Model reference · open weights

Chameleon_7B_mGPT

LLMs Alpha-VLLM Omni (any→any) 1 build Licence not stated 0 dl/mo

Chameleon_7B_mGPT is an open-weight language model from Alpha-VLLM. Chameleon_7B_mGPT (BF16) weighs 14.1 GB; the smallest configuration that runs it is RTX 4060 Ti 16 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • Chameleon_7B_mGPT is a 7.0B parameter any-to-any model developed by Alpha-VLLM.
  • It is a converted checkpoint of the Chameleon-7b model intended to ease the initialization of Lumina-mGPT training.
  • The model features a modified qk-norm implementation that ensures parameter consistency within attention head groups during fine-tuning.

Summary of the Alpha-VLLM/Chameleon_7B_mGPT model card, 2026-10-01

What it is

Released byAlpha-VLLM
Released2024-07-28
Parameters7.0B
VRAM14.1 GB for the weights

What it runs on

Memory and cards for Chameleon_7B_mGPT (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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