pricing page | Canned demos only |
| [ElevenLabs](#5-elevenlabs) | Eleven v3 / Flash v2.5 | $100 / $50 | ~10K chars/mo | No | No, login required |
| [Hume](#6-hume-octave-2) | Octave 2 | $50 to $150 by plan | 10K chars/mo | No, Creator ($14/mo) and up | Login required |
| Cartesia (baseline) | Sonic-3.5 | $49 (per Artificial Analysis) | 20K credits (~27 min)/mo | No, Pro ($5/mo) and up | No, login required |
Prices pulled from each vendor's live pricing page in July 2026; the linked sources at the bottom of this page are the exact pages I used. Cartesia sells credits rather than characters, so its per-character figure uses Artificial Analysis' normalization.
The fastest way to pressure-test that table is with real audio: Sign up free at https://platform.speechify.ai/signup (500K characters a month, no card) and run your own script through us and Cartesia side by side.
## 1. SpeechifyAI
Yes, our own platform is on the list, and you should treat that with exactly the suspicion it deserves. Here is the case, made entirely from things you can verify without believing a word we say.
The quality claim is not ours: Simba 3.2's Elo 1,240 on [Artificial Analysis' blind arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice) is a third-party number produced by listeners who did not know which model they were hearing, and it sits 32 Elo above Cartesia's Sonic 3.5. The price claim is on our [public pricing page](https://speechify.ai/pricing): $10 per 1M characters on the $10/month Starter plan, $8 on Pro, $6 on Scale. Against Cartesia's roughly $49 per 1M that is a 5x gap, for a higher arena score.
The hands-on test was the easiest of the day, because the [speechify.ai](https://speechify.ai) homepage is itself a blind test: it plays our synthesis of a passage next to an unlabeled flagship competitor and lets you pick, no account needed. Cartesia, by contrast, would not let me synthesize a word without signing up first.
The billing model is the other half of the pitch, and it is aimed squarely at Cartesia's weak spot. There are no credits to convert and no seconds-of-audio arithmetic: you add a prepaid balance and we draw it down at the real per-character and per-minute rate, with optional auto top-up so production never stalls. Voice-agent minutes are all-in, one line item covering LLM, speech-to-text, text-to-speech and telephony orchestration, from $0.07 per minute (and $0.06 at Enterprise volume) rather than a platform fee with the model billed separately on top.
On voices, Simba 3.2 serves the full English voice roster, each voice tuned for a wide dynamic range. The wider Simba catalog runs 900+ voices across 30+ languages, and self-serve cloning from the $10 plan means your brand's own voice is never on anyone else's menu. The free tier is the one I would point any evaluating developer at: 500K characters per month, commercial use included, with a hard cap instead of surprise overages, and no account wall between you and your first synthesis. Sign up free at https://platform.speechify.ai/signup and run my test sentence against Cartesia today; the whole evaluation costs nothing.
**Pick SpeechifyAI if:** you want high arena quality at a fifth of Cartesia's price, billed per character and per minute instead of in credits, or all-in voice-agent minutes (LLM, STT, TTS and telephony orchestration in one rate, quoted per contract).
**Stay away if:** sub-90ms model latency is a hard requirement you will benchmark before anything else.
## 2. Deepgram Aura-2
Deepgram is the consolidation play, and for a Cartesia user building voice agents it is the most natural switch on this list: if you already use them for speech-to-text (many voice-agent teams do), Aura-2 puts synthesis on the same vendor, same console, same invoice. Their [playground](https://playground.deepgram.com/?endpoint=speak) let me browse and preview the Aura-2 voice list without an account, though typing my own test passage required signing up, halfway between OpenAI's fully open demo and Cartesia's wall.
Pricing is refreshingly plain: [Aura-2 costs $0.030 per 1K characters](https://deepgram.com/pricing) pay-as-you-go ($30 per 1M), Aura-1 half that, and every new account gets $200 of usage credit with no credit card, the most generous no-strings trial in this test. The trade-off is scope: the voice list is a curated few dozen, primarily English with a handful of other languages, and nobody picks Aura-2 for expressive character work. It is built to sound professional on a phone line, and does. Deepgram does not appear on the Speech Arena, so there is no blind-test Elo to cite, one reason it is second here and not first. If Deepgram is the platform you are actually leaving, our [Deepgram alternatives](/alternatives/deepgram) guide ranks the field from that side.
**Pick Deepgram if:** you want STT and TTS from one enterprise vendor with transparent per-character pricing, or you want $200 of real testing room.
**Stay away if:** you need wide language coverage, a large characterful voice catalog, or a public arena quality score.
## 3. OpenAI gpt-4o-mini-tts
OpenAI's TTS is the path of least resistance if your backend already talks to their API, and their [openai.fm](https://www.openai.fm) demo was the most open of the day: it is fully public, and alongside voice selection you write a free-text "vibe" prompt that steers delivery. I gave it my test passage with the Marin voice and a Sincere vibe, and it handled "4,096-token benchmark" cleanly, no account required, which is a pointed contrast with Cartesia.
Pricing is token-based rather than per-character, which makes like-for-like comparison annoying: [OpenAI's pricing page](https://developers.openai.com/api/docs/pricing) lists gpt-4o-mini-tts at $0.60 per 1M text input tokens plus $12.00 per 1M audio output tokens (audio output dominates the bill), with the older character-priced tts-1 at $15 per 1M characters and tts-1-hd at $30. On the arena, tts-1-hd ranks in the high twenties, well below Cartesia, so this is a convenience-and-cost pick, not a quality upgrade.
The catch is the ceiling. Eleven preset voices, no voice cloning, no per-word timestamps for caption alignment, and voice steering by prompt is expressive but not deterministic: the same vibe prompt can read differently across generations. If OpenAI is the platform you are actually weighing, our dedicated [OpenAI alternatives](/alternatives/openai) guide ranks the same field for its users.
**Pick OpenAI if:** you are already on their stack and want cheap, promptable speech without another vendor contract.
**Stay away if:** you need voice cloning, brand-locked custom voices, or arena-grade quality.
## 4. Rime Coda
Rime is the contact-center specialist, and it competes with Cartesia most directly on the ground Cartesia cares about: real-time, high-volume phone conversations. Founded by linguists and pointed hard at healthcare, banking and food ordering, its flagship Coda headlines 600+ voices across 50+ languages, and Rime is the one vendor here leading with on-prem and VPC deployment on its pricing page, which is exactly what a compliance-bound enterprise wants to read.
[Starter pricing](https://rime.ai/pricing) is $0.05 per 1K characters ($50 per 1M) with a properly generous 3,000 free minutes on signup and 20 concurrent generations. On the arena, Coda ranks mid-pack (Elo 1,042), below Cartesia on raw quality, so the reason to move here is deployment control and telephony fit, not a leaderboard win. The public site only plays canned industry demos, so my test passage went unspoken here too.
**Pick Rime if:** you run high-volume customer calls and need deployment control (on-prem/VPC) plus voices tuned for telephony.
**Stay away if:** you want self-serve evaluation with custom text, or arena-evaluated quality is the priority.
## 5. ElevenLabs
ElevenLabs is the default name in AI voice, and it is the switch to make when voice *variety* is why you are leaving Cartesia. Its community library is the largest anywhere at 10,000+ voices, its instant and professional cloning are self-serve, and its ecosystem (dubbing, music, sound effects) is broader than any competitor's. On the [pricing page](https://elevenlabs.io/pricing/api) that breadth costs $0.05 per 1K characters for Flash/Turbo and $0.10 per 1K for Multilingual v2/v3, which is $50 to $100 per 1M characters, the most expensive per-character rate in this comparison.
On quality it no longer leads: Eleven v3 ranks eleventh on the arena (Elo 1,175), below Cartesia's Sonic 3.5, and its public TTS page requires an account before you can synthesize custom text, so like Cartesia it fails the try-before-you-buy test. If you are leaving ElevenLabs specifically, our [ElevenLabs alternatives](/alternatives/elevenlabs) guide covers the field from that angle.
**Pick ElevenLabs if:** browsing thousands of off-the-shelf character voices, or the dubbing/music/SFX ecosystem, is load-bearing for your product.
**Stay away if:** you are optimizing cost per character, or arena-evaluated quality is your priority over voice variety.
## 6. Hume Octave 2
Hume comes at speech from emotion-science research, and it shows in the product shape: Octave 2 is built to be directed ("sound like a tired night-shift nurse delivering good news") rather than just voiced, and their EVI line does full speech-to-speech conversation with empathic responses. For interactive characters, companions and mental-health-adjacent products, nothing else on this list is aimed as squarely at the job.
The [pricing page](https://www.hume.ai/pricing) is plan-gated rather than flatly usage-priced: Free gives 10K characters a month, Creator at $14/month gives 140K with overage at $0.15 per 1K, and the rate falls with plan size to $0.05 per 1K on the $500 Business tier. That works out to $50 to $150 per 1M characters, so Hume is a specialty spend, not a discount off Cartesia. Unusually, voice cloning is unlimited on every tier including Free. If Hume is the platform you are actually weighing, our [Hume alternatives](/alternatives/hume) guide ranks the field from that side.
**Pick Hume if:** emotional direction and empathic voice interaction are the product, not a garnish.
**Stay away if:** you are optimizing cost per character for bulk narration or high-volume agents; the math does not favor it.
## Also considered, and a warning about PlayHT
Google, Microsoft Azure and Amazon Polly all sell capable TTS, and if your company already lives in one of those clouds, procurement gravity may decide for you (Google's Gemini 3.1 Flash TTS ranks third on the arena at $18.3 per 1M, a legitimately strong option). We compare them individually on our [text-to-speech comparison pages](/compare/build/text-to-speech).
MiniMax's Speech 2.8 HD ranks well on the arena but at $100 per 1M chars it prices like the premium tier without the ecosystem. Inworld's realtime models rank impressively and are worth watching if you build games or interactive characters and, like Cartesia, care about latency above all.
And PlayHT deserves its own paragraph. It appeared on virtually every "voice AI alternatives" list ever written, often as the default recommendation. Meta acquired the PlayAI team in mid-2025, and when I checked in July 2026, both play.ht and play.ai failed to resolve at all. Every team that built on it has been forced off. Treat that as the permanent footnote on this category: the voice platform you pick is a dependency, so weigh the vendor's incentives to keep serving developers, not just the demo quality.
## Which alternative fits your use case
- **Real-time voice agents on a budget:** SpeechifyAI, for one all-in per-minute rate with LLM and telephony included and no credit math; Cartesia only if raw model latency is the single metric you will benchmark first.
- **One vendor for STT + TTS:** Deepgram. The $200 no-card credit also makes it the cheapest platform to evaluate seriously.
- **Already on OpenAI, shipping this week:** OpenAI's gpt-4o-mini-tts. Accept the fixed voice set and move on.
- **Regulated contact centers:** Rime, for the on-prem/VPC deployment story alone.
- **Voice variety and self-serve cloning:** ElevenLabs, if the 10,000+ voice library is the point and you can absorb the per-character cost.
- **Emotive characters and empathic interfaces:** Hume Octave, priced as a specialty, not a saving.
- **Staying on Cartesia:** defensible if sub-90ms latency is genuinely load-bearing and you will assemble the surrounding stack yourself. Renegotiate with the leaderboard's price column open in another tab.
## Migrating off Cartesia
The practical part. TTS migrations are usually smaller than teams fear, because the integration surface is thin: one synthesis endpoint, a voice ID, and an audio format.
1. **Re-map voices first.** This is the real work. Shortlist replacement voices on the new platform and A/B them against your current Cartesia output with your actual content, not the vendor's demo copy.
2. **Translate credits into real per-character cost.** Before you compare, convert your Cartesia credit spend (15 credits per second of audio) into characters or minutes so you are comparing the same unit. This is usually the moment the price gap becomes obvious.
3. **Run both in parallel for a week.** Per-character billing makes dual-running cheap insurance: mirror a slice of production traffic to the new vendor and diff failure rates, latency and listener feedback.
4. **Check latency against your real bar, not the headline.** Cartesia's sub-90ms claim is model latency; measure end-to-end on your own network with your own text, because that is the number your users hear. SpeechifyAI's [API docs](https://docs.speechify.ai) cover streaming, SSML and speech-marks support.
If you are weighing us specifically against Cartesia feature by feature, the [SpeechifyAI vs Cartesia comparison](/compare/build/text-to-speech/cartesia) goes deeper on the head-to-head. And the [free tier](https://speechify.ai/pricing) exists precisely so you can rerun every test on this page yourself, including the one where you do not take a vendor's word for anything: Sign up free at https://platform.speechify.ai/signup, no card, and your first 500K characters are on us.
FAQ:
Q: What is the best Cartesia alternative for developers in 2026?
A: For most production TTS workloads it is SpeechifyAI: on Artificial Analysis' blind Speech Arena leaderboard (July 2026), Simba 3.2 scores Elo 1,240 at $10 per 1M characters, while Cartesia's Sonic 3.5 scores Elo 1,208 and roughly $49 per 1M by the same board's normalization. If your one deciding metric is raw model latency, Cartesia remains a reasonable choice; on price-to-quality it is beaten.
Q: Is Cartesia Sonic still worth using?
A: Yes, for latency-critical work. Sonic 3.5 is evaluated on the same blind Speech Arena, and Cartesia advertises sub-90ms model latency across dozens of languages. If shaving every millisecond off agent response time is the deciding factor and you are happy to assemble the surrounding stack yourself, Cartesia is a strong product. Most teams, though, are choosing on cost per character, where it is expensive.
Q: How much cheaper are Cartesia alternatives?
A: Cartesia sells credits rather than characters, and Artificial Analysis normalizes Sonic 3.5 to about $49 per 1M characters. Against that, SpeechifyAI charges $10 per 1M on Starter down to $6 on Scale, OpenAI's tts-1 is $15 per 1M, and Deepgram Aura-2 is $30, so like-for-like savings of roughly 2x to 5x are realistic for comparable or better arena quality.
Q: Why does Cartesia bill in credits instead of per character?
A: Cartesia's plans meter usage in credits: text-to-speech costs 15 credits per second of audio, the free tier includes 20K credits (about 27 minutes) a month, and voice cloning costs a one-time 225 credits. Because a credit maps to seconds of audio rather than input characters, forecasting a monthly bill takes arithmetic that per-character vendors like SpeechifyAI, Deepgram and OpenAI's legacy models let you skip.
