Mistral AI

Mistral AI: Mixtral 8x22B Instruct

mistralai/mixtral-8x22b-instruct

Access Mixtral 8x22B Instruct 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/mixtral-8x22b-instruct"
}).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/mixtral-8x22b-instruct"
        }).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/mixtral-8x22b-instruct",
    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/mixtral-8x22b-instruct",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Model Card

Mixtral 8x22B is a sparse MoE model with 141B total / 39B active parameters, 64K context, and native function calling. It outperforms Llama 2 70B and matches GPT-3.5 while being cost-efficient under Apache 2.0.

Context Window 66K

tokens

Max Output N/A

tokens

Input Cost $2

per million tokens

Output Cost $6

per million tokens

Release Date Apr 17, 2024

 

Model Playground

Try Mixtral 8x22B Instruct instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

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Benchmarks

How Mixtral 8x22B Instruct performs on standard evaluations.

Artificial Analysis
Intelligence Index
9.8
Better than 15% of tracked models
BenchmarkScore
GPQA Diamond Graduate-level science Q&A
33.2%
Humanity's Last Exam Cross-domain reasoning
4.1%
LiveCodeBench Recent coding problems
14.8%
SciCode Scientific programming
18.8%
MATH-500 Competition math
54.5%
AIME 2024 Advanced math exam
0.0%

Scores sourced from Artificial Analysis.

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Frequently Asked Questions

How do I use Mixtral 8x22B Instruct?

You can access Mixtral 8x22B Instruct 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 Mixtral 8x22B Instruct free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Mixtral 8x22B Instruct 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 Mixtral 8x22B Instruct?
Pricing for Mixtral 8x22B Instruct is based on the number of input and output tokens used per request.
Price per 1M tokens
Input$2
Output$6
Who created Mixtral 8x22B Instruct?

Mixtral 8x22B Instruct was created by Mistral AI and released on Apr 17, 2024.

What is the context window of Mixtral 8x22B Instruct?

Mixtral 8x22B Instruct supports a context window of 66K tokens. For reference, that is roughly equivalent to 131 pages of text.

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

Yes — the Mixtral 8x22B Instruct 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 Mixtral 8x22B Instruct to your app without worrying about API keys or setup.

Read the Docs View Tutorials