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Specifications
Specifications and pricing as served by Composite
Model ID
meta-llama/llama-guard-4-12b
Provider
DeepInfra
Context window
163,840 tokens
Accepts
image, text
Returns
text
Input price
$0.180 per million tokens
Output price
$0.180 per million tokens
Prompt caching
Not offered for this model
Moderated
No
Cost on a monthly plan
About 1.3 plan credits per typical call (8k in, 1k out)
Routing endpoints
2 (base plus 1 routing variant)
Use Meta: Llama Guard 4 12B in JanitorAI or SillyTavern
Make a Composite API key and type meta-llama/llama-guard-4-12b as the model name. JanitorAI takes the full URL https://composite.lucidity.sh/v1/chat/completions; SillyTavern, ChubAI, Agnai and RisuAI take https://composite.lucidity.sh/v1. It runs on credits, a plan, or your own provider key.
This model has not carried enough traffic on Composite yet to publish a success rate, a latency figure or a traffic rank. The numbers appear here once it has.
Routing variants
The same model behind 1 alternative endpoint. Call the id directly to pin a route; the base id above picks for you.
Route
Model ID
Provider
Price
cheapThink
meta-llama/llama-guard-4-12b:cheapThink
DeepInfra
$0.180 per million tokens input · $0.180 per million tokens output
Pricing
$0.180 per million tokens input · $0.180 per million tokens output
Credits pay the provider’s price plus 25%; cache hits cost less.
On a monthly plan, a typical call (8k tokens in, 1k out) uses about 1.3 plan credits, at the provider's own price.
Provider
DeepInfra
Roleplay fit
Llama models are a widely-supported open baseline, useful when you want predictable, well-documented behavior.
Context behavior
With a 163,840-token context window, it can hold a long-running roleplay or a full lorebook in memory without losing earlier plot details, so it suits multi-session campaigns and character cards with heavy backstory.
Cost for regular use
It is priced low enough for high-volume daily roleplay without the per-message cost adding up quickly.
From the provider
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...