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Can I run endless-frontier_BigBang-v1-GGUF on an RTX 6000 Ada?

Yes, just

Its Q8_0 file (37.8 GB) fits in the 43.2 GB an RTX 6000 Ada can use, with room for ≈ 254K tokens of context.

Full analysis of endless-frontier_BigBang-v1-GGUF Everything that runs on RTX 6000 Ada Get the Q8_0 file on Hugging Face
ollama run hf.co/bartowski/endless-frontier_BigBang-v1-GGUF:Q8_0

Files and context on RTX 6000 Ada

Each file of endless-frontier_BigBang-v1-GGUF (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.

FileSizeOn RTX 6000 Ada Context (16-bit)Context (8-bit)
BF1671.1 GBDoesn't fit——
Q8_037.8 GBTight254K256K
Q6_K_L30.8 GBFits256K256K
Q6_K30.5 GBFits256K256K
Q5_K_L25.8 GBFits256K256K
Q5_K_M25.5 GBFits256K256K
Q5_K_S24.6 GBFits256K256K
Q4_122.4 GBFits256K256K
Q4_K_L22.2 GBFits256K256K
Q4_K_M21.9 GBFits256K256K
Q4_K_S21.1 GBFits256K256K
Q4_020.4 GBFits256K256K
IQ4_NL20.3 GBFits256K256K
IQ4_XS19.3 GBFits256K256K
Q3_K_XL17.8 GBFits256K256K
IQ3_M17.4 GBFits256K256K
Q3_K_L17.4 GBFits256K256K
Q3_K_M16.7 GBFits256K256K
IQ3_XS16.7 GBFits256K256K
Q3_K_S16.0 GBFits256K256K
IQ3_XXS15.3 GBFits256K256K
Q2_K_L13.6 GBFits256K256K
Q2_K13.1 GBFits256K256K
IQ2_M12.5 GBFits256K256K
IQ2_S11.5 GBFits256K256K
IQ2_XS11.3 GBFits256K256K
IQ2_XXS10.3 GBFits256K256K

endless-frontier_BigBang-v1-GGUF on other hardware

Popular models that run on RTX 6000 Ada

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.