Can I run it?
Can I run MiMo V2.6 Distill Qwen 9B on NVIDIA H100 SXM 80GB?
Runs great
Runs great fully on your NVIDIA H100 SXM 80GB at BF16, 8K context, about 101–138 tok/s. Weights 16.7 GB plus 0.27 GB of KV cache — 17.4 GB of 76.0 GB usable. Up to 256K context still fits.
Best quantBF16
Working context8K
Max that fits256K
Speed101–138 tok/s
Weights16.7 GB
KV cache0.27 GB
Total17.4 GB
Usable76.0 GB
MiMo V2.6 Distill Qwen 9B details · NVIDIA H100 SXM 80GB page · How this estimate is made
Run commands
llama.cpp
llama-server -hf bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF:BF16 -c 8192 -ngl 32
No matching name in the Ollama library snapshot.
LM Studio
lms get bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF # Then load quant BF16
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%.
- BF16 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 Qwen3.8 27B on NVIDIA H100 SXM 80GB? — Runs, BF16, 33–46 tok/s
- Can I run gemma 4 12b it on NVIDIA H100 SXM 80GB? — Runs great, BF16, 68–93 tok/s
- Can I run Qwen3.5 9B on NVIDIA H100 SXM 80GB? — Runs great, BF16, 101–138 tok/s
Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.