Mistral AI

Mistral AI: Mistral Small 3

mistralai/mistral-small-24b-instruct-2501

Access Mistral Small 3 from Mistral AI using Puter.js AI API.

Get Started 
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms", {
    model: "mistralai/mistral-small-24b-instruct-2501"
}).then(response => {
    document.body.innerHTML = response.message.content;
});

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms", {
            model: "mistralai/mistral-small-24b-instruct-2501"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

# pip install openai
from openai import OpenAI

client = OpenAI(
    base_url="https://api.puter.com/puterai/openai/v1/",
    api_key="YOUR_PUTER_AUTH_TOKEN",
)

response = client.chat.completions.create(
    model="mistralai/mistral-small-24b-instruct-2501",
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms"}
    ],
)

print(response.choices[0].message.content)

curl https://api.puter.com/puterai/openai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
  -d '{
    "model": "mistralai/mistral-small-24b-instruct-2501",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Model Card

Mistral Small 3 is a 24B parameter latency-optimized model achieving ~81% MMLU accuracy at 150 tokens/second. It's designed for fast-response conversational agents and low-latency function calling under Apache 2.0.

Context Window 33K

tokens

Max Output 16K

tokens

Input Cost $0.05

per million tokens

Output Cost $0.08

per million tokens

Release Date Jan 30, 2025

 

Output Speed 154

tokens / sec

Latency 0.46s

time to first token

Model Playground

Try Mistral Small 3 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat mistralai/mistral-small-24b-instruct-2501
Mistral AI
Chat with Mistral Small 3
Powered by Puter.js

Benchmarks

How Mistral Small 3 performs on standard evaluations.

Artificial Analysis
Intelligence Index
12.7
Better than 27% of tracked models
Artificial Analysis
Math Index
4.3
Better than 7% of tracked models
BenchmarkScore
GPQA Diamond Graduate-level science Q&A
46.2%
Humanity's Last Exam Cross-domain reasoning
4.1%
LiveCodeBench Recent coding problems
25.2%
SciCode Scientific programming
23.6%
MATH-500 Competition math
71.5%
AIME 2024 Advanced math exam
8.0%
AIME 2025 Advanced math exam
4.3%
IFBench Instruction following
26.4%
LCR Long-context reasoning
0.0%
τ²-Bench Tool use / agents
19.6%

Scores sourced from Artificial Analysis.

Find other Mistral AI models →

Chat

Mistral Small 4

Mistral Small 4 is a 119B-parameter open-source Mixture-of-Experts model (6B active per token) released under Apache 2.0, unifying instruction-following, reasoning, multimodal (text + image), and agentic coding into a single deployment. It features 128 experts, a 256k context window, and configurable reasoning effort that lets developers toggle between fast responses and deep step-by-step reasoning per request. Compared to its predecessor Mistral Small 3, it delivers 40% lower latency and 3x higher throughput while matching or surpassing GPT-OSS 120B on key benchmarks.

 Chat

Mistral Small Creative

Mistral Small Creative is a specialized Labs model variant optimized for creative content generation. It builds on the Mistral Small architecture with adjustments for more imaginative and varied outputs in writing tasks.

 Chat

Ministral 14B

Ministral 14B is part of the Ministral 3 family, a 14B parameter multimodal model with vision capabilities under Apache 2.0. It offers advanced capabilities for local deployment with instruct, base, and reasoning variants achieving 85% on AIME'25.

Frequently Asked Questions

How do I use Mistral Small 3?

You can access Mistral Small 3 by Mistral AI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.

Is Mistral Small 3 free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Mistral Small 3 to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.

What is the pricing for Mistral Small 3?
Pricing for Mistral Small 3 is based on the number of input and output tokens used per request.
Price per 1M tokens
Input$0.05
Output$0.08
Who created Mistral Small 3?

Mistral Small 3 was created by Mistral AI and released on Jan 30, 2025.

What is the context window of Mistral Small 3?

Mistral Small 3 supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.

What is the max output length of Mistral Small 3?

Mistral Small 3 can generate up to 16K tokens in a single response.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Mistral Small 3 API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

Get started with Puter.js

Add Mistral Small 3 to your app without worrying about API keys or setup.

Read the Docs View Tutorials