---
title: Mixtral 8x22B Instruct — Powerful MoE LLM | ModelsLab
description: Access Mistral: Mixtral 8x22B Instruct API for 64K context, function calling, and top math/code performance. Deploy via LLM endpoint now.
url: https://modelslab.com/mistral-mixtral-8x22b-instruct
canonical: https://modelslab.com/mistral-mixtral-8x22b-instruct
type: website
component: Seo/ModelPage
generated_at: 2026-04-15T02:02:51.911372Z
---

Available now on ModelsLab · Language Model

Mistral: Mixtral 8x22B Instruct
Sparse Power, Dense Results
---

[Try Mistral: Mixtral 8x22B Instruct](/models/open_router/mistralai-mixtral-8x22b-instruct) [API Documentation](https://docs.modelslab.com)

Run Mixtral Efficiently
---

MoE Architecture

### 39B Active Parameters

Uses 39B active out of 141B total for fast inference on Mistral: Mixtral 8x22B Instruct API.

64K Context

### Long Document Recall

Processes 64K tokens for precise recall in Mistral: Mixtral 8x22B Instruct model tasks.

Native Function Calling

### Build Applications Fast

Supports function calling and constrained output in mistral mixtral 8x22b instruct.

Examples

See what Mistral: Mixtral 8x22B Instruct can create
---

Copy any prompt below and try it yourself in the [playground](/models/open_router/mistralai-mixtral-8x22b-instruct).

Code Generator

“Write a Python function to parse JSON logs, extract error counts by type, and output a summary table using pandas. Include error handling for malformed JSON.”

Math Solver

“Solve this system of equations step-by-step: 2x + 3y = 8, 4x - y = 5. Explain each algebraic manipulation and verify the solution.”

Multilingual Summary

“Summarize this French technical article on renewable energy trends in English, highlighting key statistics and projections for 2030. Article text: \[insert article\].”

Function Caller

“You have tools: get\_weather(city), calculate\_distance(loc1, loc2). User asks: What's the distance from Paris to London and current weather in London? Call tools sequentially.”

For Developers

A few lines of code.
Instruct model. One call.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about Mistral: Mixtral 8x22B Instruct
---

[Read the docs ](https://docs.modelslab.com)

### What is Mistral: Mixtral 8x22B Instruct?

### How to access Mistral: Mixtral 8x22B Instruct API?

### What context length for mistral mixtral 8x22b instruct?

### Is Mistral: Mixtral 8x22B Instruct model good for coding?

### Best Mistral: Mixtral 8x22B Instruct alternative?

### mistral: mixtral 8x22b instruct API pricing?

Ready to create?
---

Start generating with Mistral: Mixtral 8x22B Instruct on ModelsLab.

[Try Mistral: Mixtral 8x22B Instruct](/models/open_router/mistralai-mixtral-8x22b-instruct) [API Documentation](https://docs.modelslab.com)

---

*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

---
*Generated by ModelsLab - 2026-04-15*