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%

13 answers

Avg Latency

513ms

9 runs

Pricing

$0.18

input

$0.18

output

per 1M tokens

Context

164K

tokens

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Other Models from Meta

Compare performance with other models from the same creator

Model	Score	Latency	Cost/1M
Meta: Llama 4 Maverick	69.1%	4.7s	$0.38
Meta: Llama 4 Scout	66.0%	6.8s	$0.19
Meta: Llama 3.3 70B Instruct	60.6%	21.0s	Free
Meta: Llama 3.3 70B Instruct	56.8%	20.9s	$0.21
Meta: Llama 3.1 405B Instruct	54.1%	48.9s	$3.50
Meta: Llama 3.1 70B Instruct	44.6%	14.5s	$0.40
Meta: Llama 3 70B Instruct	40.0%	20.1s	$0.63
Meta: Llama 3.2 3B Instruct	37.1%	31.7s	$0.02
Meta: Llama 3.2 1B Instruct	30.2%	31.9s	$0.11
Meta: Llama 3.1 8B Instruct	30.0%	32.2s	$0.03
Meta: Llama 3 8B Instruct	25.0%	8.8s	$0.04
Meta: Llama 3.2 11B Vision Instruct	22.5%	44.8s	$0.05
Meta: LlamaGuard 2 8B	15.7%	708ms	$0.20
Meta: Llama 3.1 405B (base)	5.8%	36.1s	$4.00
Llama Guard 3 8B	3.1%	6.6s	$0.04
Meta: Llama 3.2 3B Instruct	0.0%	1.4s	Free
Meta: Llama 3.2 90B Vision Instruct	—	—	$0.38
Meta: Llama 3.1 405B Instruct	—	—	Free

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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);

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