Q: Which Cartesia alternative has the best free tier for commercial use?
A: SpeechifyAI's free tier includes 500K TTS characters per month with commercial use allowed and a hard spending cap. Deepgram gives $200 of pay-as-you-go credit with no card, and Rime advertises 3,000 free minutes on signup. Cartesia's own free tier does not include a commercial license at all; commercial use starts on the $5 Pro plan.
--------------------------------------------------------------------------------
URL: https://speechify.ai/alternatives/deepgram
Title: The 6 best Deepgram alternatives for developers, tested July 2026
The best Deepgram alternative for text-to-speech in 2026 is SpeechifyAI: Simba 3.2 is scored on Artificial Analysis' blind Speech Arena, which Aura is not, at $10 per 1M characters against Aura-2's $30, with multilingual voices and self-serve cloning Aura lacks. Cartesia (latency), Rime (telephony), OpenAI (stack), ElevenLabs (voice breadth) and Hume (emotion) round out the list. We tested every one hands-on.
How we tested: I opened Deepgram's playground and every alternative's demo in a fresh browser session on the same day, synthesized the same test passage on each where the platform allowed it, screenshotted the real sessions and the sign-in walls platforms put up before they let you synthesize custom text, and pulled every price from the vendor's live pricing page that afternoon. For voice quality I do not trust my own ears as a benchmark, so quality rankings come from Artificial Analysis' Speech Arena, a blind listener-preference Elo leaderboard, as it stood on the day of testing.
The alternatives, ranked:
1. SpeechifyAI — Best price-to-quality for production TTS and all-in voice agents, with multilingual voices and self-serve cloning Aura lacks (https://speechify.ai)
2. Cartesia Sonic — Voice agents where arena-proven quality and sub-90ms model latency are the deciding factors (https://www.cartesia.ai)
3. Rime Coda — High-volume contact-center voices with on-prem and VPC deployment, the closest match to Deepgram's telephony niche (https://rime.ai)
4. OpenAI gpt-4o-mini-tts — Teams already on the OpenAI stack that want promptable, low-cost speech (https://developers.openai.com/api/docs/guides/text-to-speech)
5. ElevenLabs — The largest off-the-shelf community voice library and self-serve cloning (https://elevenlabs.io)
6. Hume Octave 2 — Expressive, emotion-directed speech and empathic voice interfaces (https://www.hume.ai)
export const img = (name) => `/images/alternatives/deepgram/${name}.webp`;
I spent an afternoon this July doing something I recommend to anyone evaluating voice AI vendors: I opened every serious Deepgram competitor in a clean browser, tried to make each one say the same sentence, and wrote down what actually happened. Not what the landing pages promise. What happened.
The test passage, for the record: "Before we ship on Thursday, can you re-run the 4,096-token benchmark? Last night's build cut latency from 210 to 87 milliseconds, which honestly surprised everyone." Numbers, an abbreviation, a question, a dry aside. If a model mangles any of those, you hear it immediately.
This page is the result. It is a working document (the tested-on date above is real, and we re-verify prices when it changes), and because SpeechifyAI is on its own list, every claim here links to a source you can check without trusting us.
## Why developers leave Deepgram
Let me be fair to Deepgram first, because it is a serious platform and this is a text-to-speech comparison, not a verdict on the whole company. Deepgram's Nova speech-to-text is genuinely world-class across [45+ languages](https://deepgram.com/pricing), and the whole platform is built for enterprise trust: SOC 2 Type 1 and 2, HIPAA with BAAs, GDPR with an EU data-residency endpoint, and on-prem or VPC deployment. If you are here, you almost certainly came for the STT and are now asking whether Aura, its text-to-speech, is the right voice for your product too.
For a lot of teams, the honest answer is "not the best one available," for three reasons.
**Aura has no blind-arena quality score.** Every other vendor on this page has a published Elo on [Artificial Analysis' Speech Arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice), a blind listener-preference leaderboard. Deepgram's Aura does not appear on it at all, so you are trusting Deepgram's own description of how it sounds rather than a third-party blind test. For a phone-line voice that is often fine; for anything customer-facing where quality is the product, it is a gap.
**The voice set is small and English-centric.** Aura-2 ships a curated few dozen voices tuned to sound professional on a call, primarily English. There is no self-serve voice cloning, so your brand's own voice is not an option, and wide language coverage on the TTS side is not the story (that is the STT side's strength). To Deepgram's credit, the [playground](https://playground.deepgram.com/?endpoint=speak) lets you preview the whole Aura-2 voice list without an account, more open than the vendors that wall it, though typing your own test passage still needs a free sign-up.
**The per-character price is mid-market.** On the [pricing page](https://deepgram.com/pricing) Aura-2 is $0.030 per 1K characters ($30 per 1M) pay-as-you-go and Aura-1 is $0.0150 per 1K ($15 per 1M). That is refreshingly transparent, but it is three times what top-tier arena voices charge for models that also carry a public quality score.
The good news, and the reason this page is friendlier to Deepgram than most, is that none of this forces an all-or-nothing switch: the TTS integration surface is thin, so you can keep Deepgram for transcription and swap only the voice. More on that at the end.
## How I ranked quality
A vendor telling you their model sounds best is worthless, including when the vendor is us. So this list leans on the one public benchmark that works like a proper blind test: [Artificial Analysis' Speech Arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice), where listeners hear two unlabeled clips and pick the better one, producing an Elo score with confidence intervals.
In July 2026 the provider-voices board had Alibaba's Qwen-Audio-3.0-TTS-Plus at Elo 1,235, SpeechifyAI's Simba 3.2 at Elo 1,240, Google's Gemini 3.1 Flash TTS at Elo 1,215 and Cartesia's Sonic 3.5 at Elo 1,208. Deepgram's Aura is not on the board, which is exactly why "how does it actually sound against these" is a question you cannot answer from Deepgram's site alone.
Keep that price column in view as you read the breakdowns. The gap between what a leaderboard-scored voice costs and what Aura-2 charges is the single most useful fact on this page.
## The comparison at a glance
| Platform | Model tested | Price per 1M chars (API) | Free tier | Arena Elo | Public playground |
| --- | --- | --- | --- | --- | --- |
| [SpeechifyAI](#1-speechifyai) | Simba 3.2 | $10 (Starter) to $6 (Scale) | 500K chars/mo | 1,240 | Yes, no login |
| [Cartesia](#2-cartesia-sonic) | Sonic-3.5 | $49 (per Artificial Analysis) | 20K credits (~27 min)/mo | 1,208 | No, login required |
| [Rime](#3-rime-coda) | Coda | $50 (Starter) | 3,000 minutes | 1,042 | Canned demos only |
| [OpenAI](#4-openai-gpt-4o-mini-tts) | gpt-4o-mini-tts | Token-priced (tts-1: $15) | None (pay as you go) | 1,103 (tts-1-hd) | Yes (openai.fm), no login |
| [ElevenLabs](#5-elevenlabs) | Eleven v3 / Flash v2.5 | $100 / $50 | ~10K chars/mo | 1,175 | No, login required |
| [Hume](#6-hume-octave-2) | Octave 2 | $50 to $150 by plan | 10K chars/mo | 1,056 | Login required |
| Deepgram (baseline) | Aura-2 | $30 | $200 credit, no card | Not ranked | Previews only |
Prices pulled from each vendor's live pricing page in July 2026; the linked sources at the bottom of this page are the exact pages I used. Cartesia sells credits rather than characters, so its per-character figure uses Artificial Analysis' normalization.
The fastest way to pressure-test that table is with real audio: Sign up free at https://platform.speechify.ai/signup (500K characters a month, no card) and run your own script through us and Deepgram side by side.
## 1. SpeechifyAI
Yes, our own platform is on the list, and you should treat that with exactly the suspicion it deserves. Here is the case, made entirely from things you can verify without believing a word we say.
The quality claim is not ours: Simba 3.2's Elo 1,240 on [Artificial Analysis' blind arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice) is a third-party number produced by listeners who did not know which model they were hearing, and it exists precisely where Aura's does not. The price claim is on our [public pricing page](https://speechify.ai/pricing): $10 per 1M characters on the $10/month Starter plan, $8 on Pro, $6 on Scale. Against Deepgram Aura-2's $30 per 1M that is a 3x gap, for an arena-scored model rather than an unranked one.
The hands-on test was the easiest of the day, because the [speechify.ai](https://speechify.ai) homepage is itself a blind test: it plays our synthesis of a passage next to an unlabeled flagship competitor and lets you pick, no account needed.
Where SpeechifyAI most directly answers a Deepgram TTS user is on the three gaps above. Simba 3.2 serves the full English voice roster, and across the Simba family the 900+ voice catalog spans 30+ languages, so multilingual TTS is a first-class story, not an English-first one. Self-serve cloning from the $10 plan means your brand's own voice is on the menu. And voice agents are all-in, one line item covering LLM, speech-to-text, text-to-speech and telephony orchestration, from $0.07 per minute, which lines up almost exactly against Deepgram's own $0.075 per minute Standard voice-agent rate while including the model. On the enterprise trust that brought you to Deepgram, SpeechifyAI carries SOC 2 Type II and SSO at the Enterprise tier.
The free tier is the one I would point any evaluating developer at: 500K characters per month, commercial use included, with a hard cap instead of surprise overages. Sign up free at https://platform.speechify.ai/signup and run my test sentence against Aura today; the whole evaluation costs nothing.
**Pick SpeechifyAI if:** you want arena-evaluated quality where Aura has no score, multilingual voices and self-serve cloning, or all-in voice-agent minutes, at a third of Aura-2's price.
**Stay away if:** you specifically need speech-to-text and text-to-speech from a single vendor and will not split the two (see the migration note below on why you may not have to).
## 2. Cartesia Sonic
If you run Deepgram for real-time voice agents, Cartesia is the quality-and-latency specialist to weigh first. The [Sonic page](https://www.cartesia.ai/sonic) claims sub-90ms model latency for Sonic-3.5, and on [Artificial Analysis' arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice) Sonic 3.5 scores Elo 1,208, a genuinely strong showing and, unlike Aura, a public one.
The trade-offs versus Deepgram are two. Pricing is credit-based rather than per-character (Artificial Analysis normalizes Sonic 3.5 to about $49 per 1M, higher than Aura-2), and the playground gates custom text behind a GitHub/Google sign-in where Deepgram at least lets you preview voices without one. If Cartesia is the platform you end up weighing seriously, our [Cartesia alternatives](/alternatives/cartesia) guide ranks the field from that side.
**Pick Cartesia if:** arena-proven quality and sub-90ms latency for voice agents are the deciding metrics and credit-based billing does not bother you.
**Stay away if:** you want per-character pricing, or to evaluate with your own text before creating an account.
## 3. Rime Coda
Rime is the closest match to the niche Deepgram's Aura actually competes in: high-volume, real-time customer calls. Founded by linguists and pointed hard at healthcare, banking and food ordering, its flagship Coda headlines 600+ voices across 50+ languages, and Rime leads with on-prem and VPC deployment on its pricing page, mirroring the enterprise-deployment story that likely drew you to Deepgram in the first place.
[Starter pricing](https://rime.ai/pricing) is $0.05 per 1K characters ($50 per 1M) with 3,000 free minutes on signup. On the arena, Coda ranks mid-pack (Elo 1,042), so the reason to move here from Aura is telephony fit and deployment control, not a leaderboard jump. The public site only plays canned industry demos, so my test passage went unspoken here too.
**Pick Rime if:** you run regulated, high-volume contact centers and need deployment control (on-prem/VPC) plus voices tuned for telephony.
**Stay away if:** you want self-serve evaluation with custom text, or arena-evaluated quality is the priority.
## 4. OpenAI gpt-4o-mini-tts
OpenAI's TTS is the path of least resistance if your backend already talks to their API, and their [openai.fm](https://www.openai.fm) demo was the most open of the day: it is fully public, and alongside voice selection you write a free-text "vibe" prompt that steers delivery. I gave it my test passage with the Marin voice and a Sincere vibe, and it handled "4,096-token benchmark" cleanly, no account required.
Pricing is token-based rather than per-character: [OpenAI's pricing page](https://developers.openai.com/api/docs/pricing) lists gpt-4o-mini-tts at $0.60 per 1M text input tokens plus $12.00 per 1M audio output tokens, with the older character-priced tts-1 at $15 per 1M characters and tts-1-hd at $30. On the arena, tts-1-hd ranks in the high twenties (Elo 1,103), better documented than Aura but not a quality leader. The ceiling is real: eleven preset voices, no voice cloning, and prompt-based delivery is expressive but not deterministic. If OpenAI is the platform you are actually weighing, our [OpenAI alternatives](/alternatives/openai) guide ranks the same field for its users.
**Pick OpenAI if:** you are already on their stack and want cheap, promptable speech without another vendor contract.
**Stay away if:** you need voice cloning, brand-locked custom voices, or arena-grade quality.
## 5. ElevenLabs
ElevenLabs is the switch to make when voice *variety* is the point. Its community library is the largest anywhere at 10,000+ voices, its instant and professional cloning are self-serve, and its ecosystem (dubbing, music, sound effects) is broader than any competitor's, all of which are exactly the things Aura's curated English set is not built for. On the [pricing page](https://elevenlabs.io/pricing/api) that breadth costs $0.05 per 1K characters for Flash/Turbo and $0.10 per 1K for Multilingual v2/v3, which is $50 to $100 per 1M characters, more than Aura-2.
On quality it ranks eleventh on the arena (Eleven v3, Elo 1,175), above OpenAI and, since Aura is unranked, presumably above it too, though nobody can prove the latter. Its public TTS page requires an account before you can synthesize custom text, so unlike Deepgram's public voice previews you cannot kick the tires anonymously. If you are leaving for voice variety specifically, our [ElevenLabs alternatives](/alternatives/elevenlabs) guide covers the field from that angle.
**Pick ElevenLabs if:** browsing thousands of off-the-shelf character voices, or the dubbing/music/SFX ecosystem, is load-bearing for your product.
**Stay away if:** you are optimizing cost per character, or arena-evaluated quality is your priority over voice variety.
## 6. Hume Octave 2
Hume comes at speech from emotion-science research, and it shows in the product shape: Octave 2 is built to be directed ("sound like a tired night-shift nurse delivering good news") rather than just voiced, and their EVI line does full speech-to-speech conversation with empathic responses. For interactive characters, companions and mental-health-adjacent products, nothing else on this list is aimed as squarely at the job, and it is a very different job than Aura's telephony voices.
