Model reference · open weights

Lumina-mGPT-768

LLMs Alpha-VLLM Omni (any→any) 1 build Licence not stated 2k dl/mo

Lumina-mGPT-768 is an open-weight language model from Alpha-VLLM. Lumina-mGPT-7B-768 (BF16) weighs 14.0 GB; the smallest configuration that runs it is 2× RTX 3060 12 GB.

What it is

Released byAlpha-VLLM
Released2024-07-29
Parameters7.0B
VRAM14.0 GB for the weights

What it runs on

Memory and cards for Lumina-mGPT-7B-768 (BF16)

14.0 GBweights, file size
524 MBcache per 1K tokens
654 MBruntime overhead, at least
4,096 tokenscontext max
CardRequests at onceContext maxMemory
4K each
RTX 3060 12 GB——11.6 GB
RTX 4060 Ti 16 GB—1K15.4 GB
RTX 3090 24 GB4all 4K23.4 GB
RTX 4090 24 GB4all 4K23.4 GB
RTX 5090 32 GB7all 4K31.0 GB
L40S 48 GB13all 4K44.0 GB
A100 80 GB29all 4K78.2 GB
H100 80 GB27all 4K78.1 GB
RTX PRO 6000 Blackwell 96 GB35all 4K93.8 GB
DGX Spark (GB10) 128 GB unified41all 4K107 GB
H200 141 GB55all 4K138 GB
B200 180 GB73all 4K176 GB
2× RTX 3060 12 GB
tensor parallel
3all 4K11.6 GB a card
2× RTX 4060 Ti 16 GB
tensor parallel
7all 4K15.4 GB a card
2× RTX 4090 24 GB
tensor parallel
14all 4K23.4 GB a card
2× RTX 3090 24 GB
tensor parallel
14all 4K23.4 GB a card
2× RTX 5090 32 GB
tensor parallel
21all 4K31.0 GB a card
Memory needed at each load
Requests at once4K tokens each
116.8 GB
525.4 GB
831.9 GB
1649.0 GB
3283.4 GB
64152 GB

One card, with vLLM's small-card settings.

From the model card

What Alpha-VLLM says about Lumina-mGPT-768

Lumina-mGPT is a family of multimodal autoregressive models capable of various vision and language tasks, particularly excelling in generating flexible photorealistic images from text descriptions.

Read the full model card

Usage

We provide the implementation of Lumina-mGPT, as well as sampling code, in our github repository.

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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