--- title: Meta: Llama Guard 4 12B API | Text Generation | ModelsLab description: 12B parameter multimodal LLM safety classifier for text/image content moderation in prompts/responses, 164K context window, MLCommons-aligned.[1][2][4] url: https://modelslab.com/models/meta/meta-llama-llama-guard-4-12b.md canonical: https://modelslab.com/models/meta/meta-llama-llama-guard-4-12b type: product component: Playground/LLM/Index generated_at: 2026-07-19T20:12:14.900503Z --- Meta: Llama Guard 4 12B --- [LLMs.txt](https://modelslab.com/models/meta/meta-llama-llama-guard-4-12b/llms.txt) [.md](https://modelslab.com/models/meta/meta-llama-llama-guard-4-12b.md) Meta: Llama Guard 4 12B --- 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 Guard 4 12B meta meta-llama-llama-guard-4-12b Copy model ID PricingInput $0.18 / 1M tokens Output $0.18 / 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/OpenAI: gpt-oss-120b openai-gpt-oss-120b From $0.10/M tokens](https://modelslab.com/models/openai/openai-gpt-oss-120b) [#### meta/Meta Llama 3.2 90B Vision Instruct Turbo meta-llama-Llama-3.2-90B-Vision-Instruct-Turbo From $1.44/M tokens](https://modelslab.com/models/meta/meta-llama-Llama-3.2-90B-Vision-Instruct-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) [#### 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) [#### pearl-ai/Pearl-ai Gemma-4-31B-it-pearl pearl-ai-gemma-4-31b-it From $0.57/M tokens](https://modelslab.com/models/pearl-ai/pearl-ai-gemma-4-31b-it) [#### amazon/Amazon: Nova 2 Lite amazon-nova-2-lite-v1 From $1.40/M tokens](https://modelslab.com/models/amazon/amazon-nova-2-lite-v1) [#### qwen/Qwen QwQ-32B Qwen-QwQ-32B From $1.20/M tokens](https://modelslab.com/models/qwen/Qwen-QwQ-32B) [#### qwen/Qwen: Qwen3 VL 30B A3B Thinking qwen-qwen3-vl-30b-a3b-thinking From $0.84/M tokens](https://modelslab.com/models/qwen/qwen-qwen3-vl-30b-a3b-thinking) [#### qwen/Qwen: Qwen3.6 Plus qwen-qwen3.6-plus From $1.14/M tokens](https://modelslab.com/models/qwen/qwen-qwen3.6-plus) [#### nvidia/NVIDIA: Nemotron 3 Nano 30B A3B nvidia-nemotron-3-nano-30b-a3b From $0.13/M tokens](https://modelslab.com/models/nvidia/nvidia-nemotron-3-nano-30b-a3b) [#### inclusionai/inclusionAI: Ling-2.6-1T inclusionai-ling-2.6-1t From $0.35/M tokens](https://modelslab.com/models/inclusionai/inclusionai-ling-2.6-1t) [#### google/Google: Gemini 2.5 Pro google-gemini-2.5-pro From $5.63/M tokens](https://modelslab.com/models/google/google-gemini-2.5-pro) [#### qwen/Qwen: Qwen2.5 7B Instruct qwen-qwen-2.5-7b-instruct From $0.07/M tokens](https://modelslab.com/models/qwen/qwen-qwen-2.5-7b-instruct) [#### anthropic/Anthropic: Claude Opus 4.1 anthropic-claude-opus-4.1 From $45.00/M tokens](https://modelslab.com/models/anthropic/anthropic-claude-opus-4.1) [#### qwen/Qwen2.5 72B Instruct Turbo Qwen-Qwen2.5-72B-Instruct-Turbo From $1.20/M tokens](https://modelslab.com/models/qwen/Qwen-Qwen2.5-72B-Instruct-Turbo) [#### openai/OpenAI: GPT-4o (2024-11-20) openai-gpt-4o-2024-11-20 From $6.25/M tokens](https://modelslab.com/models/openai/openai-gpt-4o-2024-11-20) [#### amazon/Amazon: Nova Pro 1.0 amazon-nova-pro-v1 From $2.00/M tokens](https://modelslab.com/models/amazon/amazon-nova-pro-v1) [#### google/Gemini 2.5 Flash gemini-2.5-flash From $1.40/M tokens](https://modelslab.com/models/google/gemini-2.5-flash) 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 Guard 4 12B --- Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM... ### Technical Specifications Model IDmeta-llama-llama-guard-4-12b CategoryLLM Models TaskText Generation Price$0.18 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 Guard 4 12B 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-guard-4-12b", "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 Guard 4 12B API costs $0.180000 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 [Learn more about Meta: Llama Guard 4 12B](https://modelslab.com/meta-llama-guard-4-12b) [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 Guard 4 12B FAQ --- ### What is Meta: Llama Guard 4 12B? Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM... ### How do I use the Meta: Llama Guard 4 12B API? You can integrate Meta: Llama Guard 4 12B 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-guard-4-12b" in your API requests. We provide SDKs for Python, JavaScript, and cURL examples in the API documentation. ### How much does Meta: Llama Guard 4 12B cost? Meta: Llama Guard 4 12B costs $0.180000 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 Guard 4 12B model ID? The model ID for Meta: Llama Guard 4 12B is "meta-llama-llama-guard-4-12b". Use this ID in your API requests to specify this model. ### Does Meta: Llama Guard 4 12B have a free tier? Yes, ModelsLab offers a free tier that lets you try Meta: Llama Guard 4 12B 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*