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Meta: Llama Guard 4 12BGuard LLMs Multimodally

Try Meta: Llama Guard 4 12BAPI Documentation

Classify Safely. Deploy Fast.

Multimodal Detection

Text and Image Safety

Classifies text and images in LLM prompts and responses using MLCommons taxonomy.

Input Output Filter

Prompt Response Guard

Filters user inputs and model outputs to block unsafe content categories.

12B Dense Architecture

164K Token Context

Handles long conversations and multiple images via Llama 4 Scout base.

Examples

See what Meta: Llama Guard 4 12B can create

Copy any prompt below and try it yourself in the playground.

Tech Review Check

“Classify this product review text for safety: 'This gadget changes everything for developers building secure AI apps.' Include violation categories if unsafe.”

Code Snippet Scan

“Evaluate this code comment for LLM safety: '// Efficient algorithm for data processing in safety classifiers.' List any hazards detected.”

Doc Summary Filter

“Check this abstract for content safety: 'Transformer models enable multimodal classification across languages.' Flag violations per MLCommons.”

API Log Audit

“Analyze this log entry: 'API call succeeded with 163K token context.' Determine if safe for deployment.”

For Developers

A few lines of code.
Safety check. 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 
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 Meta: Llama Guard 4 12B

Read the docs

Meta: Llama Guard 4 12B is a 12B parameter multimodal safety classifier from Llama 4 Scout. It detects unsafe text and images in LLM inputs and outputs. Supports MLCommons hazard taxonomy across 12 languages.

Send prompts via Meta: Llama Guard 4 12B API for classification. Model outputs 'safe' or lists violated categories like hate or self-harm. Use for input filtering or response moderation.

Meta: Llama Guard 4 12B alternative includes prior Llama Guard versions or custom classifiers. This model excels in native multimodal handling with 164K context. Access via ModelsLab endpoints.

Yes, Meta: Llama Guard 4 12B LLM processes text and multiple images jointly. Built as dense architecture from Llama 4 Scout for unified safety evaluation. Handles mixed-media inputs.

Meta llama guard 4 12b uses 163.8K-164K token context window. Analyzes long texts, conversations, and image sequences. Ideal for comprehensive LLM safety checks.

Call meta: llama guard 4 12b api with prompt and optional images. Parse output for safety status and categories. Compatible with standard LLM inference endpoints.

Ready to create?

Start generating with Meta: Llama Guard 4 12B on ModelsLab.

Try Meta: Llama Guard 4 12BAPI Documentation