--- title: Mistral: Mixtral 8x22B Instruct | Text Generation | ModelsLab description: Build with Mistral: Mixtral 8x22B Instruct API by Mistralai. Text generation, chat, code, and reasoning. Pay-per-use. Free tier. url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/models/mistralai/mistralai-mixtral-8x22b-instruct/api.md canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/models/mistralai/mistralai-mixtral-8x22b-instruct/api.md type: product component: Playground/LLM/Index generated_at: 2026-05-13T10:35:55.842810Z --- Mistral: Mixtral 8x22B Instruct --- [LLMs.txt](https://modelslab-frontend-v2-927501783998.us-east4.run.app/models/open_router/mistralai-mixtral-8x22b-instruct/llms.txt) [.md](https://modelslab-frontend-v2-927501783998.us-east4.run.app/models/mistralai/mistralai-mixtral-8x22b-instruct.md) mistralai-mixtral-8x22b-instruct mistralai Closed Source Model $4.000000 / call Mistral: Mixtral 8x22B Instruct --- Choose a prompt below to get started or type your own message Explain quantum computing in simple terms Write a Python function to sort a list Create a marketing email for a SaaS product Compare REST vs GraphQL APIs Send ### Mistral: Mixtral 8x22B Instruct mistralai mistralai-mixtral-8x22b-instruct Copy model ID PricingInput $2.00 / 1M tokens Output $6.00 / 1M tokens API EndpointsOpenAI Compatible `https://modelslab.com/api/v7/llm/chat/completions`Endpoint Anthropic Compatible `https://modelslab.com/api/v7/llm/v1/messages`Messages `https://modelslab.com/api/v7/llm/v1/messages/count_tokens`Count Tokens `https://modelslab.com/api/v7/llm/v1/models`Models Use with Claude Code cURL Example ParametersSystem MessageYou are a helpful AI assistant specialized in providing accurate and detailed responses. 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[Microsoft: Phi 4 Closed Source Model](https://modelslab-frontend-v2-927501783998.us-east4.run.app/models/open_router/microsoft-phi-4) About Mistral: Mixtral 8x22B Instruct --- Mistral's official instruct fine-tuned version of \[Mixtral 8x22B\](/models/mistralai/mixtral-8x22b). It uses 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. Its strengths include: - strong math, coding,... ### Technical Specifications Model IDmistralai-mixtral-8x22b-instructCategoryLLM ModelsTaskText GenerationPrice$4.000000 per million tokensAddedFebruary 20, 2026 ### Key Features - Chat completion and multi-turn conversation API - Streaming response with token-by-token output - Function calling and tool use support - System prompts and role-based messaging - JSON mode and structured output ### Quick Start Integrate Mistral: Mixtral 8x22B Instruct into your application with a single API call. Get your API key from the [pricing page](https://modelslab-frontend-v2-927501783998.us-east4.run.app/pricing) to get started. PythonJavaScriptcURLPHP ``` import requests import json url = "https://modelslab.com/api/v7/llm/chat/completions" headers = { "Content-Type": "application/json" } data = { "model_id": "mistralai-mixtral-8x22b-instruct", "messages": [ { "role": "user", "content": "Hello!" } ], "max_tokens": 1000, "key": "YOUR_API_KEY" } try: response = requests.post(url, headers=headers, json=data) response.raise_for_status() # Raises an HTTPError for bad responses (4XX or 5XX) result = response.json() print("API Response:") print(json.dumps(result, indent=2)) except requests.exceptions.HTTPError as http_err: print(f"HTTP error occurred: {http_err} - {response.text}") except Exception as err: print(f"Other error occurred: {err}") ``` View the [full API documentation](https://modelslab-frontend-v2-927501783998.us-east4.run.app/models/mistralai/mistralai-mixtral-8x22b-instruct/api) for SDKs, code examples in Python, JavaScript, and more. ### Pricing Mistral: Mixtral 8x22B Instruct API costs $4.000000 per million tokens. Pay only for what you use with no minimum commitments. [View pricing plans](https://modelslab-frontend-v2-927501783998.us-east4.run.app/pricing) ### Use Cases - AI chatbots and virtual assistants - Code generation and developer tools - Content writing and copywriting automation - Data analysis, summarization, and extraction [Learn more about Mistral: Mixtral 8x22B Instruct](https://modelslab-frontend-v2-927501783998.us-east4.run.app/mistral-mixtral-8x22b-instruct) [Browse LLM Models](https://modelslab-frontend-v2-927501783998.us-east4.run.app/models?feature=llmaster) [More from Mistralai](https://modelslab-frontend-v2-927501783998.us-east4.run.app/models/open_router) [View Pricing](https://modelslab-frontend-v2-927501783998.us-east4.run.app/pricing) Mistral: Mixtral 8x22B Instruct FAQ --- ### What is Mistral: Mixtral 8x22B Instruct? Mistral's official instruct fine-tuned version of \[Mixtral 8x22B\](/models/mistralai/mixtral-8x22b). It uses 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. Its strengths include: - strong math, coding,... ### How do I use the Mistral: Mixtral 8x22B Instruct API? You can integrate Mistral: Mixtral 8x22B Instruct into your application with a single API call. Sign up on ModelsLab to get your API key, then use the model ID "mistralai-mixtral-8x22b-instruct" in your API requests. We provide SDKs for Python, JavaScript, and cURL examples in the API documentation. ### How much does Mistral: Mixtral 8x22B Instruct cost? Mistral: Mixtral 8x22B Instruct costs $4.000000 per million tokens. ModelsLab uses pay-per-use pricing with no minimum commitments. A free tier is available to get started. ### What is the Mistral: Mixtral 8x22B Instruct model ID? The model ID for Mistral: Mixtral 8x22B Instruct is "mistralai-mixtral-8x22b-instruct". Use this ID in your API requests to specify this model. ### Does Mistral: Mixtral 8x22B Instruct have a free tier? Yes, ModelsLab offers a free tier that lets you try Mistral: Mixtral 8x22B Instruct and other AI models. Sign up to get free API credits and start building immediately. --- *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 - 2026-05-13*