Mistral AI

Mistral AI: Mistral Saba

mistralai/mistral-saba

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

Model Card

Mistral Saba is a 24B parameter regional model trained for Arabic and South Asian languages including Tamil and Malayalam. It outperforms models 5x its size on Arabic benchmarks while providing culturally relevant responses.

Context Window 33K

tokens

Max Output N/A

tokens

Input Cost $0.2

per million tokens

Output Cost $0.6

per million tokens

Release Date Feb 17, 2025

 

Model Playground

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

Chat mistralai/mistral-saba
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Chat with Mistral Saba
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Benchmarks

How Mistral Saba performs on standard evaluations.

Artificial Analysis
Intelligence Index
12.1
Better than 23% of tracked models
BenchmarkScore
GPQA Diamond Graduate-level science Q&A
42.4%
Humanity's Last Exam Cross-domain reasoning
4.1%
SciCode Scientific programming
24.1%
MATH-500 Competition math
67.7%
AIME 2024 Advanced math exam
13.0%

Scores sourced from Artificial Analysis.

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Frequently Asked Questions

How do I use Mistral Saba?

You can access Mistral Saba 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 Saba free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Mistral Saba 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 Saba?
Pricing for Mistral Saba is based on the number of input and output tokens used per request.
Price per 1M tokens
Input$0.2
Output$0.6
Who created Mistral Saba?

Mistral Saba was created by Mistral AI and released on Feb 17, 2025.

What is the context window of Mistral Saba?

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

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

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

Read the Docs View Tutorials