The [pricing page](https://www.hume.ai/pricing) is plan-gated rather than flatly usage-priced: Free gives 10K characters a month, Creator at $14/month gives 140K with overage at $0.15 per 1K, and the rate falls with plan size to $0.05 per 1K on the $500 Business tier. That works out to $50 to $150 per 1M characters. Unusually, voice cloning is unlimited on every tier including Free. If Hume is the platform you are actually weighing, our [Hume alternatives](/alternatives/hume) guide ranks the field from that side.
**Pick Hume if:** emotional direction and empathic voice interaction are the product, not a garnish.
**Stay away if:** you are optimizing cost per character for bulk narration or high-volume telephony; the math does not favor it.
## Also considered, and a warning about PlayHT
Google, Microsoft Azure and Amazon Polly all sell capable TTS, and if your company already lives in one of those clouds, procurement gravity may decide for you (Google's Gemini 3.1 Flash TTS ranks third on the arena at $18.3 per 1M, a legitimately strong option). We compare them individually on our [text-to-speech comparison pages](/compare/build/text-to-speech).
MiniMax's Speech 2.8 HD ranks well on the arena but at $100 per 1M chars it prices like the premium tier without the ecosystem. Inworld's realtime models rank impressively and are worth watching if you build games or interactive characters.
And PlayHT deserves its own paragraph. It appeared on virtually every "voice AI alternatives" list ever written, often as the default recommendation. Meta acquired the PlayAI team in mid-2025, and when I checked in July 2026, both play.ht and play.ai failed to resolve at all. Every team that built on it has been forced off. Treat that as the permanent footnote on this category: the voice platform you pick is a dependency, so weigh the vendor's incentives to keep serving developers, not just the demo quality.
## Which alternative fits your use case
- **You bought Deepgram for STT and just want a better voice:** SpeechifyAI. Arena-evaluated quality where Aura has no score, multilingual, self-serve cloning, at a third of the price, and you can keep Deepgram for transcription.
- **Real-time voice agents:** SpeechifyAI for one all-in per-minute rate; Cartesia if arena-proven latency is the single metric you will benchmark first.
- **Regulated, high-volume contact centers:** Rime, for the on-prem/VPC deployment story and telephony-tuned voices closest to Aura's niche.
- **Already on OpenAI, shipping this week:** OpenAI's gpt-4o-mini-tts. Accept the fixed voice set and move on.
- **Voice variety and self-serve cloning:** ElevenLabs, if the 10,000+ voice library is the point and you can absorb the per-character cost.
- **Emotive characters and empathic interfaces:** Hume Octave, priced as a specialty, not a saving.
- **Staying on Deepgram:** entirely defensible if the STT-plus-TTS-on-one-vendor consolidation is worth more to you than TTS quality and price. Just do it with the leaderboard open in another tab.
## Migrating off Deepgram
The practical part, and it is smaller than most because of a Deepgram-specific advantage: you probably do not have to migrate the whole thing.
1. **Split STT from TTS first.** Deepgram's Nova speech-to-text is genuinely strong; there is no reason to move it just because you are moving the voice. The two are separate endpoints, so keep transcription on Deepgram and evaluate TTS on its own.
2. **Re-map voices.** Shortlist replacement voices on the new platform and A/B them against your current Aura output with your actual content, not the vendor's demo copy.
3. **Run both in parallel for a week.** Per-character billing makes dual-running cheap insurance: mirror a slice of production traffic to the new vendor and diff failure rates, latency and listener feedback.
4. **Check streaming and timestamps.** If you rely on low-latency streaming or per-word timing for captions and turn-taking, verify the replacement exposes them before you commit. SpeechifyAI's [API docs](https://docs.speechify.ai) cover streaming, SSML and speech-marks support.
If you are weighing us specifically against Deepgram feature by feature, the [SpeechifyAI vs Deepgram comparison](/compare/build/text-to-speech/deepgram) goes deeper on the head-to-head. And the [free tier](https://speechify.ai/pricing) exists precisely so you can rerun every test on this page yourself, including the one where you do not take a vendor's word for anything: Sign up free at https://platform.speechify.ai/signup, no card, and your first 500K characters are on us.
FAQ:
Q: What is the best Deepgram alternative for text-to-speech in 2026?
A: For most production TTS workloads it is SpeechifyAI: on Artificial Analysis' blind Speech Arena leaderboard (July 2026), Simba 3.2 scores Elo 1,240 at $10 per 1M characters, while Deepgram's Aura-2 costs $30 per 1M and does not appear on the arena at all. SpeechifyAI also adds the multilingual coverage, self-serve voice cloning and all-in voice agents that Deepgram's TTS does not offer.
Q: Is Deepgram's Aura TTS still worth using?
A: Yes, in one situation: if you already run Deepgram for speech-to-text and want telephony-grade English voices on the same vendor, console and invoice, Aura-2 is convenient and its per-character pricing is transparent. Its limits are that it has no blind-arena quality score, a small and English-centric voice set, and no self-serve voice cloning, so it is a consolidation choice, not a quality-leadership one.
Q: How much cheaper are Deepgram TTS alternatives?
A: Deepgram Aura-2 is $0.030 per 1K characters ($30 per 1M) pay-as-you-go, and Aura-1 is $0.0150 per 1K ($15 per 1M). Against that, SpeechifyAI charges $10 per 1M on Starter down to $6 on Scale and OpenAI's tts-1 is $15 per 1M, so like-for-like savings of 2x to 5x are realistic for models that also carry a public arena quality score.
Q: Can I keep Deepgram for speech-to-text and switch only the text-to-speech?
A: Yes, and it is a common move. Deepgram's Nova speech-to-text is genuinely strong across dozens of languages, and the TTS integration surface is thin: one synthesis endpoint, a voice ID and an audio format. Swapping only Aura for a higher-quality, cheaper TTS like SpeechifyAI while keeping Deepgram for transcription is low-risk and does not touch your STT pipeline.
Q: Which Deepgram alternative has the best free tier for commercial use?
A: SpeechifyAI's free tier includes 500K TTS characters per month with commercial use allowed and a hard spending cap. Deepgram itself gives the most generous no-strings trial in this group, $200 of pay-as-you-go credit with no card, and Rime advertises 3,000 free minutes on signup. ElevenLabs' free tier does not include a commercial license.
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URL: https://speechify.ai/alternatives/elevenlabs
Title: The 6 best ElevenLabs alternatives for developers, tested July 2026
The best ElevenLabs alternative for most developers in 2026 is SpeechifyAI: Simba 3.2 ranks above Eleven v3 on Artificial Analysis' blind Speech Arena, at $10 per 1M characters, a tenth of its $100. Cartesia (lowest claimed latency), OpenAI (existing stack), Deepgram (STT plus TTS), Hume (emotional control) and Rime (on-prem CX) round out the list. We tested every one hands-on.
How we tested: I opened every platform's playground or public demo in a fresh browser session on the same day, tried to synthesize the same test passage on each, screenshotted the real sessions (including the sign-up walls where a platform would not let me in), and pulled every price from the vendor's live pricing page that afternoon. For voice quality I do not trust my own ears as a benchmark, so quality rankings come from Artificial Analysis' Speech Arena, a blind listener-preference Elo leaderboard, as it stood on the day of testing.
The alternatives, ranked:
1. SpeechifyAI — Best price-to-quality for production TTS APIs and all-in voice agents (https://speechify.ai)
2. OpenAI gpt-4o-mini-tts — Teams already on the OpenAI stack that want promptable, low-cost speech (https://developers.openai.com/api/docs/guides/text-to-speech)
3. Cartesia Sonic — Voice agents where claimed sub-90ms model latency is the deciding factor (https://www.cartesia.ai)
4. Deepgram Aura-2 — Consolidating speech-to-text and text-to-speech on one enterprise vendor (https://deepgram.com)
5. Hume Octave — Expressive, emotion-directed speech and empathic voice interfaces (https://www.hume.ai)
6. Rime — High-volume contact-center voices with on-prem and VPC deployment (https://rime.ai)
export const img = (name) => `/images/alternatives/elevenlabs/${name}.webp`;
I spent an afternoon this July doing something I recommend to anyone evaluating voice AI vendors: I opened every serious ElevenLabs competitor in a clean browser, tried to make each one say the same sentence, and wrote down what actually happened. Not what the landing pages promise. What happened.
The test passage, for the record: "Before we ship on Thursday, can you re-run the 4,096-token benchmark? Last night's build cut latency from 210 to 87 milliseconds, which honestly surprised everyone." Numbers, an abbreviation, a question, a dry aside. If a model mangles any of those, you hear it immediately.
This page is the result. It is a working document (the tested-on date above is real, and we re-verify prices when it changes), and because SpeechifyAI is on its own list, every claim here links to a source you can check without trusting us.
## Why developers leave ElevenLabs
ElevenLabs is the default name in AI voice, and it earned that. But three patterns push developers to look elsewhere, and none of them are secrets.
**The per-character math gets expensive fast.** On the [ElevenAPI pricing page](https://elevenlabs.io/pricing/api) as of July 2026, Flash/Turbo costs $0.05 per 1K characters and Multilingual v2/v3 costs $0.10 per 1K. That is $50 to $100 per 1M characters. An audiobook-length project (roughly 500K characters) costs $25 to $50 in synthesis alone, and every retake bills again: change one word in a paragraph and the whole paragraph re-renders at full price. ElevenLabs itself acknowledged the pricing pressure by [cutting API prices and introducing pay-as-you-go in May 2026](https://elevenlabs.io/blog/weve-lowered-api-agents-pricing-and-introduced-pay-as-you-go).
**Quality leadership has moved.** This is the uncomfortable one. On [Artificial Analysis' Speech Arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice), a blind listener-preference Elo leaderboard, ElevenLabs' flagship Eleven v3 scored Elo 1,174 on the day I tested, behind several models from Alibaba, Google, Cartesia and Inworld, some of which cost a fifth to a tenth as much per character.
**You cannot even try it with your own text anymore.** ElevenLabs' public text-to-speech page now requires signing in before you can synthesize a custom sentence. That is their right, but it was the only platform in this test where I could not run my test passage without creating an account first.
None of this makes ElevenLabs a bad product. It makes it a product you should compare before renewing, which is what the rest of this page is for.
## How I ranked quality
A vendor telling you their model sounds best is worthless, including when the vendor is us. So this list leans on the one public benchmark that works like a proper blind test: [Artificial Analysis' Speech Arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice), where listeners hear two unlabeled clips and pick the better one, producing an Elo score with confidence intervals.
In July 2026 the provider-voices board had Alibaba's Qwen-Audio-3.0-TTS-Plus at Elo 1,236, SpeechifyAI's Simba 3.2 at Elo 1,240, Google's Gemini 3.1 Flash TTS at Elo 1,214, Cartesia's Sonic 3.5 at Elo 1,207 and ElevenLabs' Eleven v3 at Elo 1,174.
Keep that price column in view as you read the breakdowns. The gap between what top arena voices cost and what ElevenLabs charges is the single most useful fact on this page.
## The comparison at a glance
| Platform | Model tested | Price per 1M chars (API) | Free tier | Commercial use on free tier | Public playground |
| --- | --- | --- | --- | --- | --- |
| [SpeechifyAI](#1-speechifyai) | Simba 3.2 | $10 (Starter) to $6 (Scale) | 500K chars/mo | Yes | Yes, no login |
| [OpenAI](#2-openai-gpt-4o-mini-tts) | gpt-4o-mini-tts | Token-priced (tts-1: $15) | None (pay as you go) | n/a | Yes (openai.fm), no login |
| [Cartesia](#3-cartesia-sonic) | Sonic-3.5 | $49 (per Artificial Analysis) | 20K credits (~27 min)/mo | No, Pro ($5/mo) and up | No, login required |
| [Deepgram](#4-deepgram-aura-2) | Aura-2 | $30 | $200 credit, no card | Yes (credit) | Previews only |
| [Hume](#5-hume-octave) | Octave 2 | $50 to $150 by plan | 10K chars/mo | No, Creator ($14/mo) and up | Login required |
| [Rime](#6-rime) | Coda | $50 (Starter) | 3,000 minutes | Not stated on pricing page | Canned demos only |
| ElevenLabs (baseline) | Eleven v3 / Flash v2.5 | $100 / $50 | ~10K chars/mo | No | No, login required |
Prices pulled from each vendor's live pricing page in July 2026; the linked sources at the bottom of this page are the exact pages I used. Cartesia sells credits rather than characters, so its per-character figure uses Artificial Analysis' normalization.
The fastest way to pressure-test that table is with real audio: Sign up free at https://platform.speechify.ai/signup (500K characters a month, no card) and run your own script through us and your current vendor side by side.
## 1. SpeechifyAI
Yes, our own platform is on the list, and you should treat that with exactly the suspicion it deserves. Here is the case, made entirely from things you can verify without believing a word we say.
The quality claim is not ours: Simba 3.2's Elo 1,240 on [Artificial Analysis' blind arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice) is a third-party number produced by listeners who did not know which model they were hearing. The price claim is on our [public pricing page](https://speechify.ai/pricing): $10 per 1M characters on the $10/month Starter plan, $8 on Pro, $6 on Scale. Against Eleven v3's $100 per 1M that is a 10x gap; against Flash v2.5's $50 it is still 5x, and Flash is the model ElevenLabs positions for speed, not quality.
The hands-on test was the easiest of the day, because the [speechify.ai](https://speechify.ai) homepage is itself a blind test: it plays our synthesis of a passage next to an unlabeled flagship competitor and lets you pick, no account needed.
On voices, we make a different bet than ElevenLabs. Simba 3.2 serves the full English voice roster, each voice tuned for a wide dynamic range, so the same voice carries narration, dialogue and emotional shifts that would force a voice swap elsewhere. Across the Simba family the 900+ voice catalog spans 30+ languages, and self-serve cloning from the $10 plan means the voice that matters most, your brand's own, is never on anyone else's menu. ElevenLabs' 10,000+ community library is still the biggest menu anywhere; if browsing thousands of off-the-shelf character voices is the job, that is a real reason to stay.
The free tier is the one I would point any evaluating developer at: 500K characters per month, commercial use included, with a hard cap instead of surprise overages. Sign up free at https://platform.speechify.ai/signup and run my test sentence against whatever you use today; the whole evaluation costs nothing.
