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...
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Meta: Llama Guard 4 12B holds the #266 spot for context size out of 392 chat models in the CoreAI catalog — 164K tokens, roughly 122,880 words or 246 pages of text in a single conversation. On price, it is the #92 cheapest of 128 budget-tier models by input cost. It joined the catalog on 2025-04-30. It accepts image input alongside text.
Every model in this table is available on CoreAI — open the web app and run the same prompt through Meta: Llama Guard 4 12B and Meta: Llama 4 Maverick side by side to judge with your own eyes.
A typical question (about 1,000 tokens in, 500 out) runs $0.00027 on Meta: Llama Guard 4 12B's raw per-token rates; a heavy session with a 50K-token document costs about $0.010. On CoreAI you don't juggle these numbers — one subscription covers Meta: Llama Guard 4 12B and 300+ other models under a plan usage limit, with no API keys. See plans.
Meta: Llama Guard 4 12B handles 164K tokens of context — roughly 122,880 words, or about 246 pages of text in one conversation.
Meta: Llama Guard 4 12B's underlying rates are $0.18 per 1M input tokens and $0.18 per 1M output tokens. On CoreAI it is included in one subscription alongside 300+ models, so there is no per-token billing to manage.
Yes — Meta: Llama Guard 4 12B accepts image input, so you can attach screenshots, photos or diagrams and ask questions about them.
No — Meta: Llama Guard 4 12B answers directly without an extended reasoning phase, which usually means faster responses.
Open the CoreAI web app or the iOS/Android app, pick Meta: Llama Guard 4 12B in the model selector, and chat — no API key, no per-token billing. One subscription covers Meta: Llama Guard 4 12B and 300+ other models.
The closest alternatives on CoreAI are Meta: Llama 4 Maverick, IBM: Granite 4.1 8B, inclusionAI: Ling-2.6-flash — similar tier and capability. The fastest way to choose is running one prompt through them side by side in CoreAI's Compare view.
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