Can I run DeepSeek-Coder-V2-Lite-Base on an NVIDIA B300?

Yes

Its published weights (31.4 GB) fit in the 259 GB an NVIDIA B300 can use, with room for ≈ 160K tokens of context.

Full analysis of DeepSeek-Coder-V2-Lite-Base Everything that runs on NVIDIA B300 Get the weights on Hugging Face

hf download deepseek-ai/DeepSeek-Coder-V2-Lite-Base

Files and context on NVIDIA B300

Each file of DeepSeek-Coder-V2-Lite-Base (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 B300	Context (16-bit)	Context (8-bit)
As published	31.4 GB	Fits	160K	160K
4-bit (estimate)	8.83 GB	Fits	160K	160K

DeepSeek-Coder-V2-Lite-Base on other hardware

NVIDIA B300Yes
NVIDIA H100Yes
RTX 5090Probably, at 4-bit
RTX 4090Probably, at 4-bit
RTX 3090Probably, at 4-bit
RTX 5060 Ti 16 GBProbably, at 4-bit
RTX 3060 12 GBProbably, at 4-bit
RTX 4060No
Mac with 32 GBProbably, at 4-bit
Mac with 64 GBYes
Mac with 128 GBYes

Popular models that run on NVIDIA B300

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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.