Mistral AI: Mixtral 8x7B Instruct

This model is no longer available.

Add AI to your application with Puter.js.

Explore Other Models

Model Card

Mixtral 8x7B is a sparse MoE model with 45B total / 13B active parameters using 8 experts per layer. It outperforms Llama 2 70B and GPT-3.5 while running 6x faster, mastering English, French, German, Spanish, and Italian.

Context Window 33K

tokens

Max Output 16K

tokens

Input Cost $0.54

per million tokens

Output Cost $0.54

per million tokens

Release Date Dec 11, 2023

 

Code Example

Add AI to your app with the Puter.js AI API — no API keys or setup required.

// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms").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").then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

More AI Models From Mistral AI

Find other Mistral AI models →

Chat

Mistral Medium 3.5

Mistral Medium 3.5 is a dense 128-billion-parameter multimodal model from Mistral AI that unifies instruction-following, reasoning, and coding into a single set of weights. It features a 256k-token context window, native function calling, structured JSON output, and vision capabilities via a custom-trained encoder that handles variable image sizes. A per-request reasoning_effort parameter lets you toggle between fast responses and deeper chain-of-thought processing, making the same model suitable for quick chat replies and complex agentic workflows. On benchmarks, it scores 77.6% on SWE-Bench Verified and 91.4% on τ³-Telecom. It replaces Mistral's previous Medium 3.1, Magistral, and Devstral 2 models. Priced at $1.50 per million input tokens and $7.50 per million output tokens, it's a strong fit for developers building tool-calling agents, long-horizon coding tasks, and multi-step automation pipelines.

 Chat

Mistral 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.

 Chat

Ministral 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

How do I use Mixtral 8x7B Instruct?

You can access Mixtral 8x7B 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 8x7B Instruct free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Mixtral 8x7B 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 8x7B Instruct?
Mixtral 8x7B Instruct costs $0.54 per 1M input tokens and $0.54 per 1M output tokens.
Price per 1M tokens
Input$0.54
Output$0.54
Who created Mixtral 8x7B Instruct?

Mixtral 8x7B Instruct was created by Mistral AI and released on Dec 11, 2023.

What is the context window of Mixtral 8x7B Instruct?

Mixtral 8x7B Instruct supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.

What is the max output length of Mixtral 8x7B Instruct?

Mixtral 8x7B Instruct can generate up to 16K tokens in a single response.

How does Mixtral 8x7B Instruct perform on benchmarks?

Mixtral 8x7B Instruct scores 7.7 on the Artificial Analysis Intelligence Index, outperforming 4% of tracked models.

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

Yes — the Mixtral 8x7B 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 AI to your application without worrying about API keys or setup.

Explore Models View Tutorials