Can I run it?

Can I run Qwen2.5 32B Instruct on NVIDIA H100 SXM 80GB?

Runs

Runs fully on your NVIDIA H100 SXM 80GB at F16, 8K context, about 27–37 tok/s. Weights 61.0 GB plus 2.00 GB of KV cache — 63.9 GB of 76.0 GB usable. Up to 32K context still fits.

Qwen2.5 32B Instruct details · NVIDIA H100 SXM 80GB page · How this estimate is made

Run commands

llama-server -hf bartowski/Qwen2.5-32B-Instruct-GGUF:F16 -c 8192 -ngl 64

ollama run qwen2.5

lms get bartowski/Qwen2.5-32B-Instruct-GGUF
# Then load quant F16

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%.
• F16 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 Qwen3.6 35B A3B on NVIDIA H100 SXM 80GB? — Tight fit, BF16, 299–407 tok/s
• Can I run Qwen3.8 35B A3B Distill on NVIDIA H100 SXM 80GB? — Tight fit, BF16, 298–407 tok/s
• Can I run Qwen3.8 Flash Next on NVIDIA H100 SXM 80GB? — Tight fit, UD-IQ1_M, 144–196 tok/s

Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.