--- title: "ElevenLabs Alternatives for a TypeScript Voice Agent" description: "Cartesia, Gradium, OpenAI and four local engines share one TypeScript interface. Switching engine is a one-line change. FallbackTTS keeps a backup ready." url: "https://micdrop.dev/blog/elevenlabs-alternatives-typescript" --- [Micdrop](/) › [Blog](/blog) # ElevenLabs Alternatives for a TypeScript Voice Agent Cartesia, Gradium, OpenAI and four local engines share one TypeScript interface. Switching engine is a one-line change. FallbackTTS keeps a backup ready. September 12, 2026 [Godefroy de Compreignac](https://github.com/Godefroy) Key takeaways * Your ElevenLabs plan caps how many syntheses run at once, 20 concurrent Flash requests on Pro and 30 on Scale. A voice product hits that ceiling long before it spends its credits. * Cartesia, Gradium, OpenAI, Kokoro, Piper, Pocket TTS and Qwen3-TTS all speak PCM16 at 16 kHz behind a single TypeScript interface in Micdrop, so switching engine means replacing the line that creates it. * Gradium synthesises on an EU endpoint, so you can name the region when a customer asks where the audio is generated. * Micdrop ships a FallbackTTS class that holds a list of providers and replays the unspoken text to the next one when the first gives up mid-sentence. Teams look for an alternative to [ElevenLabs](/docs/ai-integration/provided-integrations/elevenlabs) when the voice engine of their agent starts to limit them: a plan that caps simultaneous calls, a per-character bill that grows with usage, customers who need the audio generated in Europe, or the wish to run the voice on their own servers. No single engine fixes all of that. Cartesia is built for a fast first word at a lower price, Gradium generates the audio in Europe, OpenAI uses the key your agent already has, and Kokoro, Piper, Pocket TTS and Qwen3-TTS run locally with no bill at all. This article compares these engines on languages, voices, where they run and how they bill, then shows how to switch from ElevenLabs to one of them in a TypeScript voice agent built on Micdrop, where the change fits in one line of code. ## Why teams look for an ElevenLabs alternative Most teams hit the concurrency ceiling first. Few of them knew it was there. Your plan sets how many syntheses ElevenLabs runs at the same time. The [model documentation](https://elevenlabs.io/docs/models) publishes the limits: 20 concurrent Flash requests on Pro, 30 on Scale, half those numbers on Multilingual v2. A blog reading feature never reaches that ceiling. A voice agent does, because every live call holds a slot for as long as the agent is talking. ElevenLabs charges a credit per character on Multilingual v2 and half that on Flash. Those credits come in [plans](https://elevenlabs.io/pricing) running from $6 a month for 30,000 credits to $990 for six million. Your bill grows with how much your agent says. To budget calls, compare the [cost per hour of generated audio for each voice provider](/docs/ai-integration) rather than the price of a character. Every hosted provider has outages. When text to speech fails, your agent goes silent while a caller waits for an answer. Configure a second engine before that happens, especially when the voice is your interface. Data residency comes up with European buyers. Teams in health, education and the public sector ask where the audio is synthesised. Engine Runs Languages Voice catalog Reach for it when [ElevenLabs](/docs/ai-integration/provided-integrations/elevenlabs) Hosted API 29+ 1000+ The voice is what sells the product [Cartesia](/docs/ai-integration/provided-integrations/cartesia) Hosted API 15 50+ The pause before the first word matters [Gradium](/docs/ai-integration/provided-integrations/gradium) Hosted API, EU endpoint 5 150+ The audio has to stay in Europe [OpenAI](/docs/ai-integration/provided-integrations/openai) Hosted API The one you write in 13 You already hold an OpenAI key [Kokoro](/docs/ai-integration/provided-integrations/kokoro) Your Node process English 28 The whole setup has to be one npm install [Piper](/docs/ai-integration/provided-integrations/piper) A subprocess you spawn 43 100+, one file each The call happens in a language besides English [Pocket TTS](/docs/ai-integration/provided-integrations/pocket-tts) Your Node process English Cloned from a sample A specific voice has to come back [Qwen3-TTS](/docs/ai-integration/provided-integrations/qwen-tts) An mlx-audio server on a Mac 10 9 A local voice takes style instructions OpenAI’s speech API takes no language parameter and speaks whatever text you send it. The `gpt-4o-mini-tts` model adds prosody instructions written in plain English, so you can ask it for a slower delivery or a French accent. Listen to OpenAI, ElevenLabs and Gradium back to back and OpenAI sounds the least polished. You stay with one vendor, though, since