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Can I run Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-NM-DAU-NEO-MTP-GGUF on an NVIDIA H100?

Yes

Its Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-TOOLS-NM-DAU-NEO-MAX-MTP-Q8_0 file (30.2 GB) fits in the 72.0 GB an NVIDIA H100 can use, with room for ≈ 256K tokens of context.

Full analysis of Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-NM-DAU-NEO-MTP-GGUF Everything that runs on NVIDIA H100 Get the Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-TOOLS-NM-DAU-NEO-MAX-MTP-Q8_0 file on Hugging Face
ollama run hf.co/DavidAU/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-NM-DAU-NEO-MTP-GGUF

Files and context on NVIDIA H100

Each file of Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-NM-DAU-NEO-MTP-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 NVIDIA H100 Context (16-bit)Context (8-bit)
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-TOOLS-NM-DAU-NEO-MAX-MTP-Q8_030.2 GBFits256K256K
Q8_030.2 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-Q8_029.8 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-TOOLS-NM-DAU-NEO-MTP-Q8_029.0 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MTP-Q8_029.0 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-Q8_028.6 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-TOOLS-NM-DAU-NEO-MAX-MTP-Q6_K24.0 GBFits256K256K
Q6_K24.0 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-Q6_K23.6 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-TOOLS-NM-DAU-NEO-MTP-Q6_K22.4 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MTP-Q6_K22.4 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-Q6_K22.1 GBFits256K256K
Q5_K_M21.2 GBFits256K256K
Q5_K_S20.6 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MTP-Q5_K_M19.5 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MTP-Q5_K_S19.0 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-TOOLS-NM-DAU-NEO-MAX-MTP-Q4_K_M18.5 GBFits256K256K
Q4_K_M18.5 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-Q4_K_M18.0 GBFits256K256K
Q4_K_S17.5 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-TOOLS-NM-DAU-NEO-MAX-MTP-IQ4_XS17.0 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-MTP-IQ4_XS17.0 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-TOOLS-NM-DAU-NEO-MTP-Q4_K_M16.8 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MTP-Q4_K_M16.8 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-IQ4_XS16.6 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-Q4_K_M16.5 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MTP-Q4_K_S15.8 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-TOOLS-NM-DAU-NEO-MTP-IQ4_XS15.3 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MTP-IQ4_XS15.3 GBFits256K256K
IQ4_XS15.1 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-MTP-IQ3_M14.5 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-IQ3_M14.1 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MTP-IQ3_M12.8 GBFits256K256K
IQ3_M12.6 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-MTP-IQ2_M12.1 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-IQ2_M11.7 GBFits256K256K
Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MTP-IQ2_M10.2 GBFits256K256K
IQ2_M10.0 GBFits256K256K

Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-NM-DAU-NEO-MTP-GGUF on other hardware

Popular models that run on NVIDIA H100

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.