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Speech to text · Mistral AI

Run Voxtral Small in the EU for transcription and audio understanding

Voxtral Small is Mistral AI's open speech model: it transcribes audio, answers questions about recordings and summarises them, while keeping the text skills of Mistral Small. On inference.eu you call it through an OpenAI-compatible API, and your recordings are processed in EU data centres and never used for training.

  1. 0124B
  2. 02EU data centres
  3. 03Apache 2.0

What Voxtral Small is

Voxtral Small 1.0, published as Voxtral-Small-24B-2507 in July 2025, is a 24-billion-parameter model from Mistral AI that adds audio input to the Mistral Small 3 language model. It can run in a dedicated transcription mode, or take audio and text together and answer questions, summarise or follow spoken instructions.

It has a 32K-token context, which Mistral says covers up to about 30 minutes of audio for transcription and 40 minutes for understanding. It detects the spoken language automatically and is strongest in English, Spanish, French, Portuguese, Hindi, German, Dutch and Italian. The weights are released under Apache 2.0.

What it does well, and where it falls short

Voxtral's advantage over a pure transcription model is that it understands what it hears. You can ask it for a summary of a call, the action items from a meeting or the answer to a question asked in a voice note, in a single request and without a separate language model. It can also trigger function calls directly from spoken requests.

It is a large model for transcription alone, so for high-volume, plain speech to text a smaller dedicated model such as Whisper Large V3 Turbo can be more efficient. Recordings longer than about 30 to 40 minutes need to be split. Mistral notes that system prompts are not yet supported, so put instructions in the user message.

Calling Voxtral Small through the API

inference.eu uses the OpenAI request format. For plain transcription, send the audio file to the OpenAI-style transcription endpoint with the model set to voxtral-small-24b, exactly as you would with OpenAI's speech models after changing the base URL and key.

To ask questions about a recording, send the audio as an input_audio content part in a chat message together with your text question. Several audio clips and several turns in one conversation are supported. Mistral recommends temperature 0 for transcription and around 0.2 for understanding tasks. Tool definitions work as with any chat model.

Recordings processed in the EU

Voice recordings often contain names, health details or customer data, and a voice can itself be personal data. With Voxtral Small on inference.eu, audio and transcripts are processed in data centres in the European Union, used only to produce your result and never used to train any model.

Every customer receives a data processing agreement under Article 28 of the GDPR and our list of subprocessors, so you can document how recordings are handled. Billing is in euros. Voxtral Small comes from a French lab and is licensed under Apache 2.0, which allows commercial use without user limits. You remain responsible for informing callers that they are recorded.

voxtral-small-24b · Python
import os
from openai import OpenAI

client = OpenAI(base_url="https://api.inference.eu/v1", api_key=os.environ["INFERENCE_EU_API_KEY"])

with open("meeting.mp3", "rb") as audio:
    transcript = client.audio.transcriptions.create(model="voxtral-small-24b", file=audio)
print(transcript.text)

What teams use it for

  • 1

    Meeting and call summaries

    Turn recorded meetings or support calls into a summary with decisions and action items in one request.

  • 2

    Voice notes into tasks

    Let field staff record a voice note and have it transcribed, understood and turned into a ticket or a function call.

  • 3

    Multilingual transcription

    Transcribe interviews and calls in English, French, German, Spanish, Italian, Dutch or Portuguese with automatic language detection.

Voxtral Small 24B: common questions

The questions buyers, developers and legal teams ask us most. Something missing? Ask us directly.

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