the same key covers the agent and the speech. ## Cartesia, when latency is the constraint [Cartesia](https://cartesia.ai) built Sonic around time to first audio. A caller hears the gap between the end of their own sentence and the first syllable of the answer. Once the answer starts, nobody counts how fast the words come. Cartesia also charges per character, less than ElevenLabs at every tier, with plans from $5 a month to $299 on [its pricing page](https://cartesia.ai/pricing). It covers fifteen languages, against at least twenty-nine at ElevenLabs. Its voice catalog is smaller too. ``` import { CartesiaTTS } from '@micdrop/cartesia' const tts = new CartesiaTTS({ apiKey: process.env.CARTESIA_API_KEY || '', modelId: 'sonic-turbo', voiceId: process.env.CARTESIA_VOICE_ID || '', language: 'en',}) ``` Micdrop cuts the agent’s answer into sentences and hands them to the engine one at a time, so the caller hears the opening line while the model is still writing the end of the paragraph. The caller waits once, before the first sentence starts, so a fast first syllable matters even more. ## Gradium, when the audio has to stay in Europe [Gradium](https://gradium.ai) is a French provider covering both transcription and voice. Its API exposes an EU endpoint and a US one. The Micdrop integration sends everything to the EU by default, and the `region` option switches it to the US. ``` import { GradiumTTS } from '@micdrop/gradium' const tts = new GradiumTTS({ apiKey: process.env.GRADIUM_API_KEY || '', voiceId: process.env.GRADIUM_VOICE_ID || '', region: 'eu',}) ``` Voice is one of the three parts of a call, so the residency answer holds only when the agent and the transcription stay in Europe too. [Mistral](/docs/ai-integration/provided-integrations/mistral) drives the agent and transcribes with Voxtral, while Gladia and Gradium both transcribe. With these three providers you can build a [sovereign voice AI pipeline that keeps the audio inside the European Union](/docs/ai-integration/sovereign-voice-ai). Compliance still depends on where you host and on the terms you sign with each provider. ## Kokoro, Piper, Pocket TTS and Qwen3-TTS, when the voice runs on your own machine These four engines need no API key. The audio stays on your machine. Kokoro installs with one npm command and speaks English. Piper runs a small binary as a subprocess and covers 43 languages, more than the other three put together. Pocket TTS clones a voice from a few seconds of audio and speaks English. Qwen3-TTS goes through an mlx-audio server, which needs a Mac, and handles ten languages plus style instructions. Run the voice yourself and you drop both the per-character bill and the residency question. In exchange, the first word comes later and you have one more service to keep running. Kokoro, Piper and Pocket TTS differ a lot on [local text to speech latency and memory](/blog/local-tts-node-kokoro-vs-piper), measured on the same laptop. ## Swapping one for another in a TypeScript pipeline Every engine Micdrop packages extends the same abstract `TTS` class from `@micdrop/server`. The class takes a stream of text and emits PCM16 audio at 16 kHz, the format the browser client plays. Your own code never sees which provider produced the bytes. A migration looks like this, in full: ``` import { MicdropServer } from '@micdrop/server'import { OpenaiAgent } from '@micdrop/openai'import { GladiaSTT } from '@micdrop/gladia'// Was: import { ElevenLabsTTS } from '@micdrop/elevenlabs'import { CartesiaTTS } from '@micdrop/cartesia' new MicdropServer(socket, { agent: new OpenaiAgent({ apiKey: process.env.OPENAI_API_KEY || '', systemPrompt: 'You are a helpful assistant', }), stt: new GladiaSTT({ apiKey: process.env.GLADIA_API_KEY || '' }), tts: new CartesiaTTS({ apiKey: process.env.CARTESIA_API_KEY || '', modelId: 'sonic-turbo', voiceId: process.env.CARTESIA_VOICE_ID || '', }),}) ``` The interruption handling, the sentence splitting, the WebSocket protocol and the browser playback stay untouched, because they were never provider-specific. Every integration implements `cancel()` on the same interface, so cutting the agent off mid-sentence works the same whichever engine is speaking. One interface also makes A/B testing cheap. Read the provider from an environment variable, hand each call the engine you want to hear, and compare on real conversations rather than on the demo clips a vendor puts on its website. ## Writing your own integration for another provider Micdrop packages eight engines, so the ninth is yours to write. Deepgram, Azure, Google and Amazon all publish streaming speech endpoints. So does a model you fine-tuned and host yourself. To write your own, extend `TTS`, implement two methods, `speak(textStream)` and `cancel()`, then emit an `Audio` event per chunk. You can start from [two working custom TTS