Can I run it?
Can I run Qwen3.8 Flash Next on NVIDIA H100 SXM 80GB?
Tight fit
Tight fit fully on your NVIDIA H100 SXM 80GB at UD-IQ1_M, 8K context, about 144–196 tok/s. Weights 69.4 GB plus 0.24 GB of KV cache — 70.7 GB of 76.0 GB usable. Up to 128K context still fits.
Best quantUD-IQ1_M
Working context8K
Max that fits128K
Speed144–196 tok/s
Weights69.4 GB
KV cache0.24 GB
Total70.7 GB
Usable76.0 GB
Qwen3.8 Flash Next details · NVIDIA H100 SXM 80GB page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/Qwen3.8-Flash-Next-GGUF:UD-IQ1_M -c 8192 -ngl 48
Ollama
ollama run qwen3.8-flash-next
LM Studio
lms get unsloth/Qwen3.8-Flash-Next-GGUF # Then load quant UD-IQ1_M
Assumptions
- Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
- KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
- UD-IQ1_M size is the real GGUF file size from Hugging Face.
- CPU runs keep about 4 GB plus a 10% cushion for the OS.
- Speed is quoted at 8K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Step 3.7 Flash on NVIDIA H100 SXM 80GB? — Tight fit, UD-Q2_K_XL, 77–106 tok/s
- Can I run MiniMax M2 on NVIDIA H100 SXM 80GB? — Tight fit, UD-IQ2_XXS, 119–162 tok/s
- Can I run Qwen3 VL 235B A22B Instruct on NVIDIA H100 SXM 80GB? — Tight fit, UD-IQ1_M, 228–311 tok/s
Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.