Mistral AI: Mistral Small 3.2

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Mistral Small 3.2 is a 24B parameter multimodal model with 128K context, improved instruction following, and reduced repetition. It handles text and images, runs on single RTX 4090 when quantized, and delivers 150 tokens/second under Apache 2.0.

Context Window 131K

tokens

Max Output 131K

tokens

Input Cost $0.1

per million tokens

Output Cost $0.3

per million tokens

Input text, image

modalities

Tool Use Yes

 

Knowledge Cutoff Mar 2025

 

Release Date Jun 20, 2025

 

Output Speed 124

tokens / sec

Latency 0.36s

time to first token

Code Example

Add AI to your app with the Puter.js AI API — no API keys or setup required.

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

puter.ai.chat("Explain quantum computing in simple terms").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").then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

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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?
Mistral Small 3.2 costs $0.1 per 1M input tokens and $0.3 per 1M output tokens.
Price per 1M tokens
Input$0.1
Output$0.3
Who created Mistral Small 3.2?

Mistral Small 3.2 was created by Mistral AI and released on Jun 20, 2025.

What is the context window of Mistral Small 3.2?

Mistral Small 3.2 supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 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.

What is the knowledge cutoff of Mistral Small 3.2?

Mistral Small 3.2 has a knowledge cutoff date of Mar 2025. This means the model was trained on data available up to that date.

What types of input can Mistral Small 3.2 process?

Mistral Small 3.2 accepts the following input types: text, image. It produces: text.

Does Mistral Small 3.2 support tool use (function calling)?

Yes, Mistral Small 3.2 supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.

How does Mistral Small 3.2 perform on benchmarks?

Mistral Small 3.2 scores 15.1 on the Artificial Analysis Intelligence Index, outperforming 35% of tracked models. On coding, it scores 13.3 (outperforms 31% of models). On math, it scores 27.0 (outperforms 28% of models).

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.

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