Voxtral 3

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Voxtral 3

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Voxtral 3 introduces a cutting-edge sound delegate SDK and state-of-the-art address models designed for real-time, multi-step conversations throughout 50+ languages. It combines exact transcription, natural address synthesis alongside affectional adaptability, and profound tool integration for seamless workflow automation. Available via Mistral’s EU-hosted API or self-deployment, it ensures data sovereignty during delivering low-latency, human-like interactions for communication centers, virtual assistants, and hands-free copilots.

Speech transcription and sound generation have arrive a lengthy way, but construction end-to-end sound agents that can listen, reason, interact, and grip complex workflows remains difficult. 

A dependable sound delegate needs to do four things extremely fine (and simultaneously): 

  1. Listen accurately across languages, accents, speakers, and interruptions,

  2. Reason deeply about what users average in particular contexts,

  3. Speak naturally with emotion and expression, and 

  4. Take act over multiple steps through connected systems. 

Getting all four to activity together reliably in genuine period remains a challenge. 

To location this, we current Voxtral 3: a new family of state-of-the-art speech-to-text and text-to-speech models, alongside a sound delegate SDK that brings listening, thinking, tool calling, and speaking into a sole real-time streaming pipeline.

Voxtral 3 is built to create natural conversational experiences, from contact-center agents and assistance desks to virtual assistants and hands-free copilots. With assistance for dozens of languages, expressive speech, complex reasoning, and profound integration alongside your own tools and data, agents built alongside Voxtral can construe nuanced intent, logic through advanced requests, and execute multi-step actions throughout connected systems.

As alongside another Mistral models, the Voxtral 3 family is designed for sovereign deployment. Available today through Mistral's EU-hosted API or for self-deployment on your own infrastructure, it gives organizations authority complete anywhere audio is processed, how data is handled, and whether conversations are retained.

Highlights

  1. Accurate transcription throughout 50+ languages. The speech-to-text model, Voxtral Small Transcribe 3, is state-of-the-art in multilingual transcription, identifying who stated what (diarization), using keyphrases to enhance its accuracy (context-biasing). It detects whenever person has completed speaking so agents can react without postpone (end-of-turn detection).

  2. Natural address that adapts to the conversation. The text-to-speech model, Voxtral Mini TTS 3, introduces new voices that modify their emotion, pace, and accent according to conversational context, alongside assistance for 35+ languages and 50+ dialects.

  3. Human-like intellect at your (spoken) command. The new sound delegate SDK combines listening, reasoning, tool calling, and speaking into a real-time experience. Agents can recover information, engage alongside endeavor systems, and complete tasks during live conversations complete phone or web.

  4. Pro Voice for distinctly exact sound adaptation. For expert use cases anywhere essential sound cloning does not suffice, Voxtral’s Pro Voice adaptation is capable to reproduce a speaker’s distinctive character, affectional range, and speaking manner throughout languages, using fair 30 minutes of audio. 

  5. Your sound AI, on your infrastructure. Use Mistral's EU-hosted API or deploy Voxtral 3 on your own infrastructure. Keep delicate conversations inside your surroundings and authority whether any audio is retained. 

Try Voxtral now  | Learn more

It hears 50+ languages, alongside state-of-the-art accuracy.

Voxtral Transcribe 3 represents a important milestone throughout transcription, diarization (who said when) and environment biasing capabilities. The supported catalog of languages is expanded to 50, including 24 authoritative EU languages and many low-resource Asian and Indic languages.

The Small type achieves state-of-the-art results throughout diarization and multilingual transcription, including in English, French and Spanish. It outperforms Whisper, Scribe v2 and Gemini 3.5 Transcribe. The Mini variant is 4B parameters, enabling accelerated and exact transcriptions at a cost of $0.0035/min.

Both models assistance environment biasing, anywhere key conditions and free-form content can be stated to bias the transcription and enhance recall on specialized terms. This enables them to be used in manufacturing settings alongside domain-specific vocabulary without the need for fine-tuning.

