Can I run InternVL3_5-GPT-OSS-20B-A4B-Preview-HF on an RTX 6000 Ada?

Yes, just

Its published weights (42.5 GB) fit in the 43.2 GB an RTX 6000 Ada can use, with room for ≈ 29K tokens of context.

Full analysis of InternVL3_5-GPT-OSS-20B-A4B-Preview-HF Everything that runs on RTX 6000 Ada Get the weights on Hugging Face

hf download OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF

Files and context on RTX 6000 Ada

Each file of InternVL3_5-GPT-OSS-20B-A4B-Preview-HF (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 RTX 6000 Ada	Context (16-bit)	Context (8-bit)
As published	42.5 GB	Tight	29K	58K
4-bit (estimate)	11.9 GB	Fits	128K	128K

InternVL3_5-GPT-OSS-20B-A4B-Preview-HF on other hardware

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 GBNo
RTX 4060No
RTX 6000 AdaYes, just
Mac with 32 GBProbably, at 4-bit
Mac with 64 GBYes, just
Mac with 128 GBYes

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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.