Llama Guard 4 12B
VerifiedMeta's open multimodal model for safety classification of text and images.
About Llama Guard 4 12B
Llama Guard 4 12B builds on Meta's Llama architecture with added vision capabilities. It processes combined image and text data to assess safety risks. The open-weight availability allows researchers and developers to inspect and adapt the model freely.
Its strengths include large context handling for extended conversations and multimodal inputs. This enables thorough analysis of complex queries involving visuals and text. The design focuses on reliable detection of policy violations without requiring proprietary access.
Typical usage involves deployment as a guardrail layer in chat interfaces and content pipelines. Teams integrate it to review prompts, responses, and uploaded images for harmful content. It supports customization for specific safety policies in production environments.
Capabilities
How Llama Guard 4 12B compares
Llama Guard 4 12B (striped bar) vs other multimodal on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · Llama Guard 4 12B ranks #8 of 139
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Social Media Content Moderation
Detects violations in combined image and text posts across long conversation threads using multimodal safety classification.
AI System Prompt Guarding
Evaluates incoming prompts and generated responses for policy risks before they reach end users in production chat applications.
Enterprise Document Compliance Review
Analyzes lengthy multimodal documents for harmful content and regulatory violations with its extended context window.
Strengths & limitations
Strengths
- +Specialized safety focus
- +Supports image and text inputs
- +Large context window
- +Meta-developed moderation model
Limitations
- –Not a general-purpose LLM
- –Can produce over-refusals
- –Requires integration for use
Cost calculator
Estimate what Llama Guard 4 12B would cost for your usage.
Based on Llama Guard 4 12B's $0.18/1M input · $0.18/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "meta-llama/llama-guard-4-12b",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: meta-llama/llama-guard-4-12b
Editor's verdict
Llama Guard 4 12B is Meta's open-weight multimodal with a 164K-token context window.
At $0.18 per 1M output tokens, it is very cost-efficient for its class.
As an open-weight model you can self-host it or call it through a hosted API.
Best suited to specialized safety focus and supports image and text inputs.
Frequently asked questions
The model supports a context window of 163840 tokens for processing extended inputs.
User reviews
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