FLEURS 45 Forced vs Inferred

Word Error Rate — lesser is better

  • Forced

  • Inferred

4.1%4.0%4.1%4.0%4.6%4.5%6.1%4.5%4.9%4.9%6.3%5.6%16.0%14.9%Voxtral Small Transcribe 3Microsoft AI Transcribe 2Voxtral Mini Transcribe 3Gemini 3.5 TranscribeScribe v2GPT TranscribeWhisper large-v32.0%4.0%6.0%8.0%10.0%12.0%14.0%16.0%Word Error Rate

Macro-average WER complete the intersection of 45 languages in the FLEURS benchmark supported by all seven models. WER is used for all languages apart from Japanese, Korean, Thai, and Chinese, which use CER. Lower is better.

Forced = tongue specified; Inferred = tongue auto-detected. Languages: AR, BN, BG, CA, ZH, CS, DA, NL, EN, ET, FI, FR, DE, EL, GU, HI, HU, IS, ID, IT, JA, KN, KO, LV, LT, MK, MS, ML, MR, NO, FA, PL, PT, RO, RU, SK, SL, ES, SV, FIL, TE, TH, TR, UK, VI

Diarization

Concatenated Minimum Permutation WER — lesser is better

18.4%18.6%19.0%20.3%23.0%30.9%38.4%Voxtral Small Transcribe 3Voxtral Mini Transcribe 3Pyannote Orchestrator (Precision 3)Microsoft AI Transcribe 2Scribe v2Voxtral Mini Transcribe 2Gemini 3.5 Transcribe15.0%20.0%25.0%30.0%35.0%40.0%Concatenated Minimum Permutation WER

Macro-average concatenated minimum permutation WER (cpWER) complete community diarization benchmarks: AMI-IHM, AMI-SDM, Switchboard, Switchboard CallHome, AISHELL-4. For maximum compatibility of API baselines, we use 30 infinitesimal versions of AMI and AISHELL. Lower is better.

Diarization benchmark, Concatenated Minimum Permutation Word Error Rate (cpWER).

Keyphrase Recall

With and without contextual prompting — higher is better

  • Without Context

  • With Context

94.6%81.4%94.3%84.0%87.3%80.9%Voxtral Small Transcribe 3Scribe v2Gemini 3.5 Transcribe75.0%80.0%85.0%90.0%95.0%100.0%Keyphrase Recall

Voxtral Small Transcribe 3 is highlighted in brand colours. Keyphrase recall on the Earnings 22 benchmarks. The environment bias contains keyterms and a randomly sampled figure of distractors, ranging from 0 to 100. Bars are superposed complete values — the external bar is recall alongside context, the inner bar is recall without context; the apparent collection is the uplift from contextual prompting. Higher is better.

Keyphrase recall benchmark. Context = domain-specific vocabulary and speaker names supplied to the model.

Artificial Analysis Benchmark

Word Error Rate — lesser is better

Fun-Realtime-ASR-previewMicrosoft AI Transcribe 2Voxtral Small Transcribe 3Scribe v2Voxtral Mini Transcribe 3Grok Voice Transcribe 2.0Microsoft AI Transcribe 1.5StepAudio 3 ASRGemini 3.5 TranscribeVoxtral SmallGemini 3.1 Pro Preview (High)Universal-3.5 ProSolaria-3, GladiaGPT TranscribeSmallest AI PulseResonant-1Smallest AI Pulse ProInkling, Thinking MachinesQwen3.5 Omni Plus RealtimeGemini 3.1 Pro Preview (Low)Voxtral Mini Transcribe 2Soniox v5 AsyncInworld STT 1GPT-4o TranscribeEnhancedWhisper large-v3Qwen3 ASR FlashAmazon TranscribeModulate STT Batch English VFastCanary Qwen 2.5BChirp 3GPT-4o Mini Transcribecohere-transcribe-03-2026Nova 2 Pro, AmazonMeliaNova-3, DeepgramRev AI1.0%2.0%3.0%4.0%5.0%6.0%AA WER

Artificial Analysis WER Index, a valued average complete VoxPopuli, Earnings-22 and AgentTalk.

Lower is better.

Voxtral Realtime Transcribe 3 is a realtime transcription example built for agentic use-cases. It achieves high-quality transcriptions at sub-500ms latency in complete 35 languages, including alongside diarization and environment biasing.

