Does Voxtral Small 2507 support zero data retention?

Not by default. See the per-route data-handling section for each route's logging stance and retention window.

Where is Voxtral Small 2507 hosted?

Voxtral Small 2507 runs on crypto rails routes through the qynio gateway, with contractually enforced residency on supported providers.

Is Voxtral Small 2507 trained on prompts and outputs?

No. Every hosting route for Voxtral Small 2507 is configured so customer prompts and outputs are not used to train models by default.

Is a no-KYC deposit available for Voxtral Small 2507?

Yes. A no-KYC Data Processing Agreement is available on at least one route serving Voxtral Small 2507. Contact hello@qyn.io to receive it.

Voxtral Small 2507

by Mistral

Versions:Voxtral Small 2507Voxtral Small 2507

Voxtral Small 2507 is Mistral's audio-native instruct model, combining a 24B model for audio understanding with robust text processing inherited from Mistral Small 3.1. It is designed for multi-turn chat and agentic workflows, accepting both audio and text inputs for flexible, speech-driven applications. The model handles audio-to-text workflows within a 32k token context window, processing audio up to 30 minutes for transcription or 40 minutes for understanding, Q&A, and summarization without external ASR systems. Function calling directly from speech lets voice commands trigger backend APIs and workflows, unlocking voice-first agent architectures. With native multilingual support and automatic language detection across major languages including English, Spanish, French, Portuguese, Hindi, German, Dutch, and Italian, Voxtral Small works globally. Released under Apache 2.0, it is available both as an open-weight download and via API.

Open in playground Try in chat Compare

Key info

Input

Output

Features

Context window

33K

Max output

—

Input price

$0.10 /1M

Output price

$0.40 /1M

onchain settlement available
No training by default
no-KYC deposit available

Available routes

Voxtral Small 2507 runs on 1 route through the qynio gateway. Compare residency, zero retention, and training posture at a glance — full data-handling detail per route below.

Provider	Region	Zero data retention	Training	Input	Output
Mistral	EU	Not by default	No	$0.10	$0.40

Uptime and availability

Voxtral Small 2507 runs on a single route through the qynio gateway today, so its availability is that provider's availability.

100%route uptime, last 30 days

Single route, no failover target within this model.

Name a second model in the same request and the gateway tries it on retriable errors, so a busy hour never has to reach your users. .

Measured over the last 30 days from each provider's official status feed via StatusGator. Refreshed hourly. See uptime for every provider qynio monitors.

Data handling per route

Each route hosting Voxtral Small 2507 has its own privacy posture, residency, and no-KYC terms. Postures are maintained by qynio with a last-verification timestamp.

Mistral — France🇫🇷

Zero data retention is not on by default — abuse monitoring, 30-day retention. No training on customer data. EU; deposit available.

Zero data retention: Not by default — abuse monitoring, 30-day retention. Derived from the logging and moderation facts.
Training: No training on customer data.
Logging: Abuse monitoring (30-day retention)
Moderation: Not established
Caching: Not established
Subprocessor access: Not established
no-KYC deposit: deposit available
Transfer mechanism: Not applicable — data stays in EU

Get started

Call Voxtral Small 2507 through the qynio gateway with one API key. Let your coding agent set it up, or call it directly — qynio is drop-in compatible with the OpenAI, Anthropic, and Google AI SDKs.

Set it up with your agent

Copy this and paste it into a coding agent like Claude Code, Cursor or Codex and it'll wire up qynio for you.

Or call it directly

1import OpenAI from "openai";
2
3const client = new OpenAI({
4  apiKey: process.env.QYN_API_KEY,
5  baseURL: "https://api.qyn.io/v3/compat",
6});
7
8const completion = await client.chat.completions.create({
9  model: "mistral/voxtral-small-2507",
10  messages: [{ role: "user", content: "Hello" }],
11});
12console.log(completion.choices[0].message.content);