Mistral AI: Mistral Medium 3
mistralai/mistral-medium-3
Access Mistral Medium 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-medium-3"
}).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-medium-3"
}).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-medium-3",
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-medium-3",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Mistral Medium 3 delivers frontier performance at $0.4/$2 per million tokens, performing at 90%+ of Claude Sonnet 3.7 across benchmarks. It's deployable on 4+ GPUs and surpasses Llama 4 Maverick and Cohere Command A.
Context Window 131K
tokens
Max Output N/A
tokens
Input Cost $0.4
per million tokens
Output Cost $2
per million tokens
Release Date May 7, 2025
Output Speed 56
tokens / sec
Latency 0.46s
time to first token
Model Playground
Try Mistral Medium 3 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Mistral Medium 3 performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 57.8% |
| Humanity's Last Exam Cross-domain reasoning | 4.3% |
| LiveCodeBench Recent coding problems | 40.0% |
| SciCode Scientific programming | 33.1% |
| MATH-500 Competition math | 90.7% |
| AIME 2024 Advanced math exam | 44.0% |
| AIME 2025 Advanced math exam | 30.3% |
| IFBench Instruction following | 39.3% |
| LCR Long-context reasoning | 28.0% |
| Terminal-Bench Hard Agentic terminal tasks | 3.8% |
| τ²-Bench Tool use / agents | 24.3% |
Scores sourced from Artificial Analysis.
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Frequently Asked Questions
You can access Mistral Medium 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.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Mistral Medium 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.
| Price per 1M tokens | |
|---|---|
| Input | $0.4 |
| Output | $2 |
Mistral Medium 3 was created by Mistral AI and released on May 7, 2025.
Mistral Medium 3 supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.
Yes — the Mistral Medium 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 Medium 3 to your app without worrying about API keys or setup.
Read the Docs View Tutorials