Meta Llama Llama Guard 4 12B, developed by Meta, features 12B parameters and 164k-token context window. 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. Available at $0.18/1M tokens.
Visit Meta: Llama Guard 4 12BAI-Powered
Leverages advanced AI technology to deliver cutting-edge capabilities and results.
Fast & Efficient
Optimized performance ensures quick results without compromising on quality.
Purpose-Built
Specifically designed for llms tasks and workflows.
Meta Llama Model Timeline
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Specifications
AI Evaluation
A versatile multimodal model handling both text and visual inputs. Strong choice for applications requiring cross-modal understanding and analysis.
Pros
- Competitive pricing ($0.18/1M)
- 164k token context window
- Multi-modal input support
- Optimized for RAG workflows
Cons
- API integration required
- May need prompt tuning
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