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LLama Guard 4

by Meta

AI Model
Low Confidence

Llama Guard 4 is a natively multimodal safety classifier with 12 billion parameters trained jointly on text and multiple images. It is a dense architecture pruned from the Llama 4 Scout pre-trained model and 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). Llama Guard 4 itself acts as an LLM: it generates 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 within a single safety classifier. Specifically, it combines the capabilities of the previous Llama Guard 3-8B and Llama Guard 3-11B-vision models by supporting English and multilingual text prompts (on the languages supported by Llama Guard 3) as well as mixed text-and-image prompts for image understanding. Unlike Llama Guard 3-11B-vision, Llama Guard 4 now supports safety classification when multiple images are given in the prompt as input. Llama Guard 4 is also integrated into the Llama Moderations API for text and images.

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Transparency Score

Weighted across four pillars · updated January 25, 2026

Overall grade
42% weighted
ABCDF
Model
—
Not yet assessed
Infrastructure
—
Not yet assessed

Vendor Information

Complete information about the vendor/provider of this AI application

MetaView all products →
Meta Platforms, Inc.(Trading as: Meta)
Contact Information
about.meta.com
+1-650-543-4800
Registered Address
1 Meta Way, Menlo Park, CA, 94025

EU AI Act Provider Information

Verification Status:
Partially Verified
(Last verified: August 5, 2026)
Meta Platforms, Inc.(Trading as: Meta)
1 Meta Way, Menlo Park, CA, 94025
+1-650-543-4800
Meta EMEA
Merrion Road, Dublin, IE
Compliance Documents
CE Marking: Not Applicable

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Added: January 22, 2026
Updated: January 25, 2026

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