Audio
Mistral audio covers three jobs: turning speech into text, turning text into speech, and running both in live conversations. Voxtral 3 models transcribe recorded files and live streams, with speaker labels, timestamps, and custom vocabulary. They generate speech with preset or cloned voices, which you direct with emotion and pace tags. You can also send audio to a chat model to summarize or question a recording, and build voice agents that answer callers in real time.
This section is for developers who integrate audio through the API and SDKs, and for product teams who evaluate what Voxtral can do.
Not a developer? Dictate prompts and talk with Work in Voice mode, or analyze a recording by uploading it to a chat. with no code to write.
The audio docs cover Voxtral 3. If your code still calls Voxtral 2 models, Migrate from Voxtral 2 lists what to change.
Get started
1. Create an API key
Every request needs an API key from AI Studio.
- Select
Create new key, give the key a name, and set an expiration date. - Copy the key. It appears only once.
- Store the key in the
MISTRAL_API_KEYenvironment variable, where the examples read it:
export MISTRAL_API_KEY="your-api-key"For screenshots and every key option, see Activate Studio and generate an API key. If your organization manages keys centrally, see API keys in the Admin docs.
2. Install the SDK
The curl examples need no installation. For Python or TypeScript, install the Mistral SDK:
pip install "mistralai[realtime]"The realtime extra adds the WebSocket client for realtime transcription.
3. Run your first call
Send a recorded file and get its transcript back. Download the sample recording first, or fetch it from the command line:
curl -O https://docs.mistral.ai/audio/obama.mp3import os
from mistralai.client import Mistral
client = Mistral(api_key=os.environ["MISTRAL_API_KEY"])
with open("obama.mp3", "rb") as audio:
transcription = client.audio.transcriptions.complete(
model="voxtral-mini-transcribe-3",
file={"file_name": "obama.mp3", "content": audio},
)
print(transcription.text)This example runs on Voxtral Mini Transcribe 3. To check the full response and see what to try next, follow Quickstart: transcribe an audio file.
Meet the models
Voxtral 3 has five models: three turn speech into text, and two turn text into speech.
Speech to text
Voxtral Mini Transcribe 3
Transcription of recorded audio files.
Voxtral Mini Transcribe Realtime 3
Live transcription of audio streams, with configurable latency.
Voxtral Small Transcribe 3
Higher-quality transcription of recorded audio files.
Text to speech
Voxtral TTS 3
Speech generation from text, with preset voices and zero-shot voice cloning.
Voxtral TTS Realtime 3
Streaming speech generation for live conversations.
To choose, start from what you need to do:
| Model | Use it to | Key numbers |
|---|---|---|
Voxtral Mini Transcribe 3 (voxtral-mini-transcribe-3-0) | Transcribe recorded files, with speaker labels, segment timestamps, and custom vocabulary | 65,536-token context, shared by the audio and the vocabulary list |
Voxtral Mini Transcribe Realtime 3 (voxtral-mini-transcribe-realtime-3-0) | Transcribe live audio for captions and voice agents, with turn detection | Streaming delay from 80 to 1,200 ms, or 2,400 ms, set per session |
Voxtral Small Transcribe 3 (voxtral-small-transcribe-3-0) | Transcribe recorded files at higher quality | Transcription only at launch |
Voxtral TTS 3 (voxtral-mini-tts-3-0) | Generate speech from text with preset or cloned voices | 5 output formats, WAV at 24 kHz; 34 emotion tags and 2 pace tags |
Voxtral TTS Realtime 3 (voxtral-mini-tts-realtime-3-0) | Stream speech for live conversations |
To compare modes, options, and features in detail, see Speech to Text and Text to Speech.
Understand the concepts
Before you tune options or design a voice product, read how each part of the audio stack works and what each choice trades off.
What you can build
Pick the scenario closest to your product. Each guide combines several capabilities into one result and links to the article behind every step.