--- title: Mixtral 8x7B Instruct — Powerful LLM | ModelsLab description: Access Mistral: Mixtral 8x7B Instruct API for fast inference and strong instruction following. Generate text, code, and summaries now. url: https://modelslab.com/mistral-mixtral-8x7b-instruct canonical: https://modelslab.com/mistral-mixtral-8x7b-instruct type: website component: Seo/ModelPage generated_at: 2026-04-25T17:08:52.835293Z --- Available now on ModelsLab · Language Model Mistral: Mixtral 8x7B Instruct Mixtral Power, Dense Speed --- [Try Mistral: Mixtral 8x7B Instruct](/models/open_router/mistralai-mixtral-8x7b-instruct) [API Documentation](https://docs.modelslab.com) Run Mixtral Efficiently --- Sparse MoE ### 46B Params, 12.9B Active Uses two of eight experts per token for 6x faster inference than Llama 2 70B. Instruction Tuned ### Precise Task Following Fine-tuned with SFT and DPO; scores 8.30 on MT-Bench, matches GPT-3.5. Multilingual Support ### 32k Token Context Handles English, French, German, Italian, Spanish; excels in code and chat. Examples See what Mistral: Mixtral 8x7B Instruct can create --- Copy any prompt below and try it yourself in the [playground](/models/open_router/mistralai-mixtral-8x7b-instruct). Code Review “Review this Python function for bugs and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2)” Text Summary “Summarize the key benefits of sparse mixture of experts in LLMs, focusing on inference speed and parameter efficiency.” JSON Generation “Generate a JSON schema for a task management API with endpoints for creating, listing, and updating tasks.” Creative Story “Write a 200-word sci-fi story about an AI exploring abandoned space stations, in third-person narrative.” For Developers A few lines of code. Instruct Mixtral. 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 ```

import requests

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

``` FAQ Common questions about Mistral: Mixtral 8x7B Instruct --- [Read the docs ](https://docs.modelslab.com) ### What is Mistral: Mixtral 8x7B Instruct? Sparse MoE LLM with 46.7B total parameters, activates 12.9B per token. Outperforms Llama 2 70B on benchmarks with 6x faster inference. Instruction-tuned for chat and tasks. ### How does Mistral: Mixtral 8x7B Instruct API work? Send formatted prompts via API with user/assistant roles. Supports 32k context. Router selects two experts per token for efficient processing. ### Is Mistral: Mixtral 8x7B Instruct model multilingual? Supports English, French, German, Italian, Spanish. Handles code generation well. Context up to 32k tokens. ### What makes mistral mixtral 8x7b instruct alternative strong? Apache 2.0 license, open weights. Beats GPT-3.5 on many benchmarks. Cost-effective due to sparse activation. ### Does mistral: mixtral 8x7b instruct API have moderation? No built-in moderation mechanisms. Outputs depend on input prompts. Use strict formatting for best results. ### How to use mistral mixtral 8x7b instruct LLM for coding? Provide code snippets in user prompts. Fine-tuned for completion and generation. Matches top open models in coding benchmarks. Ready to create? --- Start generating with Mistral: Mixtral 8x7B Instruct on ModelsLab. [Try Mistral: Mixtral 8x7B Instruct](/models/open_router/mistralai-mixtral-8x7b-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 - 2026-04-25*