Mistral AI: Mixtral 8x7B Instruct v0.1
mistral/mixtral-8x7b-instruct-v0.1
Access Mixtral 8x7B Instruct v0.1 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: "mistral/mixtral-8x7b-instruct-v0.1"
}).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: "mistral/mixtral-8x7b-instruct-v0.1"
}).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="mistral/mixtral-8x7b-instruct-v0.1",
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": "mistral/mixtral-8x7b-instruct-v0.1",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Mixtral 8x7B Instruct v0.1 is a sparse mixture-of-experts chat model from Mistral AI, released in December 2023 as the instruction-tuned version of the base Mixtral 8x7B model.
It combines 8 feedforward expert blocks of 7B parameters each into one network, for 46.7 billion total parameters, of which a router activates about 12.9 billion per token. This gives it response quality closer to a much larger dense model while running with roughly 6x faster inference than Llama 2 70B.
Mistral reports it matches or outperforms GPT-3.5 on most standard benchmarks, scoring 8.30 on MT-Bench versus GPT-3.5's 8.32, and outperforms Llama 2 70B on most benchmarks tested, including a 70.6% MMLU score. It handles English, French, German, Spanish, and Italian.
With a 32K context window and Apache 2.0 licensing, it's a low-cost option for general chat and multilingual tasks that don't need a full 70B-class dense model.
Context Window 33K
tokens
Max Output 33K
tokens
Input Cost $0
per million tokens
Output Cost $0
per million tokens
Release Date N/A
Model Playground
Try Mixtral 8x7B Instruct v0.1 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
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ChatMistral Small Creative
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Frequently Asked Questions
You can access Mixtral 8x7B Instruct v0.1 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 Mixtral 8x7B Instruct v0.1 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 |
| Output | $0 |
Mixtral 8x7B Instruct v0.1 supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.
Mixtral 8x7B Instruct v0.1 can generate up to 33K tokens in a single response.
Yes — the Mixtral 8x7B Instruct v0.1 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 8x7B Instruct v0.1 to your app without worrying about API keys or setup.
Read the Docs View Tutorials