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meta-llama/llama-guard-4-12bCatalogue: Indexed in the reference catalogue; nothing on this deployment answers as this model yet.
Published by the vendor; the platform bills at the target's declared price.
Meta meta-llama/llama-guard-4-12b
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...
Llama Guard 4 12B earns a request when it needs image input, running on your own hardware; a short, general request would go to Nemotron 3.5 Super VL (free) instead - free per million input tokens against $0.18 here; and the hardest requests, where the quality floor rules it out, to Claude Opus 5.5 (batch). Your rules decide the floor; the trace shows the comparison for every request.
Lower input price and an intelligence index within 5 points (this model has no published index).
Nothing on this deployment answers as this model yet. Connect your own provider under Model providers, or add a target to your catalogue - the router picks it up without retraining.
# targets.yaml - declare a target that runs Llama Guard 4 12B
targets:
- id: llama-guard-4-12b
kind: llm
name: Llama Guard 4 12B
metadata:
model: meta-llama/llama-guard-4-12b # links the target to this catalogue entry
capabilities:
domains: [general]
supports_tools: false
context_window: 163840
cost:
usd_per_1k_tokens: 0.000180Input list price per million tokens; Llama Guard 4 12B is the 6th cheapest of 8 listed.
Other models by the same vendor in the catalogue.
Photo: RDNE Stock project
A higher intelligence index, best first, with the price it comes at.
The catalogue prints input and output prices and what three typical monthly workloads cost on each.