All models

Meta: Llama Guard 4 12B

by Meta

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.

Avg Score

0.0%

0 answers

Avg Latency

0ms

0 runs

Pricing

$0.18

input

/

$0.18

output

per 1M tokens

Context

164K

tokens

Alternatives

Models with similar or better quality but different tradeoffs

No alternatives found

Run benchmarks on this model to discover alternatives

Other Models from Meta

Compare performance with other models from the same creator

Benchmark Performance

How this model performs across different benchmarks

No benchmark data available

Run benchmarks with this model to see performance breakdown

Price vs Performance

Compare cost efficiency across all models

Current model
Other models
X-axis uses log scale for better visualization of price range

Score Over Time

Performance trends across all benchmark runs

No score trend data

Score history will appear here after multiple runs

Benchmark Activity

Number of benchmark runs over time

No activity data

Activity will appear here after benchmark runs

Quickstart

Get started with this model using OpenRouter

View on OpenRouter
import { OpenRouter } from "@openrouter/sdk";

const openrouter = new OpenRouter({
  apiKey: "<OPENROUTER_API_KEY>"
});

const completion = await openrouter.chat.completions.create({
  model: "meta-llama/llama-guard-4-12b",
  messages: [
    {
      role: "user",
      content: "Hello!"
    }
  ]
});

console.log(completion.choices[0].message.content);

Get your API key at openrouter.ai/keys