Can I run SmolVLM2-500M-Video-Instruct on an NVIDIA B200?

Yes

Its published weights (2.03 GB) fit in the 162 GB an NVIDIA B200 can use, with room for ≈ 8K tokens of context.

Full analysis of SmolVLM2-500M-Video-Instruct Everything that runs on NVIDIA B200 Get the weights on Hugging Face

hf download HuggingFaceTB/SmolVLM2-500M-Video-Instruct

Files and context on NVIDIA B200

Each file of SmolVLM2-500M-Video-Instruct (and of GGUF versions the site has analyzed), and how much context fits next to it, with the context cache in 16-bit or 8-bit.

File	Size	On NVIDIA B200	Context (16-bit)	Context (8-bit)
As published	2.03 GB	Fits	8K	8K
4-bit (estimate)	285 MB	Fits	8K	8K

SmolVLM2-500M-Video-Instruct on other hardware

NVIDIA B200Yes
NVIDIA H100Yes
RTX 5090Yes
RTX 4090Yes
RTX 3090Yes
RTX 5060 Ti 16 GBYes
RTX 3060 12 GBYes
RTX 4060Yes
Mac with 32 GBYes
Mac with 64 GBYes
Mac with 128 GBYes

Popular models that run on NVIDIA B200

Qwen3-0.6BQwen · 752M
Qwen3-VL-8B-InstructQwen · 8.77B
gpt2openai-community · 137M
Qwen3-8BQwen · 8.19B
Qwen3-Coder-30B-A3B-Instruct-GGUFunsloth · 30.5B
gemma-4-26B-A4B-itgoogle · 25.8B
Qwen2.5-7B-InstructQwen · 7.62B
Qwen3.5-9BQwen · 9.65B

Assumes 90% of the card's memory is usable and at least 4K tokens of context for one conversation, with the context cache in 16-bit unless noted. Fits leaves at least 20% of that memory for context; Tight leaves less.