**Pick SpeechifyAI if:** you want high arena quality at a tenth of ElevenLabs' flagship price, or all-in voice-agent minutes (LLM, STT, TTS and telephony orchestration in one rate, quoted per contract).
**Stay away if:** you need thousands of preset voices to pick from on the newest model generation, today.
## 2. OpenAI gpt-4o-mini-tts
OpenAI's TTS is the path of least resistance if your backend already talks to their API, and their [openai.fm](https://www.openai.fm) demo was the most fun I had all day: it is fully public, and alongside voice selection you write a free-text "vibe" prompt that steers delivery. I gave it my test passage with the Professional preset and it handled "4,096-token benchmark" cleanly.
Pricing is token-based rather than per-character, which makes like-for-like comparison annoying: [OpenAI's pricing page](https://developers.openai.com/api/docs/pricing) lists gpt-4o-mini-tts at $0.60 per 1M text input tokens plus $12.00 per 1M audio output tokens (audio output dominates the bill), with the older character-priced tts-1 at $15 per 1M characters and tts-1-hd at $30. Practical cost lands well below ElevenLabs for most workloads.
The catch is the ceiling. Eleven preset voices, no voice cloning, no per-word timestamps for caption alignment, and voice steering by prompt is expressive but not deterministic: the same vibe prompt can read differently across generations, which matters if you need take-to-take consistency. We rank the field for OpenAI's own users in the dedicated [OpenAI alternatives](/alternatives/openai) guide.
**Pick OpenAI if:** you are already on their stack and want cheap, promptable speech without another vendor contract.
**Stay away if:** you need voice cloning, brand-locked custom voices, or reproducible delivery across renders.
## 3. Cartesia Sonic
Cartesia is the latency specialist. The [Sonic page](https://www.cartesia.ai/sonic) claims sub-90ms model latency for Sonic-3.5 across 42 languages, and on [Artificial Analysis' arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice) Sonic 3.5 scores Elo 1,207, a genuinely strong showing (and at $49 per 1M characters by Artificial Analysis' normalization, half of Eleven v3's price for a higher arena score).
Hands-on, though, Cartesia was one of the platforms I could not fully test: [play.cartesia.ai](https://play.cartesia.ai) redirects straight to a GitHub/Google sign-in, and the public site only offers canned samples. Their site also still advertised "Ranked #1 in Speech Arena" on the day the live arena had them fourth, which is the kind of thing you learn to check vendors on.
Pricing is credit-based: Free gets 20K credits a month (about 27 TTS minutes) without a commercial license, Pro at $5/month adds commercial use and instant cloning, Startup at $49 covers about 1.25M credits, Scale at $299 about 8M. Their Line voice agents run $0.06 per minute plus $0.014 per minute telephony, with LLM usage currently free for UI-created agents "for a limited time," so model that bill carefully before it un-limits. If Cartesia is the platform you are weighing, our [Cartesia alternatives](/alternatives/cartesia) guide ranks the field from that side.
**Pick Cartesia if:** shaving every millisecond off agent response time is your deciding metric and a $5 entry price works.
**Stay away if:** you want to evaluate with your own text before creating an account, or you dislike credit-math billing.
## 4. Deepgram Aura-2
Deepgram is the consolidation play: if you already use them for speech-to-text (many voice-agent teams do), Aura-2 puts synthesis on the same vendor, same console, same invoice. Their [playground](https://playground.deepgram.com/?endpoint=speak) let me browse and preview the Aura-2 voice list without an account, though typing my own test passage required signing up, halfway between OpenAI's fully open demo and ElevenLabs' wall.
Pricing is refreshingly plain: [Aura-2 costs $0.030 per 1K characters](https://deepgram.com/pricing) pay-as-you-go ($30 per 1M), Aura-1 half that, and every new account gets $200 of usage credit with no credit card, the most generous no-strings trial in this test. The trade-off is scope: the voice list is a curated few dozen, primarily English with a handful of European and Japanese options in the playground, and nobody picks Aura-2 for expressive character work. It is built to sound professional on a phone line, and does. We rank the field for Deepgram's own users in the dedicated [Deepgram alternatives](/alternatives/deepgram) guide.
**Pick Deepgram if:** you want STT and TTS from one enterprise vendor with transparent per-character pricing, or you want $200 of real testing room.
**Stay away if:** you need wide language coverage or a large, characterful voice catalog.
## 5. Hume Octave
Hume comes at speech from emotion-science research, and it shows in the product shape: Octave 2 is built to be directed ("sound like a tired night-shift nurse delivering good news") rather than just voiced, and their EVI line does full speech-to-speech conversation with empathic responses. For interactive characters, companions and mental-health-adjacent products, nothing else on this list is aimed as squarely at the job.
The [pricing page](https://www.hume.ai/pricing) is plan-gated rather than flatly usage-priced: Free gives 10K characters a month, Creator at $14/month gives 140K with overage at $0.15 per 1K, and the rate falls with plan size to $0.05 per 1K on the $500 Business tier. That works out to $50 to $150 per 1M characters, so at small scale Hume costs ElevenLabs money for a different specialty, not a discount. Commercial licensing starts at Creator, and unusually, voice cloning is unlimited on every tier including Free. We rank the field for Hume's own users in the dedicated [Hume alternatives](/alternatives/hume) guide.
**Pick Hume if:** emotional direction and empathic voice interaction are the product, not a garnish.
**Stay away if:** you are optimizing cost per character for bulk narration; the math does not favor it.
## 6. Rime
Rime is the contact-center specialist, founded by linguists and pointed hard at high-stakes phone conversations in healthcare, banking and food ordering. The new flagship model, Coda, headlines 600+ voices across 50+ languages, and Rime is the only vendor on this list leading with on-prem and VPC deployment on its pricing page, which is exactly what a compliance-bound enterprise wants to read.
[Starter pricing](https://rime.ai/pricing) is $0.05 per 1K characters ($50 per 1M, the same rate as ElevenLabs Flash) with a properly generous 3,000 free minutes on signup and 20 concurrent generations. The public site only plays canned industry demos, so my test passage went unspoken here too, and note the FAQ language positions everything around CX use cases rather than narration or characters.
**Pick Rime if:** you run high-volume customer calls and need deployment control (on-prem/VPC) plus voices tuned for telephony.
**Stay away if:** you want self-serve evaluation with custom text, or creator-style expressive narration.
## Also considered, and a warning about PlayHT
Google, Microsoft Azure and Amazon Polly all sell capable TTS, and if your company already lives in one of those clouds, procurement gravity may decide for you (Google's Gemini 3.1 Flash TTS ranks third on the arena at $18.3 per 1M, a legitimately strong option). We compare them individually on our [text-to-speech comparison pages](/compare/build/text-to-speech).
MiniMax's Speech 2.8 HD ranks eighth on the arena but at $100 per 1M chars it prices like Eleven v3 without the ecosystem. Inworld's realtime models rank impressively (fifth and sixth) and are worth watching if you build games or interactive characters.
And PlayHT deserves its own paragraph. It appeared on virtually every "ElevenLabs alternatives" list ever written, including as the default recommendation for years. Meta acquired the PlayAI team in mid-2025, and when I checked in July 2026, both play.ht and play.ai failed to resolve at all. Every team that built on it has been forced off. Treat that as the permanent footnote on this category: the voice platform you pick is a dependency, so weigh the vendor's incentives to keep serving developers, not just the demo quality.
## Which alternative fits your use case
- **Bulk narration, audiobooks, content pipelines:** SpeechifyAI. High arena quality at $6 to $10 per 1M characters changes what long-form audio costs; re-renders stop hurting.
- **Real-time voice agents:** SpeechifyAI if you want one all-in per-minute rate with LLM and telephony included; Cartesia if raw model latency is your religion and you will assemble the stack yourself.
- **Already on OpenAI, shipping this week:** OpenAI's gpt-4o-mini-tts. Accept the fixed voice set and move on.
- **One vendor for STT + TTS:** Deepgram. The $200 no-card credit also makes it the cheapest platform to evaluate seriously.
- **Emotive characters and empathic interfaces:** Hume Octave, priced as a specialty, not a saving.
- **Regulated contact centers:** Rime, for the on-prem/VPC deployment story alone.
- **Staying on ElevenLabs:** defensible if the 10,000+ voice library or the dubbing/music/SFX ecosystem is load-bearing for your product. Renegotiate with the leaderboard open in another tab.
## Migrating off ElevenLabs
The practical part. TTS migrations are usually smaller than teams fear, because the integration surface is thin: one synthesis endpoint, a voice ID, and an audio format.
1. **Re-map voices first.** This is the real work. Shortlist replacement voices on the new platform and A/B them against your current output with your actual content, not the vendor's demo copy.
2. **Check your SSML and timestamps.** Tag support differs between platforms. If you rely on per-word timing (captions, avatars, karaoke-style highlighting), verify the replacement exposes speech marks before you commit. SpeechifyAI's [API docs](https://docs.speechify.ai) cover our SSML and speech-marks support.
3. **Run both in parallel for a week.** Per-character billing makes dual-running cheap insurance: mirror a slice of production traffic to the new vendor and diff failure rates, latency and listener feedback.
4. **Mind the request limits.** Free and starter tiers cap characters per request and concurrent generations differently (ElevenLabs caps requests at 40K characters; our Build API caps speech requests at 2K characters and stream requests at 20K, with concurrency rising by plan). Batch accordingly.
If you are weighing us specifically against ElevenLabs feature by feature, the [SpeechifyAI vs ElevenLabs comparison](/compare/build/text-to-speech/elevenlabs) goes deeper on the head-to-head. And the [free tier](https://speechify.ai/pricing) exists precisely so you can rerun every test on this page yourself, including the one where you do not take a vendor's word for anything: Sign up free at https://platform.speechify.ai/signup, no card, and your first 500K characters are on us.
FAQ:
Q: What is the best ElevenLabs alternative for developers in 2026?
A: For most production TTS workloads it is SpeechifyAI: on Artificial Analysis' blind Speech Arena leaderboard (July 2026), Simba 3.2 scores Elo 1,240 at $10 per 1M characters, while ElevenLabs' flagship Eleven v3 scores Elo 1,174 at $100 per 1M. If your constraint is different, Cartesia leads on claimed latency, OpenAI on stack convenience, and Rime on deployment control.
Q: Is ElevenLabs still worth using?
A: Yes, for specific jobs. Its 10,000+ community voice library is the largest anywhere, its ecosystem (dubbing, music, sound effects, voice changer) is broader than any competitor's, and Flash v2.5 at roughly 75ms is genuinely fast. If you need breadth of voices and adjacent audio products more than you need the best price per character, ElevenLabs remains a reasonable choice.
Q: How much cheaper are ElevenLabs alternatives?
A: ElevenLabs' API pricing in July 2026 was $0.05 per 1K characters for Flash/Turbo and $0.10 per 1K for Multilingual v2/v3, which is $50 to $100 per 1M characters. SpeechifyAI charges $10 per 1M on Starter down to $6 per 1M on Scale, Deepgram Aura-2 is $30 per 1M, and OpenAI's tts-1 is $15 per 1M, so like-for-like savings of 3x to 10x are realistic.
Q: What happened to PlayHT (PlayAI)?
A: PlayAI's team was acquired by Meta in mid-2025, and as of our July 2026 check both play.ht and play.ai no longer resolve at all. If you built on PlayHT you have already been forced to migrate, which is worth remembering as a platform-risk lesson when choosing any voice vendor.
Q: Which ElevenLabs alternative has the best free tier for commercial use?
A: SpeechifyAI's free tier includes 500K TTS characters per month with commercial use allowed and a hard spending cap. Deepgram gives $200 of pay-as-you-go credit with no card. Rime advertises 3,000 free minutes on signup. ElevenLabs' free tier is roughly 10K Multilingual characters per month and does not include a commercial license.
--------------------------------------------------------------------------------
URL: https://speechify.ai/alternatives/hume
Title: The 6 best Hume alternatives for developers, tested July 2026
The best Hume alternative for text-to-speech in 2026 is SpeechifyAI: Simba 3.2 ranks well above Octave on Artificial Analysis' blind Speech Arena, at $10 per 1M characters, a fraction of Octave's $50-to-$150, with emotion control and self-serve cloning. ElevenLabs (breadth), OpenAI (promptable), Cartesia (latency), Rime (telephony) and Deepgram (STT plus TTS) round out the list. We tested every one hands-on.
How we tested: I opened Hume's product and every alternative's demo in a fresh browser session on the same day, synthesized the same test passage on each where the platform allowed it, screenshotted the real sessions and the sign-in walls platforms put up before they let you synthesize custom text, and pulled every price from the vendor's live pricing page that afternoon. For voice quality I do not trust my own ears as a benchmark, so quality rankings come from Artificial Analysis' Speech Arena, a blind listener-preference Elo leaderboard, as it stood on the day of testing.
The alternatives, ranked:
1. SpeechifyAI — Best price-to-quality for production TTS and all-in voice agents, with emotion control and self-serve cloning at a fraction of Octave's price (https://speechify.ai)
2. ElevenLabs — The largest off-the-shelf community voice library plus expressive, self-serve cloning (https://elevenlabs.io)
3. OpenAI gpt-4o-mini-tts — Teams already on the OpenAI stack that want cheap, prompt-directed speech (https://developers.openai.com/api/docs/guides/text-to-speech)
4. Cartesia Sonic — Voice agents where arena-proven quality and sub-90ms model latency are the deciding factors (https://www.cartesia.ai)
5. Rime Coda — High-volume contact-center voices with on-prem and VPC deployment (https://rime.ai)
6. Deepgram Aura-2 — Consolidating speech-to-text and text-to-speech on one enterprise vendor (https://deepgram.com)
export const img = (name) => `/images/alternatives/hume/${name}.webp`;
I spent an afternoon this July doing something I recommend to anyone evaluating voice AI vendors: I opened every serious Hume competitor in a clean browser, tried to make each one say the same sentence, and wrote down what actually happened. Not what the landing pages promise. What happened.
The test passage, for the record: "Before we ship on Thursday, can you re-run the 4,096-token benchmark? Last night's build cut latency from 210 to 87 milliseconds, which honestly surprised everyone." Numbers, an abbreviation, a question, a dry aside. If a model mangles any of those, you hear it immediately.