skeletons](/docs/ai-integration/custom-integrations/custom-tts), one for a WebSocket API that streams as it generates and one for an HTTP API that returns the whole clip. Your class then drops into the same `tts` slot as the packaged ones, and into `FallbackTTS` alongside them. ## Keeping a second engine ready with FallbackTTS Your replacement engine usually makes the best backup, so configure both at once with [`FallbackTTS`](/docs/ai-integration/fallback-strategies/tts-fallback). It holds a list of factories, uses the first, and moves to the next when the current one gives up after its retries. ``` import { FallbackTTS } from '@micdrop/server'import { ElevenLabsTTS } from '@micdrop/elevenlabs'import { CartesiaTTS } from '@micdrop/cartesia' const tts = new FallbackTTS({ factories: [ () => new ElevenLabsTTS({ apiKey: process.env.ELEVENLABS_API_KEY || '', voiceId: process.env.ELEVENLABS_VOICE_ID || '', maxRetry: 2, // Give up early so the switch happens fast }), () => new CartesiaTTS({ apiKey: process.env.CARTESIA_API_KEY || '', modelId: 'sonic-turbo', voiceId: process.env.CARTESIA_VOICE_ID || '', }), ],}) ``` `FallbackTTS` keeps a copy of the text it sends. When a provider fails halfway through a sentence, the next engine picks up the words that never got spoken, so the caller hears the whole answer in a different voice. graph TD A\[Agent writes the answer\] --> B\[FallbackTTS receives the text\] B --> C\[ElevenLabs synthesises\] C -->|Audio| D\[PCM16 to the browser\] C -->|Failed after 2 retries| E\[Destroy it, start Cartesia\] E --> F\[Replay the unspoken text\] F --> D Set `maxRetry` low on the first provider so the caller barely notices the switch. The default is three retries a second apart, which leaves the call silent for three seconds before the switch even starts, on top of the time each attempt takes to fail. The list rotates rather than ending, so the last provider hands back to the first. Put a local engine last and the call keeps a voice even while every hosted API you use is down. ## Which engine to pick Stay on ElevenLabs when the voice itself is the product and your peak call count fits under your plan’s concurrency limit. Cartesia, Gradium, OpenAI and the local engines all have smaller voice catalogs. Switch to Cartesia when callers complain about the silence before the first word, and when the per-character bill has started to matter. Pick Gradium when your buyer needs the audio synthesised in Europe. Before you promise anything, check how to [move the agent and the transcription to Europe with the voice](/docs/ai-integration/sovereign-voice-ai). OpenAI suits a team that would rather keep one vendor for the agent and the voice, when the exact timbre matters less than the number of contracts. A local engine makes the per-character bill disappear, as long as you have somewhere to run the model. Whichever you pick, configure two of them. The second engine costs one factory function to write. You get that back the first time your main provider goes down mid-call. ## Frequently asked questions ### What is the best ElevenLabs alternative for a voice agent? It depends on which constraint pushed you off ElevenLabs. Cartesia is the closest match, a hosted streaming API billed per character and built around time to first audio. Gradium answers the European data residency question. Kokoro, Piper, Pocket TTS and Qwen3-TTS remove the bill entirely by running on your own hardware. All of them have a smaller voice catalog than ElevenLabs, so when your product sells on one specific voice, stay on ElevenLabs and add a fallback rather than switch. ### Is there a free alternative to ElevenLabs? Yes, if you count the engines you run yourself. Kokoro is Apache 2.0, Pocket TTS is MIT, Piper moved to GPL-3.0 when it absorbed espeak-ng, and all three generate audio on a laptop CPU with no API key. Qwen3-TTS is free too, and it runs through an mlx-audio server on a Mac. Free covers the software and the synthesis. You still pay for the machine that runs it and for the memory the model holds while your server is up. Hosted APIs offer free tiers instead, sized for trying a voice rather than for serving calls. ### Which text to speech API has the lowest latency? Cartesia Sonic and ElevenLabs Flash both compete on time to first audio. ElevenLabs [publishes around 75 ms of inference](https://elevenlabs.io/docs/models) for Flash, excluding the network. Treat every published number as a floor, since your own latency includes the round trip from your server and the provider’s queue at that moment. Measure the engines you shortlisted from the region you deploy in, on sentences your agent actually says. ### Can I use ElevenLabs and another provider at the same time? Yes, and that is what `FallbackTTS` is for. It takes a list of factory functions, speaks through the first, and switches to