Mistral AI: Ministral 8B
mistralai/ministral-8b-2512
Access Ministral 8B 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/ministral-8b-2512"
}).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/ministral-8b-2512"
}).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/ministral-8b-2512",
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/ministral-8b-2512",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Ministral 8B is an 8B parameter multimodal model offering best-in-class text and vision capabilities for edge deployment. It supports single-GPU operation and provides an optimal balance of performance and efficiency under Apache 2.0.
Context Window 262K
tokens
Max Output 262K
tokens
Input Cost $0.1
per million tokens
Output Cost $0.1
per million tokens
Input image, text
modalities
Tool Use Yes
Knowledge Cutoff Dec 2025
Release Date Dec 16, 2025
Output Speed 101
tokens / sec
Latency 0.36s
time to first token
Model Playground
Try Ministral 8B instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Ministral 8B performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 47.1% |
| Humanity's Last Exam Cross-domain reasoning | 4.3% |
| LiveCodeBench Recent coding problems | 30.3% |
| SciCode Scientific programming | 20.8% |
| AIME 2025 Advanced math exam | 31.7% |
| IFBench Instruction following | 29.1% |
| LCR Long-context reasoning | 24.0% |
| Terminal-Bench Hard Agentic terminal tasks | 4.5% |
| τ²-Bench Tool use / agents | 26.6% |
Scores sourced from Artificial Analysis.
Find other Mistral AI models →
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ChatMistral Small 4
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.
ChatMinistral 14B
Ministral 14B is part of the Ministral 3 family, a 14B parameter multimodal model with vision capabilities under Apache 2.0. It offers advanced capabilities for local deployment with instruct, base, and reasoning variants achieving 85% on AIME'25.
Frequently Asked Questions
You can access Ministral 8B 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 Ministral 8B 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 | $0.1 |
| Output | $0.1 |
Ministral 8B was created by Mistral AI and released on Dec 16, 2025.
Ministral 8B supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.
Ministral 8B can generate up to 262K tokens in a single response.
Ministral 8B has a knowledge cutoff date of Dec 2025. This means the model was trained on data available up to that date.
Ministral 8B accepts the following input types: image, text. It produces: text.
Yes, Ministral 8B supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Ministral 8B scores 14.8 on the Artificial Analysis Intelligence Index, outperforming 34% of tracked models. On coding, it scores 10.0 (outperforms 22% of models). On math, it scores 31.7 (outperforms 32% of models).
Yes — the Ministral 8B 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 Ministral 8B to your app without worrying about API keys or setup.
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