This page is the result. It is a working document (the tested-on date above is real, and we re-verify prices when it changes), and because SpeechifyAI is on its own list, every claim here links to a source you can check without trusting us.
## Why developers leave Hume
Let me be fair to Hume first, because it is doing something genuinely distinctive. Hume comes at speech from emotion-science research, and Octave, its text-to-speech, is built to be *directed* in natural language ("sound like a tired night-shift nurse delivering good news") rather than just voiced. Its EVI line does full empathic speech-to-speech conversation. For interactive characters, companions and mental-health-adjacent products, nothing else in this comparison is aimed as squarely at the job, and voice cloning is unlimited on every tier, including Free. If emotional direction is the product, Hume earned its place on the shortlist.
Two things push developers to look elsewhere anyway.
**It is a specialty spend, not a saving.** On the [pricing page](https://www.hume.ai/pricing) Octave is plan-gated rather than flatly usage-priced: Free gives 10K characters a month, Creator gives 140K, and the overage rate falls from $0.15 per 1K on the entry plans to $0.05 per 1K on the $500 Business tier. That works out to $50 to $150 per 1M characters, so at small scale Hume costs what ElevenLabs costs, for a different specialty rather than a discount. If you are optimizing cost per character for anything high-volume, the math does not favor it.
**The company's center of gravity is moving toward evaluation, not TTS.** Hume's homepage now bills the company as "the data and evaluation layer for emotionally intelligent voice AI," leading with its voice-AI leaderboards and human-feedback research rather than the synthesis product. That is a fine thing to be, but if you are integrating a production voice you want a vendor whose main event is the voice. Octave is one product inside a research-and-evaluation company, and on raw naturalness it ranks mid-pack (more on that next).
None of this makes Octave a bad product. It makes it a specialist you should price against generalists before you build on it, which is what the rest of this page is for.
## How I ranked quality
A vendor telling you their model sounds best is worthless, including when the vendor is us. So this list leans on the one public benchmark that works like a proper blind test: [Artificial Analysis' Speech Arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice), where listeners hear two unlabeled clips and pick the better one, producing an Elo score with confidence intervals.
In July 2026 the provider-voices board had Alibaba's Qwen-Audio-3.0-TTS-Plus at Elo 1,235, SpeechifyAI's Simba 3.2 at Elo 1,240, Google's Gemini 3.1 Flash TTS at Elo 1,215 and Cartesia's Sonic 3.5 at Elo 1,208. Hume's Octave 2 sits at Elo 1,056, which is the useful context Hume's own emotion-first marketing does not give you: the emotional direction is real, but the underlying naturalness is mid-pack, not leading.
Keep that price column in view as you read the breakdowns. The gap between a leaderboard-scored voice at $10 and Octave's specialty pricing is the single most useful fact on this page.
## The comparison at a glance
| Platform | Model tested | Price per 1M chars (API) | Free tier | Arena Elo | Self-serve cloning |
| --- | --- | --- | --- | --- | --- |
| [SpeechifyAI](#1-speechifyai) | Simba 3.2 | $10 (Starter) to $6 (Scale) | 500K chars/mo | 1,240 | Yes, from $10 |
| [ElevenLabs](#2-elevenlabs) | Eleven v3 / Flash v2.5 | $100 / $50 | ~10K chars/mo | 1,175 | Yes, paid tiers |
| [OpenAI](#3-openai-gpt-4o-mini-tts) | gpt-4o-mini-tts | Token-priced (tts-1: $15) | None (pay as you go) | 1,103 (tts-1-hd) | No (sales-gated) |
| [Cartesia](#4-cartesia-sonic) | Sonic-3.5 | $49 (per Artificial Analysis) | 20K credits (~27 min)/mo | 1,208 | Yes, from $5 |
| [Rime](#5-rime-coda) | Coda | $50 (Starter) | 3,000 minutes | 1,042 | Enterprise |
| [Deepgram](#6-deepgram-aura-2) | Aura-2 | $30 | $200 credit, no card | Not ranked | No |
| Hume (baseline) | Octave 2 | $50 to $150 by plan | 10K chars/mo | 1,056 | Yes, every tier |
Prices pulled from each vendor's live pricing page in July 2026; the linked sources at the bottom of this page are the exact pages I used. Cartesia sells credits rather than characters, so its per-character figure uses Artificial Analysis' normalization.
The fastest way to pressure-test that table is with real audio: Sign up free at https://platform.speechify.ai/signup (500K characters a month, no card) and run your own script through us and Hume side by side.
## 1. SpeechifyAI
Yes, our own platform is on the list, and you should treat that with exactly the suspicion it deserves. Here is the case, made entirely from things you can verify without believing a word we say.
The quality claim is not ours: Simba 3.2's Elo 1,240 on [Artificial Analysis' blind arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice) is a third-party number produced by listeners who did not know which model they were hearing, and it sits roughly 184 Elo above Octave 2. The price claim is on our [public pricing page](https://speechify.ai/pricing): $10 per 1M characters on the $10/month Starter plan, $8 on Pro, $6 on Scale. Against Octave's $50 to $150 per 1M that is a 5x to 15x gap, for a higher arena score.
The hands-on test was the easiest of the day, because the [speechify.ai](https://speechify.ai) homepage is itself a blind test: it plays our synthesis of a passage next to an unlabeled flagship competitor and lets you pick, no account needed.
Where SpeechifyAI most directly answers a Hume user is on expressiveness without the specialty price. Simba 3.2 offers emotion control and SSML, so the same voice carries narration, dialogue and emotional shifts, and it serves the full English voice roster, with the wider Simba catalog spanning 900+ voices across 30+ languages. Self-serve cloning from the $10 plan means your brand's own voice is on the menu, and if you are building conversational products, all-in voice agents bundle LLM, speech-to-text, text-to-speech and telephony from $0.07 per minute rather than assembling Hume's EVI stack yourself.
The free tier is the one I would point any evaluating developer at: 500K characters per month, commercial use included, with a hard cap instead of surprise overages. Sign up free at https://platform.speechify.ai/signup and run my test sentence against Octave today; the whole evaluation costs nothing.
**Pick SpeechifyAI if:** you want top arena quality with emotion control and self-serve cloning, at a fifth to a fifteenth of Octave's price, or all-in voice agents.
**Stay away if:** natural-language emotional direction ("act sarcastic, then relieved") and empathic speech-to-speech are literally the product, in which case Hume's specialty is the point.
## 2. ElevenLabs
If what you valued in Hume was expressive range and voice variety, ElevenLabs is the broadest counter on the market: a 10,000+ community voice library, self-serve instant and professional cloning, and an ecosystem (dubbing, music, sound effects) nobody else matches. On the arena, Eleven v3 ranks eleventh (Elo 1,175), above Octave 2, so you also move up on raw naturalness.
The catch is cost. The [pricing page](https://elevenlabs.io/pricing/api) lists Flash/Turbo at $0.05 per 1K characters and Multilingual v2/v3 at $0.10 per 1K, which is $50 to $100 per 1M characters, in the same band as Hume rather than below it. And its public TTS page requires an account before you can synthesize custom text. If you are leaving Hume for voice variety specifically, our [ElevenLabs alternatives](/alternatives/elevenlabs) guide ranks the field from that angle.
**Pick ElevenLabs if:** browsing thousands of character voices and a broad audio ecosystem is the point.
**Stay away if:** you are optimizing cost per character, or arena-evaluated quality is your priority over voice variety.
## 3. OpenAI gpt-4o-mini-tts
OpenAI's delivery model is conceptually the closest thing to Octave's: alongside voice selection on the fully public [openai.fm](https://www.openai.fm) demo, you write a free-text "vibe" prompt that steers tone and emotion, much like directing Octave. I gave it my test passage with the Marin voice and a Sincere vibe, and it handled "4,096-token benchmark" cleanly, no account required.
Pricing is token-based: [OpenAI's pricing page](https://developers.openai.com/api/docs/pricing) lists gpt-4o-mini-tts at $0.60 per 1M text input tokens plus $12.00 per 1M audio output tokens, with the older character-priced tts-1 at $15 per 1M characters and tts-1-hd at $30. That is well below Octave. The ceilings are eleven preset voices, no self-serve cloning, and prompt-based delivery that is expressive but not deterministic. If OpenAI is the platform you are actually weighing, our [OpenAI alternatives](/alternatives/openai) guide ranks the same field for its users.
**Pick OpenAI if:** you are already on their stack and want cheap, prompt-directed speech.
**Stay away if:** you need voice cloning, brand-locked custom voices, or arena-grade quality.
## 4. Cartesia Sonic
If your Hume use case was really a real-time voice agent that happened to want expressive output, Cartesia is the quality-and-latency specialist to weigh. The [Sonic page](https://www.cartesia.ai/sonic) claims sub-90ms model latency, and on the arena Sonic 3.5 scores Elo 1,208, well above Octave.
The trade-offs are credit-based pricing (Artificial Analysis normalizes Sonic 3.5 to about $49 per 1M) and a playground gated behind sign-in. It is less about emotional direction than raw quality and speed, so it fits the agent half of Hume's audience more than the character half. Our [Cartesia alternatives](/alternatives/cartesia) guide covers it in depth.
**Pick Cartesia if:** arena-proven quality and sub-90ms latency for voice agents are the deciding metrics.
**Stay away if:** natural-language emotional direction is what you need, or you dislike credit-math billing.
## 5. Rime Coda
Rime is the contact-center specialist, pointed at high-volume phone conversations in healthcare, banking and food ordering. Its flagship Coda headlines 600+ voices across 50+ languages, and Rime leads with on-prem and VPC deployment, which matters if your empathic use case is also a regulated one.
[Starter pricing](https://rime.ai/pricing) is $0.05 per 1K characters ($50 per 1M) with 3,000 free minutes on signup. On the arena Coda ranks mid-pack (Elo 1,042), so the reason to choose it over Octave is deployment control and telephony fit rather than expressive range.
**Pick Rime if:** you run regulated, high-volume contact centers and need deployment control.
**Stay away if:** natural-language emotional direction or arena-evaluated quality is the requirement.
## 6. Deepgram Aura-2
Deepgram is the consolidation play: if you already use its world-class Nova speech-to-text, Aura-2 puts synthesis on the same vendor, console and invoice. Its [playground](https://playground.deepgram.com/?endpoint=speak) previews the Aura-2 voice list publicly, though custom text needs a free sign-up, and every account gets $200 of no-card credit.
[Aura-2 is $0.030 per 1K characters](https://deepgram.com/pricing) ($30 per 1M), below Octave, but it is the opposite of Hume in temperament: a curated, English-centric set built to sound professional on a phone line, with no self-serve cloning and no blind-arena score. If Deepgram is the platform you are weighing, our [Deepgram alternatives](/alternatives/deepgram) guide ranks the field from that side.
**Pick Deepgram if:** you want speech-to-text and text-to-speech from one enterprise vendor with transparent pricing.
**Stay away if:** emotional expressiveness, a large voice catalog, or a public quality score is what you need.
## Also considered, and a warning about PlayHT
Google, Microsoft Azure and Amazon Polly all sell capable TTS, and if your company already lives in one of those clouds, procurement gravity may decide for you (Google's Gemini 3.1 Flash TTS ranks third on the arena at $18.3 per 1M, a legitimately strong option). We compare them individually on our [text-to-speech comparison pages](/compare/build/text-to-speech).
MiniMax's Speech 2.8 HD ranks well on the arena but at $100 per 1M chars it prices like the premium tier without the ecosystem. Inworld's realtime models rank impressively and are worth watching if you build games or interactive characters, which overlaps with Hume's own audience.
And PlayHT deserves its own paragraph. It appeared on virtually every "voice AI alternatives" list ever written, often as the default recommendation. Meta acquired the PlayAI team in mid-2025, and when I checked in July 2026, both play.ht and play.ai failed to resolve at all. Every team that built on it has been forced off. Treat that as the permanent footnote on this category: the voice platform you pick is a dependency, so weigh the vendor's incentives to keep serving developers, not just the demo quality.
## Which alternative fits your use case
- **Expressive product voice without the specialty price:** SpeechifyAI. Top arena quality with emotion control and self-serve cloning at a fifth to a fifteenth of Octave's cost.
- **Voice variety and a broad audio ecosystem:** ElevenLabs, if the 10,000+ voice library is the point and you can absorb the per-character cost.
- **Prompt-directed delivery on the cheap:** OpenAI's gpt-4o-mini-tts, whose "vibe" prompt is the closest thing to Octave's direction model.
- **Real-time voice agents:** SpeechifyAI for one all-in per-minute rate; Cartesia if arena-proven latency is the single metric you will benchmark first.
- **Regulated, high-volume contact centers:** Rime, for the on-prem/VPC deployment story.
- **One vendor for STT + TTS:** Deepgram, with $200 of no-card credit to evaluate.
- **Staying on Hume:** the right call if natural-language emotional direction and empathic speech-to-speech are the product itself, and unlimited cloning on every tier is worth the specialty price.
## Migrating off Hume
The practical part. TTS migrations are usually smaller than teams fear, because the integration surface is thin: one synthesis endpoint, a voice ID, and an audio format.
1. **Separate "emotional direction" from "a good voice."** Be honest about which you actually use. If you lean on Octave's natural-language direction heavily, test the alternative's expressive controls (SpeechifyAI's emotion and SSML, OpenAI's vibe prompt) with your real scripts before switching. If you were mostly using Octave as a nice voice, almost anything here is an upgrade on price.
2. **Re-map voices and re-clone.** Shortlist replacements and A/B them against your current Octave output with your actual content. Cloning is self-serve on SpeechifyAI, Cartesia and ElevenLabs if you need your existing brand voice.
3. **Run both in parallel for a week.** Per-character billing makes dual-running cheap insurance: mirror a slice of production traffic and diff quality, latency and listener feedback.
4. **Check SSML and timestamps.** If you rely on tag-level control or per-word timing for captions and turn-taking, verify the replacement exposes them. SpeechifyAI's [API docs](https://docs.speechify.ai) cover SSML and speech-marks support.
If you are weighing us specifically against Hume feature by feature, the [SpeechifyAI vs Hume comparison](/compare/build/text-to-speech/hume) goes deeper on the head-to-head. And the [free tier](https://speechify.ai/pricing) exists precisely so you can rerun every test on this page yourself, including the one where you do not take a vendor's word for anything: Sign up free at https://platform.speechify.ai/signup, no card, and your first 500K characters are on us.
