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Model reference · open weights

chameleon

LLMs facebook Vision + text 1 build Its own licence terms 28k dl/mo

chameleon is an open-weight language model from Meta. chameleon-7b (BF16) weighs 14.1 GB; the smallest configuration that runs it is RTX 4060 Ti 16 GB.

  • Chameleon is a mixed-modal early-fusion foundation model developed by Meta's FAIR team.
  • It is designed for image-text-to-text tasks and is available in 7.0B and 30B parameter variants.
  • The model is distributed under the Chameleon Research License.

Summary of the facebook/chameleon-7b model card, 2026-10-01

Hugging Face ↗GitHub ↗Paper ↗

What it is

Released byMeta
Released2024-03-26
Parameters7.0B
VRAM14.1 GB for the weights

What it runs on

Memory and cards for chameleon-7b (BF16)

14.1 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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