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Model reference · open weights

LlamaGuard

LLMs meta-llama Text gen 1 build Open, with conditions 3k dl/mo

LlamaGuard is an open-weight language model from Meta. LlamaGuard-7b (BF16) weighs 13.5 GB; the smallest configuration that runs it is RTX 4060 Ti 16 GB.

  • LlamaGuard is a 6.7B parameter text-generation model developed by Meta for classifying the safety of LLM inputs and responses.
  • It operates in English and is released under the llama2 license.
  • The model generates text indicating whether content is safe or unsafe and lists violating subcategories based on a provided taxonomy of harms.

Summary of the meta-llama/LlamaGuard-7b model card, 2026-10-03

Hugging Face ↗GitHub ↗Paper ↗

What it is

Released byMeta
Released2023-12-05
Parameters6.7B
VRAM13.5 GB for the weights

What it runs on

Memory and cards for LlamaGuard-7b (BF16)

13.5 GBweights, file size
762 MBruntime overhead, at least

How much memory each request adds isn't estimated yet for this architecture. The weights need at least the cards below, plus room for the context.

CardWeights alone
RTX 3060 12 GBdoes not fit
RTX 4060 Ti 16 GBtight
RTX 3090 24 GBfits
RTX 4090 24 GBfits
RTX 5090 32 GBfits
L40S 48 GBfits
A100 80 GBfits
H100 80 GBfits
RTX PRO 6000 Blackwell 96 GBfits
DGX Spark (GB10) 128 GB unifiedfits
H200 141 GBfits
B200 180 GBfits

How it works

How language models work

Your prompttext / messagesTransformerattention over tokensNext-token loopgenerate + streamResponsetext · tool callsA language model reads your tokens and predicts the next one, again and again, streaming the reply back.
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