FAQ:
Q: What is the best Hume alternative for text-to-speech in 2026?
A: For most production TTS workloads it is SpeechifyAI: on Artificial Analysis' blind Speech Arena leaderboard (July 2026), Simba 3.2 scores Elo 1,240 at $10 per 1M characters, while Hume's Octave 2 sits mid-pack (Elo 1,056) and costs $50 to $150 per 1M depending on plan. SpeechifyAI also offers emotion control and self-serve voice cloning, so you keep the expressive direction that drew you to Hume without the specialty price.
Q: Is Hume Octave still worth using?
A: Yes, for one thing in particular: emotional direction. Octave is built to be steered in natural language ('sound like a tired night-shift nurse delivering good news') rather than just voiced, and Hume's EVI line does full empathic speech-to-speech conversation. For interactive characters, companions and mental-health-adjacent products, nothing else on this list is aimed as squarely at the job. Voice cloning is also unlimited on every tier, including Free. It is a specialty tool, priced like one.
Q: How much cheaper are Hume alternatives?
A: Hume's Octave TTS is plan-gated: overage runs $0.15 per 1K characters on the entry plans down to $0.05 per 1K on the $500 Business tier, which works out to $50 to $150 per 1M. Against that, SpeechifyAI charges $10 per 1M on Starter down to $6 on Scale, OpenAI's tts-1 is $15 per 1M, and Deepgram Aura-2 is $30, so savings of 2x to 15x are realistic depending on Hume tier.
Q: Which Hume alternative also supports emotional or expressive delivery?
A: Several. SpeechifyAI offers emotion control and SSML, ElevenLabs offers a wide expressive range, and OpenAI steers delivery with a free-text 'vibe' instruction prompt much like Octave's direction model. The difference is price and, for SpeechifyAI specifically, a strong arena Elo underneath the expressiveness rather than Octave's mid-pack Elo.
Q: Does Hume or its alternatives have the most generous voice cloning?
A: Hume is genuinely the most generous on cloning policy: it is unlimited on every tier including the Free plan. Among the alternatives, SpeechifyAI offers self-serve cloning from the $10 Starter plan, Cartesia from its $5 Pro plan, and ElevenLabs on paid tiers. If unlimited cloning at zero cost is the single deciding feature, Hume's Free tier is hard to beat, though it caps you at 10K characters a month.
--------------------------------------------------------------------------------
URL: https://speechify.ai/alternatives/openai
Title: The 6 best OpenAI TTS alternatives for developers, tested July 2026
The best OpenAI TTS alternative for most developers in 2026 is SpeechifyAI: Simba 3.2 ranks well above OpenAI's top voice, tts-1-hd, on Artificial Analysis' blind Speech Arena, at $10 per 1M characters against $30. ElevenLabs (voice breadth and self-serve cloning), Cartesia (latency), Deepgram (STT plus TTS), Hume (emotional control) and Rime (on-prem CX) complete the list.
How we tested: I ran every platform on this list through the same protocol as our ElevenLabs round earlier in July 2026: open the playground or public demo in a fresh browser session, synthesize the same test passage, screenshot the real session, and pull every price from the vendor's live pricing page. On the day this page went live I re-verified every one of those prices and re-pulled the Artificial Analysis Speech Arena standings; every number below is from that same-day check. Quality rankings come from that blind listener-preference Elo leaderboard, not from my ears or our marketing.
The alternatives, ranked:
1. SpeechifyAI — Best price-to-quality for production TTS APIs and all-in voice agents (https://speechify.ai)
2. ElevenLabs — The largest voice library anywhere plus self-serve voice cloning (https://elevenlabs.io)
3. Cartesia Sonic — Voice agents where claimed sub-90ms model latency is the deciding factor (https://www.cartesia.ai)
4. Deepgram Aura-2 — Consolidating speech-to-text and text-to-speech on one enterprise vendor (https://deepgram.com)
5. Hume Octave — Expressive, emotion-directed speech and empathic voice interfaces (https://www.hume.ai)
6. Rime — High-volume contact-center voices with on-prem and VPC deployment (https://rime.ai)
export const img = (name) => `/images/alternatives/openai/${name}.webp`;
OpenAI's text-to-speech is the API a lot of teams end up on without ever choosing it. The key is already in the environment variables, the SDK is already in the lockfile, and `gpt-4o-mini-tts` is one endpoint away. That convenience is real, and for plenty of products it is enough.
This page is for the moment it stops being enough. I put OpenAI's TTS and six competitors through the same hands-on protocol we used for our [ElevenLabs alternatives round](/alternatives/elevenlabs) this July: same fresh browser, same test passage ("Before we ship on Thursday, can you re-run the 4,096-token benchmark? Last night's build cut latency from 210 to 87 milliseconds, which honestly surprised everyone."), every price pulled from the vendor's live pricing page, and every number re-verified the day this page went live. Because SpeechifyAI is on its own list, every claim links to a source you can check without trusting us.
## Why developers leave OpenAI TTS
None of these are secrets; all of them are in OpenAI's own documentation.
**The request cap is small.** The [gpt-4o-mini-tts model page](https://developers.openai.com/api/docs/models/gpt-4o-mini-tts) states the maximum number of input tokens is 2,000. For long-form audio (articles, narration, course content) that means chunking every job, stitching the audio, and managing prosody across the seams yourself. Character-priced TTS vendors commonly accept an order of magnitude more per request.
**Token pricing makes audio costs hard to forecast.** The same model page lists $0.60 per 1M text input tokens plus $12.00 per 1M audio output tokens, and audio output dominates the bill. How many audio tokens a passage produces depends on the audio, not the text, so you find out the real unit cost after you have shipped. The legacy per-character models are predictable (tts-1 at $15 per 1M characters, tts-1-hd at $30) but they are two generations old.
**Voices are fixed unless sales says otherwise.** The API ships 11 built-in voices. OpenAI now offers custom voices, but the [TTS guide](https://developers.openai.com/api/docs/guides/text-to-speech) is explicit that they are "limited to eligible customers" via the sales team, with consent and sample recordings. If you are an indie developer or a small team wanting a brand voice, that door is not self-serve.
**Steering is a prompt, not a spec.** There is no SSML and there are no per-word timestamps. Delivery is controlled by a free-text `instructions` prompt (accent, emotional range, intonation, impressions, speed), which is genuinely expressive and genuinely non-deterministic: the same prompt can read differently across takes, which matters for retakes, captions and anything that must sound identical twice.
**And the quality story has a number now.** On [Artificial Analysis' blind Speech Arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice), OpenAI's highest-scoring entry in July 2026 is tts-1-hd at Elo 1,102. gpt-4o-mini-tts does not appear on the board at all, and the realtime voice model runs about $191.6 per 1M characters by Artificial Analysis' normalization.
To be fair before moving on: the [openai.fm](https://www.openai.fm) demo remains one of the most open playgrounds in the industry (no login, custom text, free-text vibe prompts), and it handled my test passage cleanly in this round of testing. OpenAI TTS is not a bad product. It is a convenient default with a low ceiling, and the rest of this page is about what is above that ceiling.
## How I ranked quality
A vendor telling you their model sounds best is worthless, including when the vendor is us. So this list leans on [Artificial Analysis' Speech Arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice), a blind listener-preference test: two unlabeled clips, listeners pick the better one, and the results produce Elo scores with confidence intervals.
On the July 2026 board, re-checked the day this page published: Alibaba's Qwen-Audio-3.0-TTS-Plus at Elo 1,239, SpeechifyAI's Simba 3.2 at Elo 1,240, Google's Gemini 3.1 Flash TTS at Elo 1,213, Cartesia's Sonic 3.5 at Elo 1,209 and ElevenLabs' Eleven v3 at Elo 1,170. OpenAI's best entry sits at Elo 1,102.
One honest gap in the method: Deepgram's Aura-2 is not on the arena board at all, so for Deepgram you get my hands-on impressions and their pricing, not a blind-test number.
## The comparison at a glance
| Platform | Model tested | Price per 1M chars (API) | Free tier | Commercial use on free tier | Public playground |
| --- | --- | --- | --- | --- | --- |
| [SpeechifyAI](#1-speechifyai) | Simba 3.2 | $10 (Starter) to $6 (Scale) | 500K chars/mo | Yes | Yes, no login |
| [ElevenLabs](#2-elevenlabs) | Eleven v3 / Flash v2.5 | $100 / $50 | ~10K chars/mo | No | No, login required |
| [Cartesia](#3-cartesia-sonic) | Sonic-3.5 | $49 (per Artificial Analysis) | 20K credits (~27 min)/mo | No, Pro ($5/mo) and up | No, login required |
| [Deepgram](#4-deepgram-aura-2) | Aura-2 | $30 | $200 credit, no card | Yes (credit) | Previews only |
| [Hume](#5-hume-octave) | Octave 2 | $50 to $150 by plan | 10K chars/mo | No, Creator ($14/mo) and up | Login required |
| [Rime](#6-rime) | Coda | $50 (Starter) | 3,000 minutes | Not stated on pricing page | Canned demos only |
| OpenAI (baseline) | gpt-4o-mini-tts | Token-priced ($0.60 in / $12 audio out per 1M tokens); tts-1: $15 | None (pay as you go) | n/a | Yes (openai.fm), no login |
Prices pulled from each vendor's live pricing page in July 2026 and re-checked the day this page went live; the sources at the bottom are the exact pages I used. Cartesia sells credits rather than characters, so its per-character figure uses Artificial Analysis' normalization.
The fastest way to pressure-test that table is with real audio: Sign up free at https://platform.speechify.ai/signup (500K characters a month, no card) and run your own script through us and OpenAI side by side.
## 1. SpeechifyAI
Yes, our own platform is on the list, and you should treat that with exactly the suspicion it deserves. Here is the case, made entirely from things you can verify without believing a word we say.
The quality claim is not ours: Simba 3.2's Elo 1,240 on [Artificial Analysis' blind arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice) comes from listeners who did not know which model they were hearing. OpenAI's best entry on the same board sits 138 Elo points back. The price claim is on our [public pricing page](https://speechify.ai/pricing): $10 per 1M characters on the $10/month Starter plan, $8 on Pro, $6 on Scale, per-character rates you can put in a spreadsheet before you ship, next to a per-request cap that is documented rather than discovered.
The hands-on test was the easiest of the round, because the [speechify.ai](https://speechify.ai) homepage is itself a blind test: it plays our synthesis of a passage next to an unlabeled flagship competitor and lets you pick, no account needed.
On voices, we make a different bet than a menu. Simba 3.2 serves the full English voice roster, each voice tuned for a wide dynamic range, so the same voice carries narration, dialogue and emotional shifts that would force a voice swap elsewhere, and where OpenAI steers with a prompt and hopes, you get SSML-level control that renders the same way every time. Across the Simba family the 900+ voice catalog spans 30+ languages, and self-serve cloning from the $10 plan means the voice that matters most, your brand's own, is never on anyone else's menu. If what you actually want is thousands of community voices to browse, ElevenLabs (next on this list) is the honest answer.
The free tier is the one I would point any evaluating developer at, particularly since OpenAI offers none for TTS: 500K characters per month, commercial use included, with a hard cap instead of surprise overages. Sign up free at https://platform.speechify.ai/signup and run my test sentence against your current gpt-4o-mini-tts output; the whole evaluation costs nothing.
**Pick SpeechifyAI if:** you want high arena quality at forecastable per-character prices, self-serve voice cloning from the $10 plan, or all-in voice-agent minutes (LLM, STT, TTS and telephony orchestration in one rate, quoted per contract).
**Stay away if:** you need thousands of preset voices to pick from on the newest model generation, today.
## 2. ElevenLabs
If what pushed you off OpenAI is the fixed voice menu and the sales-gated cloning, ElevenLabs is the strongest counter-programming in the industry: a 10,000+ community voice library, self-serve instant and professional voice cloning, and an ecosystem (dubbing, music, sound effects, voice changer) nobody else on this list matches. On the arena, Eleven v3 scores Elo 1,170.
You pay for all of that in the most literal way. The [ElevenAPI pricing page](https://elevenlabs.io/pricing/api) lists Flash/Turbo at $0.05 per 1K characters (about 75ms latency) and Multilingual v2/v3 at $0.10 per 1K, which is $50 to $100 per 1M characters, and subscription tiers stack on top (Creator $22, Pro $99, Scale $299, Business $990 monthly). Coming from OpenAI's pricing this is a step up in cost, not down; you are buying breadth and cloning, not savings.
Two testing notes. First, ElevenLabs' public TTS page would not synthesize my custom passage without an account, so unlike openai.fm you cannot kick the tires anonymously. Second, requests cap at 40K characters, twenty times OpenAI's 2,000-token ceiling, which is exactly the kind of spec that decides long-form pipelines. We ran a [full alternatives round on ElevenLabs itself](/alternatives/elevenlabs) if it is the vendor you are actually deciding between.
**Pick ElevenLabs if:** voice variety and self-serve cloning are why you are leaving OpenAI, and cost per character is not your binding constraint.
**Stay away if:** you were hoping an OpenAI alternative would also be cheaper; this one is not.
## 3. Cartesia Sonic
Cartesia is the latency specialist. The [Sonic page](https://www.cartesia.ai/sonic) claims sub-90ms model latency for Sonic-3.5, and on [Artificial Analysis' arena](https://artificialanalysis.ai/text-to-speech/leaderboard/provider-voice) Sonic 3.5 scores Elo 1,209, more than a hundred Elo above OpenAI's best. If you are building realtime voice agents and found OpenAI's realtime pricing hard to swallow ($191.6 per 1M characters by Artificial Analysis' normalization), this is the specialist alternative.
Hands-on, Cartesia was one of the platforms I could not fully test: [play.cartesia.ai](https://play.cartesia.ai) redirects straight to a GitHub/Google sign-in, and the public site only offers canned samples. Their site also still advertised "Ranked #1 in Speech Arena" while the live arena had them fourth, which is the kind of thing you learn to check vendors on.
Pricing is credit-based: Free gets 20K credits a month (about 27 TTS minutes) without a commercial license, Pro at $5/month adds commercial use and instant voice cloning (note: self-serve cloning for five dollars, versus a sales conversation at OpenAI), Startup at $49 covers about 1.25M credits, Scale at $299 about 8M. If Cartesia is the platform you are actually deciding on, our [Cartesia alternatives](/alternatives/cartesia) guide ranks the field from that side.
