--- title: Meta: Llama 4 Scout API | Text Generation | ModelsLab description: Build with Meta: Llama 4 Scout API by Meta. Text generation, chat, code, and reasoning. Pay-per-use. Free tier. url: https://modelslab.com/models/meta/meta-llama-llama-4-scout.md canonical: https://modelslab.com/models/meta/meta-llama-llama-4-scout type: product component: Playground/LLM/Index generated_at: 2026-07-19T20:30:29.055831Z --- Meta: Llama 4 Scout --- [LLMs.txt](https://modelslab.com/models/meta/meta-llama-llama-4-scout/llms.txt) [.md](https://modelslab.com/models/meta/meta-llama-llama-4-scout.md) Meta: Llama 4 Scout --- 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 ### Meta: Llama 4 Scout meta meta-llama-llama-4-scout Copy model ID PricingInput $0.10 / 1M tokens Output $0.30 / 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. Temperature0.7 Max Tokens1000 Top P0.9 Frequency Penalty0 Presence Penalty0 Model Info Support Related Models --- Discover similar models you might be interested in [View all LLM Models](https://modelslab.com/models?feature=llmaster) [#### openai/gpt-oss-20b gpt-oss-20b From $0.08/M tokens](https://modelslab.com/models/openai/gpt-oss-20b) [#### deepseek/DeepSeek: DeepSeek V4 Pro deepseek-deepseek-v4-pro From $0.65/M tokens](https://modelslab.com/models/deepseek/deepseek-deepseek-v4-pro) [#### google/Google: Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) google-gemini-3.1-flash-lite-image From $0.88/M tokens](https://modelslab.com/models/google/google-gemini-3.1-flash-lite-image) [#### mistralai/Mistral: Mixtral 8x22B Instruct mistralai-mixtral-8x22b-instruct From $4.00/M tokens](https://modelslab.com/models/mistralai/mistralai-mixtral-8x22b-instruct) [#### qwen/Qwen: Qwen3.6 Flash qwen-qwen3.6-flash From $0.66/M tokens](https://modelslab.com/models/qwen/qwen-qwen3.6-flash) [#### x-ai/xAI: Grok 4.20 Multi-Agent x-ai-grok-4.20-multi-agent From $1.88/M tokens](https://modelslab.com/models/x-ai/x-ai-grok-4.20-multi-agent) [#### z-ai/Z.ai: GLM 4.7 z-ai-glm-4.7 From $1.07/M tokens](https://modelslab.com/models/z-ai/z-ai-glm-4.7) [#### qwen/Qwen: Qwen3 Max qwen-qwen3-max From $2.34/M tokens](https://modelslab.com/models/qwen/qwen-qwen3-max) [#### openai/GPT-5.1-Codex-Max gpt-5.1-codex-max From $5.63/M tokens](https://modelslab.com/models/openai/gpt-5.1-codex-max) [#### google/Gemma 3N E4B Instruct google-gemma-3n-E4B-it From $0.09/M tokens](https://modelslab.com/models/google/google-gemma-3n-E4B-it) [#### perplexity/R1 1776 perplexity-ai-r1-1776 From $8.40/M tokens](https://modelslab.com/models/perplexity/perplexity-ai-r1-1776) [#### byteplus/Seed 1.8 seed-1.8 From $3.00/M tokens](https://modelslab.com/models/byteplus/seed-1.8) [#### qwen/Qwen: Qwen3.6 27B qwen-qwen3.6-27b From $1.57/M tokens](https://modelslab.com/models/qwen/qwen-qwen3.6-27b) [#### qwen/Qwen: Qwen3.5-Flash qwen-qwen3.5-flash-02-23 From $0.16/M tokens](https://modelslab.com/models/qwen/qwen-qwen3.5-flash-02-23) [#### google/Google: Nano Banana Pro (Gemini 3 Pro Image) google-gemini-3-pro-image From $7.00/M tokens](https://modelslab.com/models/google/google-gemini-3-pro-image) [#### openai/OpenAI: GPT-4 Turbo openai-gpt-4-turbo From $20.00/M tokens](https://modelslab.com/models/openai/openai-gpt-4-turbo) [#### qwen/Qwen2.5 Coder 32B Instruct qwen-qwen-2.5-coder-32b-instruct From $0.83/M tokens](https://modelslab.com/models/qwen/qwen-qwen-2.5-coder-32b-instruct) [#### anthropic/Anthropic: Claude Sonnet 4.5 anthropic-claude-sonnet-4.5 From $9.00/M tokens](https://modelslab.com/models/anthropic/anthropic-claude-sonnet-4.5) Open Source Alternatives --- Explore open-source models that offer similar capabilities with full transparency and flexibility [View all open source models](https://modelslab.com/models?feature=llm&provider=open-source-models) [MU Popular](https://modelslab.com/models/modelslab/uncensored-chat)[ModelsLab](https://modelslab.com/models/modelslab) [Modelslab: Uncensored Chat Open Source Model](https://modelslab.com/models/modelslab/uncensored-chat) About Meta: Llama 4 Scout --- Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input... ### Technical Specifications Model IDmeta-llama-llama-4-scout CategoryLLM Models TaskText Generation Price$0.2 per million tokens AddedFebruary 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 Meta: Llama 4 Scout into your application with a single API call. Get your API key from the [pricing page](https://modelslab.com/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": "meta-llama-llama-4-scout", "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}") ``` ### Pricing Meta: Llama 4 Scout API costs $0.200000 per million tokens. Pay only for what you use with no minimum commitments. [View pricing plans](https://modelslab.com/pricing) ### Use Cases - AI chatbots and virtual assistants - Code generation and developer tools - Content writing and copywriting automation - Data analysis, summarization, and extraction [Browse LLM Models](https://modelslab.com/models?feature=llmaster) [More from Meta](https://modelslab.com/models/open_router) [View Pricing](https://modelslab.com/pricing) Meta: Llama 4 Scout FAQ --- ### What is Meta: Llama 4 Scout? Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input... ### How do I use the Meta: Llama 4 Scout API? You can integrate Meta: Llama 4 Scout into your application with a single API call. Sign up on ModelsLab to get your API key, then use the model ID "meta-llama-llama-4-scout" in your API requests. We provide SDKs for Python, JavaScript, and cURL examples in the API documentation. ### How much does Meta: Llama 4 Scout cost? Meta: Llama 4 Scout costs $0.200000 per million tokens. ModelsLab uses pay-per-use pricing with no minimum commitments. A free tier is available to get started. ### What is the Meta: Llama 4 Scout model ID? The model ID for Meta: Llama 4 Scout is "meta-llama-llama-4-scout". Use this ID in your API requests to specify this model. ### Does Meta: Llama 4 Scout have a free tier? Yes, ModelsLab offers a free tier that lets you try Meta: Llama 4 Scout 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 - 2026-07-20*