the next when the current one fails after its retries, replaying the text that was never spoken. Lower `maxRetry` on the primary so the switch starts sooner, since every retry adds its delay to the silence. The voice changes mid-answer, which callers accept more easily than silence. ### Is there a European alternative to ElevenLabs? Gradium is the European voice provider Micdrop integrates. It is French, it covers both transcription and voice, and its API has an EU endpoint that the integration uses by default. For a whole call to stay in Europe the agent and the transcription have to follow. Mistral, Gladia and Gradium cover those three parts together in the sovereign voice AI guide. Micdrop makes that architecture possible. The compliance claim belongs to your deployment and to the contracts you sign with each provider. ### How do I switch text to speech provider without rewriting my app? Put the engine behind an interface. Micdrop does that with its abstract `TTS` class. Every integration emits PCM16 at 16 kHz and implements `cancel()`, so the sentence splitting, the interruption handling, the WebSocket and the browser playback stay the same whichever provider speaks. To change engine, you replace the object you pass to the `tts` option, for example `new ElevenLabsTTS(...)` with `new CartesiaTTS(...)`. For a provider with no package, you write your own class, two methods long, following the custom TTS guide. * * * The text-to-speech provider you pick on day one is the part of the stack most likely to change. [Micdrop](/) keeps that decision reversible. The engines sit behind one interface in your own Node server, `FallbackTTS` keeps a second one ready, and you switch engine by replacing the line that creates it. You can [run a first voice call in about five minutes](/docs/getting-started), then [compare every voice provider side by side](/docs/ai-integration). ![ElevenLabs Alternatives for a TypeScript Voice Agent](/.netlify/images?url=_astro%2Fthumbnail.DyoP69QJ.jpg&w=1200&h=630&dpl=6ab2987e8bb0ee00084b7f1f) On this page [1\. Why teams look for an ElevenLabs alternative](#why-teams-look-for-an-elevenlabs-alternative) [2\. Cartesia, when latency is the constraint](#cartesia-when-latency-is-the-constraint) [3\. Gradium, when the audio has to stay in Europe](#gradium-when-the-audio-has-to-stay-in-europe) [4\. Kokoro, Piper, Pocket TTS and Qwen3-TTS, when the voice runs on your own machine](#kokoro-piper-pocket-tts-and-qwen3-tts-when-the-voice-runs-on-your-own-machine) [5\. Swapping one for another in a TypeScript pipeline](#swapping-one-for-another-in-a-typescript-pipeline) [6\. Writing your own integration for another provider](#writing-your-own-integration-for-another-provider) [7\. Keeping a second engine ready with FallbackTTS](#keeping-a-second-engine-ready-with-fallbacktts) [8\. Which engine to pick](#which-engine-to-pick) [9\. Frequently asked questions](#frequently-asked-questions) On this page 1\. Why teams look for an ElevenLabs alternative 2\. Cartesia, when latency is the constraint 3\. Gradium, when the audio has to stay in Europe 4\. Kokoro, Piper, Pocket TTS and Qwen3-TTS, when the voice runs on your own machine 5\. Swapping one for another in a TypeScript pipeline 6\. Writing your own integration for another provider 7\. Keeping a second engine ready with FallbackTTS 8\. Which engine to pick 9\. Frequently asked questions Build your own voice agent Micdrop handles the microphone, the streaming and the turn taking. Bring your own API keys and ship a voice mode in an afternoon. [Get started](/docs/getting-started) ## Keep reading [![Local Text to Speech in Node: Kokoro, Piper, Pocket TTS](/.netlify/images?url=_astro%2Fthumbnail.9VKFXwtj.jpg&w=1200&h=630&dpl=6ab2987e8bb0ee00084b7f1f) September 2, 2026 ## Local Text to Speech in Node: Kokoro, Piper, Pocket TTS Three engines speak from a Node server with no API key. Pocket TTS speaks first, Piper covers 43 languages, Kokoro installs in one command. ](/blog/local-tts-node-kokoro-vs-piper) [![Best Open Source Voice AI Agent Frameworks in 2026](/.netlify/images?url=_astro%2Fthumbnail.BqaPB_wi.jpg&w=1200&h=630&dpl=6ab2987e8bb0ee00084b7f1f) August 13, 2026 ## Best Open Source Voice AI Agent Frameworks in 2026 Thirteen voice agent frameworks and hosted platforms compared on language, transport, licence and cost. Micdrop publishes this ranking and sits third in it. ](/blog/open-source-voice-agent-frameworks) [![OpenAI Realtime API vs an STT-LLM-TTS Pipeline](/.netlify/images?url=_astro%2Fthumbnail.CAvnwCrm.jpg&w=1200&h=630&dpl=6ab2987e8bb0ee00084b7f1f) August 19, 2026 ## OpenAI Realtime API vs an STT-LLM-TTS Pipeline The Realtime API gives you speech to speech in one connection. A pipeline gives you provider choice, voices and cost control. Here is how to pick between them. ](/blog/openai-realtime-api-vs-pipeline)