FLEURS 35

Realtime transcription Word Error Rate — lesser is better

4.0%4.2%5.7%5.8%6.0%6.4%7.4%8.4%8.7%Voxtral Mini Transcribe 3*Gemini 3.5 Realtime TranscribeVoxtral Mini Realtime 3 · 2400 msMicrosoft AI Transcribe 2 StreamingVoxtral Mini Realtime 3 · 960 msVoxtral Mini Realtime 3 · 480 msVoxtral Mini Realtime 3 · 240 msGPT Live TranscribeScribe v2 Realtime3.0%4.0%5.0%6.0%7.0%8.0%9.0%10.0%Word Error Rate

Macro-average WER complete 35 languages from the FLEURS benchmark. WER is used for all languages apart from Japanese, Korean, and Chinese, which use CER. Lower is better. *Voxtral Mini Transcribe 3 is an offline baseline. The remaining models are realtime.

Languages: AR, BN, BG, CA, CS, NL, EN, ET, FI, FR, DE, EL, GU, HI, ID, IT, JA, KN, KO, LV, MK, MS, ML, MR, NO, FA, PL, PT, RO, RU, SK, ES, FIL, TE, TR

End-of-turn prediction is natively supported, incorporating the two acoustic and semantic data to accurately foretell whenever a person is completed speaking. This allows for low-latency sound delegate applications, during minimizing false cut-off rates whenever the person is prematurely interrupted.

It answers alongside the correct emotion, in your or your customer’s brand's own sound and local dialect.

Voxtral Mini TTS 3.0, accessible in lot and realtime, achieves state-of-the-art expressiveness and education following for 35+ languages and 50+ dialects. At $13 per 1M characters, Voxtral Speech 3 expenses small to run than comparable models from OpenAI TTS-1, Deepgram, ElevenLabs Flash and Gemini Flash.

The address example implicitly interprets the semantic definition of environment better, producing natural address throughout a varied range of emotions and languages. New and improved features contain sound cloning from 30+ minutes of sampled audio, tradition immediate education following (IF), contextual TTS, and a vocabulary library, all of which assist the goal of address reliability in deployment. Variables for Explicit IF contain emotion, pacing, and emphasis.

Prompt

Let's end the conversation here: it's GIF.

Non-standard phoneme hint: dʒ ɪ f

All natural-sounding address relies on emotion, which determines its prosody, rhythm, pacing, emphasis, and transitions. Voxtral TTS natively interprets a prompt’s content environment to decide the emotion and sound style, making the example inherently improved at natural address without requiring additional instructions or sound prompts.

Voice Code Bench: norm per dollar

Voice Code Bench made by BeSimple AI is focused on endeavor client assistance nonaccomplishment states connected to numbers and distinctive names.

  • Other TTS

  • Mistral

20%40%60%80%100%$0$10$20$30$40$50$60$70$80$90Faithful clipsPrice (USD per 1M characters)Eleven v4Eleven v4 TurboInworld TTS-2Inworld TTS-2 FlashFish Drama 3Gemini 3.8 Flash TTSQwen-Audio 3.1 FlashQwen-Audio 3.0 PlusCartesia Sonic 3.6Gemini 3.8 Flash Lite TTSDeepgram Flux TTSSpeechify Simba 3.2OpenAI gpt-4o-mini-ttsBreeze TTS 2StepFun StepAudio 2.5Voxtral TTS

Up and to the remaining is better.

Voice Code Bench (BeSimple AI): 300 English prompts, 2 voices per scheme (female and male); fairness gemini-3.8-flash; prices from vendor pricing pages; generated 2026-10-20.

Pronunciation control: norm per dollar

Share of clips anywhere the mark term is pronounced as intended, alongside its phonemes

  • Mistral

  • Other TTS

50%60%70%80%90%$0$10$20$30$40$50$60$70$80$90Accurate pronunciationsPrice (USD per 1M characters)Voxtral TTSInworld TTS-2Cartesia Sonic 3.6Inworld TTS-2 FlashFish Drama 3Qwen-Audio 3.1 FlashEleven v4 TurboEleven v4Deepgram Flux TTSQwen-Audio 3.0 Plus

Internal eval. Up and to the remaining is better. Systems without a documented articulation authority are listed in the data, not plotted.

300 English sentences, all alongside one rare or made-up term (150 easy, 150 hard), 2 voices per system; fairness gemini-3.8-flash hears the clip alongside the word's intended IPA; prices from vendor pricing pages; generated 2026-10-20.