**Pick Cartesia if:** shaving every millisecond off agent response time is your deciding metric and a $5 entry price works.
**Stay away if:** you want to evaluate with your own text before creating an account, or you dislike credit-math billing.
## 4. Deepgram Aura-2
Deepgram is the consolidation play: if you already use them for speech-to-text (many voice-agent teams do), Aura-2 puts synthesis on the same vendor, same console, same invoice. Their [playground](https://playground.deepgram.com/?endpoint=speak) let me browse and preview the Aura-2 voice list without an account, though typing my own test passage required signing up, halfway between openai.fm's fully open demo and ElevenLabs' wall.
Pricing is refreshingly plain, and for anyone tired of estimating audio tokens it reads like relief: [Aura-2 costs $0.030 per 1K characters](https://deepgram.com/pricing) pay-as-you-go ($30 per 1M, the same rate as OpenAI's legacy tts-1-hd), and every new account gets $200 of usage credit with no credit card, the most generous no-strings trial in this test. The trade-off is scope: a curated few dozen voices, primarily English, built to sound professional on a phone line rather than expressive in a story. And as noted above, Aura-2 has no blind-arena ranking to point at. If Deepgram is the platform you are actually deciding on, our [Deepgram alternatives](/alternatives/deepgram) guide ranks the field from that side.
**Pick Deepgram if:** you want STT and TTS from one enterprise vendor with transparent per-character pricing, or $200 of real testing room.
**Stay away if:** you need wide language coverage, a large voice catalog, or third-party quality evidence.
## 5. Hume Octave
Hume comes at speech from emotion-science research. Octave 2 is built to be directed ("sound like a tired night-shift nurse delivering good news") rather than just voiced, which sounds like OpenAI's instructions prompt until you use both: Hume's whole product, including its EVI speech-to-speech line, is organized around that direction, not offering it as a bolt-on parameter.
The [pricing page](https://www.hume.ai/pricing) is plan-gated: Free gives 10K characters a month, Creator at $14/month gives 140K with overage at $0.15 per 1K, falling to $0.05 per 1K on the $500 Business tier. That works out to $50 to $150 per 1M characters, so Hume costs more than OpenAI for a different specialty, not less for the same one. Unusually, voice cloning is available on every tier including Free. If Hume is the platform you are actually deciding on, our [Hume alternatives](/alternatives/hume) guide ranks the field from that side.
**Pick Hume if:** emotional direction and empathic voice interaction are the product, not a garnish.
**Stay away if:** you are optimizing cost per character for bulk narration; the math does not favor it.
## 6. Rime
Rime is the contact-center specialist, founded by linguists and pointed hard at high-stakes phone conversations in healthcare, banking and food ordering. The flagship model, Coda, headlines 600+ voices across 50+ languages, and Rime is the only vendor on this list leading with on-prem and VPC deployment on its pricing page. OpenAI does not offer anything comparable; if your compliance team requires the model inside your network, this is the shortlist.
[Starter pricing](https://rime.ai/pricing) is $0.05 per 1K characters ($50 per 1M) with a properly generous 3,000 free minutes on signup and 20 concurrent generations. The public site only plays canned industry demos, so my test passage went unspoken here, and the positioning is squarely CX rather than narration or characters.
**Pick Rime if:** you run high-volume customer calls and need deployment control (on-prem/VPC) plus voices tuned for telephony.
**Stay away if:** you want self-serve evaluation with custom text, or creator-style expressive narration.
## Also considered, and the PlayHT warning
Google, Microsoft Azure and Amazon Polly all sell capable TTS, and if your company already lives in one of those clouds, procurement gravity may decide for you; Google's Gemini 3.1 Flash TTS ranks third on the arena at $18.3 per 1M and is the strongest of the cloud-default options. We compare them individually on our [text-to-speech comparison pages](/compare/build/text-to-speech).
And the standing warning for this category: PlayHT appeared on virtually every TTS alternatives list ever written until Meta acquired the PlayAI team in mid-2025, and when we checked this July, both play.ht and play.ai no longer resolve at all. Every team that built on it has been forced off. The voice platform you pick is a dependency; weigh the vendor's incentive to keep serving developers, not just the demo quality.
## Which alternative fits your use case
- **Bulk narration, audiobooks, content pipelines:** SpeechifyAI. High arena quality, per-character pricing you can forecast, and no 2,000-token chunking dance.
- **Voice variety and brand voices, self-serve:** ElevenLabs, with SpeechifyAI as the value option (cloning from the $10 plan).
- **Real-time voice agents:** SpeechifyAI for one all-in per-minute rate with LLM and telephony included; Cartesia if raw model latency is your religion and you will assemble the stack yourself.
- **One vendor for STT + TTS:** Deepgram. The $200 no-card credit also makes it the cheapest platform to evaluate seriously.
- **Emotive characters and empathic interfaces:** Hume Octave, priced as a specialty, not a saving.
- **Regulated contact centers:** Rime, for the on-prem/VPC deployment story alone.
- **Staying on OpenAI:** defensible if your TTS needs are simple, your volumes are modest, and one fewer vendor genuinely matters. Re-check the math the first time you chunk a long document or ask sales about a custom voice.
## Migrating off OpenAI TTS
TTS migrations are usually smaller than teams fear, because the integration surface is thin: one synthesis endpoint, a voice name, an audio format. Leaving OpenAI specifically:
1. **Re-map the 11 voices first.** Shortlist replacements on the new platform and A/B them against your current output with your actual content. If you steered delivery with `instructions` prompts, capture those prompts; on SSML-capable platforms their intent usually translates into explicit tags, which then render the same way every time.
2. **Rebuild your cost model in characters.** Token-based audio billing does not map one-to-one onto per-character pricing. Take one month of real OpenAI TTS usage, count the input characters, and price that volume on the alternative's rate card; it is usually a five-minute spreadsheet that settles the decision.
3. **Check timestamps and SSML before you commit.** OpenAI gives you neither; if captions or word-level alignment are on your roadmap, verify the replacement exposes speech marks. SpeechifyAI's [API docs](https://docs.speechify.ai) cover our SSML and speech-marks support.
4. **Run both in parallel for a week.** Mirror a slice of production traffic to the new vendor and diff failure rates, latency and listener feedback. Watch request limits while you do: our Build API caps speech requests at 2K characters and stream requests at 20K, ElevenLabs at 40K, and concurrency ceilings differ by plan everywhere.
If you are weighing us specifically against OpenAI feature by feature, the [SpeechifyAI vs OpenAI comparison](/compare/build/text-to-speech/openai) goes deeper on the head-to-head. And the [free tier](https://speechify.ai/pricing) exists precisely so you can rerun every test on this page yourself: Sign up free at https://platform.speechify.ai/signup, no card, and your first 500K characters are on us.
FAQ:
Q: What is the best OpenAI TTS alternative for developers in 2026?
A: For most production TTS workloads it is SpeechifyAI: on Artificial Analysis' blind Speech Arena leaderboard (July 2026), Simba 3.2 scores Elo 1,240 at $10 per 1M characters. OpenAI's highest-scoring voice on the same board is the legacy tts-1-hd at Elo 1,102 ($30 per 1M), and gpt-4o-mini-tts is not ranked at all. If your constraint is different, ElevenLabs leads on voice breadth and self-serve cloning, Cartesia on claimed latency.
Q: How is OpenAI TTS priced, and what does it actually cost?
A: gpt-4o-mini-tts is token-priced: $0.60 per 1M text input tokens plus $12.00 per 1M audio output tokens as of July 2026, and the audio output side dominates the bill. The legacy models are per-character: tts-1 at $15 per 1M characters and tts-1-hd at $30. Character-priced alternatives are easier to forecast: SpeechifyAI runs $10 per 1M on Starter down to $6 on Scale, and Deepgram Aura-2 is $30 per 1M.
Q: Does OpenAI TTS support voice cloning?
A: Not self-serve. OpenAI added custom voices to its Audio API, but the docs state they are limited to eligible customers and require contacting the sales team, with consent and sample recordings. If you want cloning you can set up yourself today, ElevenLabs, Cartesia (from the $5 Pro plan), Hume (every tier) and SpeechifyAI (from the $10 Starter plan) all offer it self-serve.
Q: Does OpenAI TTS support SSML?
A: No. Delivery is steered with a free-text instructions prompt covering accent, emotional range, intonation, impressions and speed. That is expressive but not deterministic: the same prompt can render differently across generations, and there are no SSML tags or per-word timestamps for caption alignment. If you need tag-level control or speech marks, verify support on the alternative before migrating; SpeechifyAI's API documents both.
Q: Which OpenAI TTS alternative has the best free tier for commercial use?
A: SpeechifyAI's free tier includes 500K TTS characters per month with commercial use allowed and a hard spending cap. Deepgram gives $200 of pay-as-you-go credit with no card required. Rime advertises 3,000 free minutes on signup. OpenAI's TTS has no free tier at all; every character is billed pay-as-you-go from the first request.
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URL: https://speechify.ai/blog/add-a-better-voice-to-deepgram-voice-agent-with-speechify
Title: Add a better voice to Deepgram's Voice Agent with Speechify
Point Deepgram Voice Agent at the open-source tts-shims OpenAI-compatible proxy to speak with a Speechify voice. The shim answers Deepgram's open_ai TTS request and keeps your Speechify key server-side.
import SignupLink from "@/components/SignupLink.astro";
import DocsLink from "@/components/DocsLink.astro";
import DeepgramShimKeyFlow from "@/components/blog/diagrams/DeepgramShimKeyFlow.astro";
> **Update, 10 September 2026:** `simba-3.2` now serves every English voice in the catalogue, cloned voices included — the earlier curated voice set is gone. Any English voice whose `models` array lists `simba-3.2` in `GET /v1/voices` works here. It stays English-only; use `simba-3.0` for other languages.
You give Deepgram Voice Agent a Speechify voice by running the OpenAI-compatible binary from [`tts-shims`](https://github.com/Speechify-AI/tts-shims) and setting Deepgram's TTS provider to `open_ai` with the `endpoint.url` pointed at that shim. Deepgram already knows how to talk to a bring-your-own OpenAI TTS endpoint, so it sends a normal `POST /v1/audio/speech` request, and the shim answers it with audio from Speechify while your key stays on the server. The important bit is that this uses the `tts-shims` `openai` binary, not the `deepgram` binary.
The finished demo is in [`speechify-ai-demos/deepgram-voice-agent-shim`](https://github.com/Speechify-AI/speechify-ai-demos/tree/main/deepgram-voice-agent-shim). You'll need a synth-capable Speechify key to run the smoke test. Get one here (https://platform.speechify.ai/signup) if you do not have one yet.
## Why not put the Speechify key in Deepgram's settings?
Deepgram's custom TTS config needs a credential it can send to whatever endpoint it calls. That `Settings` message is agent configuration, not your server environment, so a real Speechify key in `endpoint.headers.authorization` becomes part of the agent setup and travels wherever Deepgram sends it. That is the problem the shim exists to solve.
The shim makes the credential disposable. Deepgram sends a placeholder Bearer token, the shim reads `SPEECHIFY_API_KEY` from its own environment and calls Speechify with that, and the token Deepgram sent is discarded. It is the same server-side-key pattern as the [voice cloning web app](/blog/building-an-ai-voice-cloning-web-app-with-nextjs-and-speechify), packaged as a small Go proxy rather than a Next.js route handler.
## How does Deepgram Voice Agent call a third-party TTS?
Deepgram Voice Agent supports bring-your-own TTS through the `agent.speak` block of its `Settings` message. For a third party you set `provider.type` to the provider dialect and give an `endpoint` with a `url` and `headers`. The supported third-party types are `open_ai`, `eleven_labs`, `cartesia`, and `aws_polly`. There is no "custom Deepgram-dialect endpoint" option: `provider.type: "deepgram"` means Deepgram's own hosted TTS, and it takes no `endpoint` override at all.
The one that fits Speechify is `open_ai`. When you use it, Deepgram sends a request in OpenAI's text-to-speech shape to your `endpoint.url`:
```json
{ "model": "tts-1", "input": "The text the agent wants to say.", "voice": "alloy" }
```
That is exactly the request the `openai` shim answers. So the integration has three moving parts: run the OpenAI-compatible shim, point Deepgram's `open_ai` endpoint at it, and let the shim translate the speak request to Speechify.
## Build and run the shim
Clone the shim repo and build the OpenAI binary. Each provider is a separate binary under `cmd/`, so you build only the one you need:
```bash
git clone https://github.com/Speechify-AI/tts-shims
cd tts-shims
make openai
```
The build is plain Go with no dependencies. In the verified run for this post, `go version` reported `go1.26.3 darwin/arm64` and `make openai` produced `./bin/openai`. Start it on a local port:
```bash
export SPEECHIFY_API_KEY=sk_your_key_here
export SHIM_ADDR=:8771
./bin/openai
```
The binary reads a small set of environment variables shared across all the shim providers: `SPEECHIFY_API_KEY`, `SHIM_ADDR`, `SPEECHIFY_BASE_URL`, `SPEECHIFY_VERSION`, `SHIM_DEFAULT_MODEL`, `SHIM_REQUEST_TIMEOUT`, and `SHIM_SHUTDOWN_TIMEOUT`. Only `SPEECHIFY_API_KEY` is required.
Confirm it's up:
```bash
curl -s -o /dev/null -w "%{http_code}\n" http://localhost:8771/healthz
```
That returned `200` on my run.
## Verify audio flows through the shim
The `openai` shim listens on `POST /v1/audio/speech`, accepts `Authorization: Bearer`, and reads `model`, `input`, `voice`, and `response_format` from the JSON body. That is the request Deepgram will send, so you can prove the whole path with one curl before you touch Deepgram at all:
```bash
curl -s -o shim-smoke.mp3 -w "%{http_code} %{size_download}\n" \
-X POST "http://localhost:8771/v1/audio/speech" \
-H "Authorization: Bearer placeholder-ignored-by-shim" \
-H "Content-Type: application/json" \
-d '{"model":"simba-3.2","input":"Deepgram voice agent, now speaking with Speechify.","voice":"geffen_32","response_format":"mp3"}'
```
The verified result was real audio from Speechify:
```text
200 60333 bytes
shim-smoke.mp3: MPEG ADTS, layer III, v2, 128 kbps, 24 kHz, Monaural
```
At this point the shim path is proven before Deepgram enters the picture. It built, started, passed `/healthz`, took an OpenAI-shaped request with a throwaway Bearer token, called the live Speechify API, and returned a playable 24 kHz MP3.
