Mistral AI

Mistral AI: Mistral Small 3.2

mistralai/mistral-small-3.2-24b-instruct

Access Mistral Small 3.2 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-3.2-24b-instruct"
}).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-3.2-24b-instruct"
        }).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-3.2-24b-instruct",
    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-3.2-24b-instruct",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Model Card

Mistral Small 3.2 improves on 3.1 with better instruction following (84.78% vs 82.75%), reduced infinite generations (1.29% vs 2.11%), and more robust function calling. It maintains the 24B/128K context architecture under Apache 2.0.

Context Window 128K

tokens

Max Output 131K

tokens

Input Cost $0.08

per million tokens

Output Cost $0.2

per million tokens

Release Date Jun 18, 2025

 

Output Speed 158

tokens / sec

Latency 0.32s

time to first token

Model Playground

Try Mistral Small 3.2 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat mistralai/mistral-small-3.2-24b-instruct
Mistral AI
Chat with Mistral Small 3.2
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Benchmarks

How Mistral Small 3.2 performs on standard evaluations.

Artificial Analysis
Intelligence Index
15.1
Better than 38% of tracked models
Artificial Analysis
Coding Index
13.3
Better than 34% of tracked models
Artificial Analysis
Math Index
27.0
Better than 28% of tracked models
BenchmarkScore
GPQA Diamond Graduate-level science Q&A
50.5%
Humanity's Last Exam Cross-domain reasoning
4.3%
LiveCodeBench Recent coding problems
27.5%
SciCode Scientific programming
26.4%
MATH-500 Competition math
88.3%
AIME 2024 Advanced math exam
32.3%
AIME 2025 Advanced math exam
27.0%
IFBench Instruction following
33.5%
LCR Long-context reasoning
17.3%
Terminal-Bench Hard Agentic terminal tasks
6.8%
τ²-Bench Tool use / agents
29.5%

Scores sourced from Artificial Analysis.

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Frequently Asked Questions

How do I use Mistral Small 3.2?

You can access Mistral Small 3.2 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 3.2 free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Mistral Small 3.2 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 3.2?
Pricing for Mistral Small 3.2 is based on the number of input and output tokens used per request.
Price per 1M tokens
Input$0.08
Output$0.2
Who created Mistral Small 3.2?

Mistral Small 3.2 was created by Mistral AI and released on Jun 18, 2025.

What is the context window of Mistral Small 3.2?

Mistral Small 3.2 supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.

What is the max output length of Mistral Small 3.2?

Mistral Small 3.2 can generate up to 131K tokens in a single response.

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

Yes — the Mistral Small 3.2 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 3.2 to your app without worrying about API keys or setup.

Read the Docs View Tutorials