Multilingual: norm per dollar

Mean fairness mark throughout 11 languages, 1 native sound per tongue and system

  • Other TTS

  • Mistral

2.503.003.504.00$0$10$20$30$40$50$60$70$80$90Mean fairness mark (11 languages)Price (USD per 1M characters)Eleven v4Eleven v4 TurboCartesia Sonic 3.6Fish Drama 3Gemini 3.8 Flash Lite TTSGemini 3.8 Flash TTSInworld TTS-2Inworld TTS-2 FlashOpenAI gpt-4o-mini-ttsVoxtral TTS

Internal eval. Up and to the remaining is better. Systems covering small than 11 languages are listed in the data, not plotted.

377 prompts selected for release, 11 languages, unweighted average of per-language average fairness scores, 1 to 5 scale; fairness gemini-3.8-flash; prices from vendor pricing pages; generated 2026-10-20.

Expressive English: norm per dollar

Mean fairness mark on one_eval, 237 prompts selected for release

  • Other TTS

  • Mistral

2.602.803.003.20$0$10$20$30$40$50$60$70$80$90Mean fairness scorePrice (USD per 1M characters)Eleven v4Cartesia Sonic 3.6Eleven v4 TurboInworld TTS-2Gemini 3.8 Flash Lite TTSGemini 3.8 Flash TTSInworld TTS-2 FlashFish Drama 3Speechify Simba 3.2Qwen-Audio 3.1 FlashBreeze TTS 2OpenAI gpt-4o-mini-ttsStepFun StepAudio 2.5Deepgram Flux TTSQwen-Audio 3.0 PlusVoxtral TTS

Internal eval. Up and to the remaining is better.

Expressive English (one_eval): 237 prompts selected for release, 2 voices per scheme (Voxtral TTS: Sarah and James), 1 to 5 scale; fairness gemini-3.8-flash; prices from vendor pricing pages; generated 2026-10-20.

Illustrating Voxtral hill-climbing in expressiveness, numbers and distinctive names.

Prompt

Thank you for calling Mistral! I comprehend you're having difficulty logging into AI Studio. Can I verify your email address? I have current [email protected], is that correct?

Speech appears local in 35 languages and complete 50 dialects.

Voxtral TTS supports complete 35 languages and local dialects. Our multilingual evals adhere to dialect differences in pronunciation, ceremonial vs. informal register, spelling, verbosity, and locale conventions (time, dates, temperatures, addresses, currencies).

Voxtral 3 multilingual library

Voice Presets are accessible in 18 languages: Arabic (Emirati, Modern Standard), Brazilian (Portuguese), Catalan, Chinese (Mandarin), Dutch, English (American, British), French (France), German, Greek, Hindi, Italian, Korean, Norwegian, Russian, Spanish (Spain), and Vietnamese.

The sound delegate is in authority of the entire conversation.

Voxtral 3 introduces a sound delegate SDK, built on LiveKit, that runs address in, reasoning, and address out as one streaming pipeline. Voxtral Mini Transcribe Realtime 3 listens and detects whenever the visitant has completed speaking, a broad model—like Mistral Small—reasons and calls tools, and Voxtral Speech 3 replies in the spirit of the conversation so far. No phase waits for the one before it, so all rotate completes in under one second, and the delegate stops talking whenever the visitant cuts in.

During a call, the delegate can verify a caller's identity, inspect a bill, or publish an appointment, using function calling, web search, and retrieval complete your own systems. It answers and places calls complete SIP, runs in browsers and apps complete WebRTC, and connects to the telephony, IVR, and contact-center application you already use.

Each phase is a distinct model, so you can alter the LLM, the voice, or the tongue without rewriting the agent, and run the entire stack on Mistral's API in Europe or on your own infrastructure.

Get started.

Voxtral 3 is accessible today through the Mistral API, hosted through our European, US, and earth endpoints.

You can test out sound agents, audio transcription, address generation, and sound cloning in the Studio playgrounds. 

Model

Price

Voxtral Mini Transcribe 3 (batch)

$0.0035/min

Voxtral Mini Transcribe Realtime 3

$0.008/min

Voxtral Small Transcribe 3

$0.0040/min

Voxtral Speech 3 (batch and realtime, identical API)

$13/1M chars

To run the complete stack on-premises or in a personal cloud, talk to our team. 

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