## Point Deepgram's settings at the shim
In the Deepgram Voice Agent `Settings` message, set the TTS provider to `open_ai` and give it an `endpoint` pointing at your deployed shim. The full settings shape is Deepgram's, so use [Configure Voice Agent](https://developers.deepgram.com/docs/configure-voice-agent) and [Voice Agent TTS models](https://developers.deepgram.com/docs/voice-agent-tts-models) as the reference for the rest of the message.
```json
{
"type": "Settings",
"audio": {
"output": { "encoding": "linear16", "sample_rate": 24000 }
},
"agent": {
"speak": {
"provider": {
"type": "open_ai",
"model": "simba-3.2",
"voice": "geffen_32"
},
"endpoint": {
"url": "https://your-shim-host.example/v1/audio/speech",
"headers": {
"authorization": "Bearer placeholder-ignored-by-shim"
}
}
}
}
}
```
Pick a real Speechify model and voice here. The `model` and `voice` you set are forwarded to the shim, and the shim passes any name it does not recognise straight through to Speechify. Don't rely on the OpenAI defaults (`tts-1`, `alloy`): the shim resolves an unrecognised model through `SHIM_DEFAULT_MODEL`, and on a default build that is the retired `simba-english`, so `tts-1` can come back `400 model_retired`. Set `model: "simba-3.2"` and `voice: "geffen_32"` explicitly and Deepgram sends those verbatim, so the agent speaks with a current Simba 3.2 voice. That is the voice-quality reason this hop is worth it: Simba 3.2 brings streaming ~430ms to first byte, and serves every English voice in the catalogue, covered in [Simba 3.2 on the Artificial Analysis TTS leaderboard](/blog/simba-3-tops-artificial-analysis-tts-leaderboard). Any voice whose `models` list includes `simba-3.2` in `GET /v1/voices` is fair game.
The `audio.output` block is not optional, and it cost me a session to learn why. The `open_ai` speak provider requires uncontainerized 24 kHz `linear16` output. Send `container: "wav"` or a 16 kHz rate and Deepgram rejects the whole `Settings` message with `INVALID_SETTINGS: OpenAI speak provider type requires audio output format to be uncontainerized 24kHz linear16` before it speaks at all.
## Does a real agent actually call the shim?
Yes, and it is worth proving rather than trusting the config. Deepgram calls your `endpoint.url` from its own cloud, so the shim has to be reachable on a public URL. Put a tunnel in front of the local shim:
```bash
ngrok http 8771
```
Then run a Voice Agent session with `speak` pointed at the tunnel. The [demo's `agent.js`](https://github.com/Speechify-AI/speechify-ai-demos/tree/main/deepgram-voice-agent-shim) opens a session with the Deepgram SDK, streams a sample WAV as the user's turn, and configures the `open_ai` speak endpoint to hit the shim:
```javascript
speak: {
provider: { type: "open_ai", model: "simba-3.2", voice: "geffen_32" },
endpoint: {
url: `${SHIM_URL}/v1/audio/speech`,
headers: { authorization: "Bearer placeholder-ignored-by-shim" },
},
},
```
In the verified run, ngrok's request inspector showed the proof: an inbound `POST /v1/audio/speech` arriving from a Deepgram cloud IP, carrying the request Deepgram built:
```json
{ "input": "Hello! How can I help you today?", "model": "simba-3.2", "voice": "geffen_32", "response_format": "pcm" }
```
The shim returned `200`, and the agent wrote 108,480 bytes of speech to `agent-output-0.wav` (a different byte count from the earlier curl smoke test because it is a different utterance and a raw PCM response rather than an MP3). That is Deepgram deciding to speak, sending `simba-3.2` and `geffen_32` through to the shim, and getting that exact Speechify voice back.
## Run the demo
The demo wraps the verified path in one script:
```bash
git clone https://github.com/Speechify-AI/speechify-ai-demos
cd speechify-ai-demos/deepgram-voice-agent-shim
cp .env.example .env
# paste SPEECHIFY_API_KEY into .env
./run.sh
```
It clones `tts-shims` at a pinned revision into an ignored `.shim/` folder, runs `make openai`, starts the binary, checks health, then writes `shim-smoke.mp3` from the live speak call and prints `speak 200 60333 bytes`. `DEEPGRAM_API_KEY` is in `.env.example` for the live-agent step, but the smoke test only needs `SPEECHIFY_API_KEY` because it exercises the shim endpoint directly, the same way Deepgram will.
When you deploy the shim for a real agent, put it behind HTTPS, set the same environment variables there, and give Deepgram the public URL. Your users never see the Speechify key, and neither does the browser tab running the agent.
## Related reading
If you are choosing the voice-agent layer first, start with [the Voice Agents API public beta](https://docs.speechify.ai/agents/changelog/2026/6/11). For latency expectations, read [how we think about latency in SpeechifyAI voice agents](/blog/how-we-think-about-latency-in-speechifyai-voice-agents). If you are adding TTS to code you own rather than routing through Deepgram, the [Speechify Speech SDK provider](/blog/speechify-speech-sdk-provider) and the [Node.js TTS walkthrough](/blog/using-tts-in-nodejs-with-speechify) are more direct. The full API surface is in the Speechify docs (https://docs.speechify.ai).
## FAQ
### Which tts-shims provider do I use for Deepgram Voice Agent?
Use the `openai` provider, because Deepgram's third-party TTS call is OpenAI-shaped when `provider.type` is `open_ai`. You build `make openai` and the shim serves `POST /v1/audio/speech`. The `deepgram` provider in the same repo is for the opposite direction, redirecting a tool that already calls Deepgram's own Aura Speak API to Speechify, which is not this use case.
### Does Deepgram send my Speechify key to the shim?
No. Deepgram sends only the placeholder token you put in `endpoint.headers.authorization`. The shim reads `SPEECHIFY_API_KEY` from its own server environment and calls Speechify with that, so the real key lives only where the shim runs.
### Do I have to change the OpenAI model and voice names?
Set the model explicitly: `model: "simba-3.2"` with a compatible voice such as `voice: "geffen_32"`. Don't lean on the OpenAI defaults — the shim resolves an unrecognised model through `SHIM_DEFAULT_MODEL`, and on a default build that is the retired `simba-english`, so `tts-1` can return `400 model_retired`. Setting a real Simba 3.2 model and voice is the only change you need.
### Can I run the shim in Docker?
Yes. The repo's Dockerfile takes the provider as a build arg, so the OpenAI image build is `docker build --build-arg PROVIDER=openai -t tts-shim-openai .`. The binary is static (`CGO_ENABLED=0`) and the image uses a distroless runtime.
### Where should I deploy this for production?
Anywhere that can hold a server-side environment variable and expose an HTTPS URL to Deepgram. Set `SPEECHIFY_API_KEY`, pick `SHIM_ADDR`, and keep the placeholder token in the Deepgram config. Add the usual service guardrails: logs, health checks, request timeouts, and a path to rotate the Speechify key without redeploying your agent.
--------------------------------------------------------------------------------
URL: https://speechify.ai/blog/add-read-aloud-to-docs
Title: Add read-aloud to a documentation site with the Speechify API
Add a listen button to documentation with the Speechify API. A framework-agnostic walkthrough with a concrete example you can copy.
A listen button on documentation means users can hear a page while they scan it, commute, or follow a walkthrough. This tutorial adds one to a docs site with the Speechify API. It is framework-agnostic, with a concrete example you can copy. The runnable demo ([demos/docs-read-aloud](https://github.com/Speechify-AI/demos/tree/main/demos/docs-read-aloud)) is a zero-dependency Node server with a Listen button wired up.
The pattern is simple: the browser grabs the page text and posts it to a small backend endpoint; that endpoint calls Speechify with your key and hands the audio back. Your API key stays on the server and never reaches the browser. Choose batch when you want a downloadable file, streaming when you want it to start immediately.
## Which endpoint do I need?
Two options, depending on how the audio should play.
- `POST /v1/audio/speech` returns one JSON response with the complete audio, base64-encoded. Good for a downloadable clip or a cached listen button.
- `POST /v1/audio/stream` returns audio in chunks. Better when you want playback to start before the whole page finishes generating.
For a docs read-aloud button, batch is simplest: generate the file and point the player at it.
## How do I send the page text?
Pull the article text from the page, strip navigation and boilerplate so you only send content, and post it to your own endpoint. The synthesis call happens on the server, so the API key is never shipped to the browser.
**Browser** — the Listen button posts the page text to your endpoint and plays what comes back:
```js
async function readAloud(text) {
const res = await fetch("/api/speak", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ text }),
});
const clip = await res.blob();
new Audio(URL.createObjectURL(clip)).play();
}
```
**Server** — the endpoint holds the key and synthesizes with the `@speechify/api` SDK, then returns the audio bytes:
```js
import { SpeechifyClient } from "@speechify/api";
const client = new SpeechifyClient({ token: process.env.SPEECHIFY_API_KEY });
// POST /api/speak -> { text }
const response = await client.audio.speech({
input: text,
voice_id: "geffen_32",
model: "simba-3.2",
audio_format: "mp3",
});
const audio = Buffer.from(response.audio_data, "base64");
// send `audio` back to the browser as the response body
```
That's the whole relay: button → your endpoint → Speechify → audio back. The runnable demo wires exactly this with a zero-config Node server.
## How do I keep the page scannable?
Keep the button small and top-of-page. Playback is an add-on, not the focus. Cache the generated file for static pages so repeat visits do not call the API again.
## How do I handle long pages?
For long articles, streaming keeps the first sound fast. If you stick with batch, generate a single file for the whole page. Either way, send clean text and pick a presentable voice.
## FAQ
### Can I read any page aloud?
Yes, with the page's text. Send the content you want spoken in the input.
### Batch or streaming for read-aloud?
Batch is simpler for a button. Streaming starts faster on long pages.
### Which model should I use?
`simba-3.2` for English, `simba-3.0` for multilingual docs.
--------------------------------------------------------------------------------
URL: https://speechify.ai/blog/adding-text-to-speech-to-web-and-mobile-apps
Title: Adding Text-to-Speech to a Web or Mobile App: The Practical Guide
What engineers actually use to add voice to web and mobile apps, and the four decisions that matter: the browser's built-in API versus a cloud one, streaming versus batch, where the key lives, and how to keep audio playing on iOS.
import SignupLink from "@/components/SignupLink.astro";
import DocsLink from "@/components/DocsLink.astro";
There are two ways to make an app talk, and the first one is free. Knowing when the free one is enough will save you a vendor contract, and knowing when it is not will save you a rewrite.
## Decision 1: the browser's built-in voice, or a cloud API
Every modern browser ships `SpeechSynthesis`, part of the Web Speech API. It costs nothing, needs no key, and works offline.
```js
const utterance = new SpeechSynthesisUtterance("Your order shipped this morning.");
speechSynthesis.speak(utterance);
```
That is the whole integration. If it meets your requirements, stop reading and ship it.
It will not meet them if any of these matter:
- **Consistency.** The voice is whatever the operating system provides. The same code sounds like one person on macOS, someone else on Windows, and a third on Android. You cannot pin a brand voice.
- **Quality.** Built-in system voices are noticeably more synthetic than current neural models. Users notice within a sentence.
- **Server-side audio.** `SpeechSynthesis` runs in the browser and speaks. It does not hand you a file. If you need to store, send, or post-process the audio, it cannot help.
- **iOS reliability.** Safari's implementation has long-standing quirks around autoplay and interrupted playback that will cost you days.
- **Language and voice control.** Coverage depends on what the user has installed, not on what you shipped.
A cloud TTS API solves all five, at the cost of a network round trip and a per-character bill. The practical rule: **use the browser API for accessibility affordances and convenience features, use a cloud API when the voice is part of the product.**
## Decision 2: streaming or batch
Cloud APIs generally offer two endpoints and the choice is about perceived speed, not total speed.
- **Batch** synthesizes the whole input, then returns one audio file. Simplest to handle. Right for anything pre-generated: a narrated article, a notification sound, an audiobook chapter.
- **Streaming** starts returning audio bytes before the full text is synthesized. The user hears the first word while the rest is still rendering.
For anything a user is waiting on, use streaming. A 30-word reply takes about the same total time either way, but with batch the user waits in silence for all of it, and with streaming they hear speech in a few hundred milliseconds. SpeechifyAI's Simba 3.2 is ~430ms to first byte, which is the number to compare across vendors for this.
```bash
curl -X POST https://api.speechify.ai/v1/audio/stream \
-H "Authorization: Bearer $SPEECHIFY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": "Your order shipped this morning and arrives Thursday.",
"voice_id": "geffen_32",
"model": "simba-3.2"
}' \
--output reply.mp3
```
## Decision 3: where the API key lives
This one is not a preference. **The key goes on your server.** Never in the client bundle, never in a mobile binary, never in an environment variable your bundler inlines into JavaScript.
A key shipped to the browser is a key that gets extracted, and TTS keys are metered, so the bill is the attack. Mobile is not safer: anyone can pull strings out of an APK or IPA.
The shape that works:
1. The client sends **text** to your backend.
2. Your backend calls the TTS API with the key.
3. Your backend returns audio, or a short-lived signed URL to it.
That server hop also gives you the place to put a per-user rate limit, which you want, because the failure mode of an unmetered TTS endpoint is a bill rather than an outage.
```js
// server route, key stays here
app.post("/api/speak", async (req, res) => {
const r = await fetch("https://api.speechify.ai/v1/audio/stream", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.SPEECHIFY_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
input: req.body.text,
voice_id: "geffen_32",
model: "simba-3.2",
}),
});
res.setHeader("Content-Type", "audio/mpeg");
r.body.pipe(res);
});
```
## Decision 4: making it actually play on mobile
Getting audio bytes is the easy half. Playing them reliably on a phone is where the time goes.
**Autoplay is blocked until the user gestures.** iOS and Android both require a user interaction before audio plays. Audio that starts on page load, on a timer, or after an async fetch that resolves later than the tap will be silently blocked. The reliable pattern is to create and unlock the audio context inside the tap handler itself, then feed it when the bytes arrive.
**The silent switch.** On iOS, `