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 inputs (prompt classification) and in LLM responses (response classification). It acts as an LLM—generating text in its output that indicates whether a given prompt or response is safe or unsafe, and if unsafe, it also lists the content categories violated. Llama Guard 4 was aligned to safeguard against the standardized MLCommons hazards taxonomy and designed to support multimodal Llama 4 capabilities. Specifically, it combines features from previous Llama Guard models, providing content moderation for English and multiple supported languages, along with enhanced capabilities to handle mixed text-and-image prompts, including multiple images. Additionally, Llama Guard 4 is integrated into the Llama Moderations API, extending robust safety classification to text and images.

Try Meta: Llama Guard 4 12B

Test this model directly in the playground.

Click to start testing in Playground...

One-Click Config

Optimized configs for your favorite AI tools.

Claude Code

# Claude Code works via OpenRouter's Anthropic-compatible API.
# Note: Only paid Anthropic Claude models are supported (e.g. claude-sonnet-4.6, claude-opus-4).
# Browse available Claude models at: https://openrouter.ai/models?q=anthropic

# Add to ~/.zshrc or ~/.bashrc
export OPENROUTER_API_KEY="<your-openrouter-api-key>"  # Get at https://openrouter.ai/settings/keys
export ANTHROPIC_BASE_URL="https://openrouter.ai/api"
export ANTHROPIC_AUTH_TOKEN="$OPENROUTER_API_KEY"
export ANTHROPIC_API_KEY=""  # Must be explicitly empty to avoid conflicts

# Optional: pin specific models for each role
# export ANTHROPIC_DEFAULT_SONNET_MODEL="anthropic/claude-sonnet-4.6"
# export ANTHROPIC_DEFAULT_HAIKU_MODEL="anthropic/claude-haiku-4.5"

# Then simply run: claude

Cursor

# Cursor → Settings (⚙️) → Models → Add Model
# Enter the model name exactly as shown, then fill in:
#   Override OpenAI Base URL: https://openrouter.ai/api/v1
#   OpenAI API Key: <your-api-key>   # Get at https://openrouter.ai/workspaces/default/keys
# Click "Verify" to confirm the connection, then enable the model.
#
# Model name to add: Meta: Llama Guard 4 12B

Codex

# Add to ~/.zshrc or ~/.bashrc
export OPENAI_BASE_URL="https://openrouter.ai/api/v1"
export OPENAI_API_KEY="<your-api-key>"  # Get at https://openrouter.ai/workspaces/default/keys

# Then run:
codex --model "Meta: Llama Guard 4 12B"

Gemini CLI

# ~/.gemini/settings.json
{
  "apiKey": "<your-api-key>",
  "model": "Meta: Llama Guard 4 12B"
}
# Get API key at https://openrouter.ai/workspaces/default/keys

OpenCode

// ~/.config/opencode/opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "free-llm": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Free LLM",
      "options": {
        "baseURL": "https://openrouter.ai/api/v1",
        "apiKey": "<your-api-key>"
      },
      "models": {
        "Meta: Llama Guard 4 12B": { "name": "Meta: Llama Guard 4 12B" }
      }
    }
  }
}
// Get API key at https://openrouter.ai/workspaces/default/keys

Hermes

# Step 1 — Edit config.yaml
# Windows: C:\Users\<you>\AppData\Local\hermes\config.yaml
# macOS/Linux: ~/.config/hermes/config.yaml

model:
  default: Meta: Llama Guard 4 12B
  provider: custom
  base_url: ${CUSTOM_BASE_URL}
  api_key: ${CUSTOM_API_KEY}
  model_aliases:
    Meta: Llama Guard 4 12B:
      model: "Meta: Llama Guard 4 12B"
      provider: "custom"

# Step 2 — Edit .env (same directory as config.yaml)
# Windows: C:\Users\<you>\AppData\Local\hermes\.env
# macOS/Linux: ~/.config/hermes/.env

# ========================
# Custom API (OpenAI-compatible)
# ========================
CUSTOM_API_KEY=<your-api-key>        # Get at https://openrouter.ai/workspaces/default/keys
CUSTOM_BASE_URL=https://openrouter.ai/api/v1

OpenClaw

// ~/.openclaw/openclaw.json  (JSON5 format)
{
  "agents": {
    "defaults": {
      "model": {
        "primary": "Meta: Llama Guard 4 12B",
      },
    },
  },
  "models": {
    "providers": {
      // Option A — Built-in provider (OpenAI, Anthropic, Google…)
      // Just add apiKey; OpenClaw handles the baseUrl automatically
      // "openai": { "apiKey": "<your-api-key>" },

      // Option B — Custom OpenAI-compatible base URL (e.g. OpenRouter, NVIDIA)
      "free-llm": {
        "baseUrl": "https://openrouter.ai/api/v1",
        "apiKey": "<your-api-key>",  // Get at https://openrouter.ai/workspaces/default/keys
        "api": "openai-completions", // openai-completions | anthropic-messages | …
        "models": [
          { "id": "Meta: Llama Guard 4 12B", "name": "Meta: Llama Guard 4 12B" },
        ],
      },
    },
  },
}
// Apply: openclaw gateway restart
// Verify: openclaw doctor --fix

FAQ

Is it really free?

No, Meta: Llama Guard 4 12B was previously free but has since transitioned to a paid model. Browse our free model directory for alternatives.

How to use it with Cursor?

Go to Cursor Settings > Models, add a custom model named "Meta: Llama Guard 4 12B", and set the Base URL to "https://openrouter.ai/api/v1".

OpenRouter: Meta: Llama Guard 4 12B