Mistral AI

Mistral AI: Mistral Small 4

mistralai/mistral-small-2603

Access Mistral Small 4 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-2603"
}).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-2603"
        }).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-2603",
    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-2603",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Model Card

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.

Context Window 262K

tokens

Max Output 256K

tokens

Input Cost $0.15

per million tokens

Output Cost $0.6

per million tokens

Release Date Mar 16, 2026

 

Output Speed 157

tokens / sec

Latency 0.60s

time to first token

Model Playground

Try Mistral Small 4 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat mistralai/mistral-small-2603
Mistral AI
Chat with Mistral Small 4
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Benchmarks

How Mistral Small 4 performs on standard evaluations.

Artificial Analysis
Intelligence Index
27.8
Better than 67% of tracked models
Artificial Analysis
Coding Index
24.3
Better than 61% of tracked models
BenchmarkScore
GPQA Diamond Graduate-level science Q&A
76.9%
Humanity's Last Exam Cross-domain reasoning
9.5%
SciCode Scientific programming
38.0%
IFBench Instruction following
48.2%
LCR Long-context reasoning
44.7%
Terminal-Bench Hard Agentic terminal tasks
17.4%
τ²-Bench Tool use / agents
41.2%

Scores sourced from Artificial Analysis.

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Frequently Asked Questions

How do I use Mistral Small 4?

You can access Mistral Small 4 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 4 free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Mistral Small 4 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 4?
Mistral Small 4 costs $0.15 per 1M input tokens and $0.6 per 1M output tokens.
Price per 1M tokens
Input$0.15
Output$0.6
Who created Mistral Small 4?

Mistral Small 4 was created by Mistral AI and released on Mar 16, 2026.

What is the context window of Mistral Small 4?

Mistral Small 4 supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.

What is the max output length of Mistral Small 4?

Mistral Small 4 can generate up to 256K tokens in a single response.

How does Mistral Small 4 perform on benchmarks?

Mistral Small 4 scores 27.8 on the Artificial Analysis Intelligence Index, outperforming 67% of tracked models. On coding, it scores 24.3 (outperforms 61% of models).

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

Yes — the Mistral Small 4 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 4 to your app without worrying about API keys or setup.

Read the Docs View Tutorials