What is Voxtral Small 24B 2507 API?
Voxtral Small 24B 2507 is available through AIMLAPI.
Technical Specifications
- Supported inputs: Image, Text
- Output: Text
- Context window: 32,000 tokens / Max output: —
- Endpoint: /chat/completions
Performance Benchmarks
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Voxtral Small 24B 2507 API Pricing
- Input: $0.13 / 1M tokens
- Output: $0.39 / 1M tokens
Where to Use Voxtral Small 24B 2507
Coding and code review
Generate, debug, and review code across languages, reading whole files or repos in a single prompt.
Agentic and multi-step workflows
Reliable tool-calling and instruction-following suit agent loops that plan, call tools, and iterate.
Complex reasoning
Extended reasoning improves reliability on multi-step math, logic, and technical analysis.
Long-document analysis
Summarize and extract from contracts, papers, and reports without aggressive chunking.
Code Sample
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Measured on the AI/ML API gateway across live traffic. Figures are medians unless stated. Last updated 2026-10-12.
Speech transcription is a documented use case for Voxtral Small 24B 2507, which is described as a speech-to-text model for high-accuracy transcription and voice understanding.
Translation is a documented use case, with the model said to excel at translating audio and handling multilingual audio processing.
Audio understanding is a documented use case, including analyzing spoken content and supporting voice understanding workflows.
Built-in Q&A and summarization from audio are documented use cases, including asking questions directly about audio content and generating structured summaries.
import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "mistralai/voxtral-small-24b-2507", "messages": [ { "role": "user", "content": "Hello!" } ] }, ) print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", { method: "POST", headers: { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ "model": "mistralai/voxtral-small-24b-2507", "messages": [ { "role": "user", "content": "Hello!" } ] }), }); console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"mistralai/voxtral-small-24b-2507","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Cached input |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Voxtral Small 24B 2507 This page | Reasoning + agents | |||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
Voxtral Small 24B 2507 has a 32,000 tokens context window.
Voxtral Small 24B 2507 takes image, text as input and returns text.
Use mistralai/voxtral-small-24b-2507 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Voxtral Small 24B 2507 is priced at input $0.13754 / 1M tokens, output $0.41262 / 1M tokens, cached input $0.013754 / 1M tokens.
Yes, Voxtral Small 24B 2507 can stream responses as they are generated.
Yes, Voxtral Small 24B 2507 accepts image input alongside text.
Voxtral Small 24B 2507 was built by Mistral AI.
Yes, it supports function calling, including parallel tool calls, as well as structured outputs and web search.