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Can I run this LLM?

Can a NVIDIA H100 SXM (80GB) run Qwen3 32B?

Qwen · Apache 2.0 · estimated for a 80.0 GB machine at 4K context.

Yes — it runs great.

Runs great

Best fit: Qwen3 32B at Q8_0 · 34.8 GB weights · 58–87 tok/s on a NVIDIA H100 SXM (80GB).

Arena Text Overall · style-controlled

1,347Q8_0 untested

qwen3-32b · published configuration reference · Q8_0 not tested

Arena Text Overall (style-controlled), exact published entry qwen3-32b, 2026-10-08: reference rating 1,346.9. Published confidence bounds 1,337.4–1,356.3. 3,926 votes. Published qwen3-32b configuration reference. Reasoning mode is not disclosed by the Arena dataset. Tested precision, runtime and sampling settings are not disclosed in this dataset. Selected Q8_0 has not been measured by this Arena entry. No quantization quality adjustment is applied.

Snapshot published 2026-10-08 · snapshot imported 2026-10-11 UTC · validated last-good data · manual refresh

Arena leaderboard dataset · Arena / lmarena-ai, Arena Leaderboard Dataset (CC BY 4.0). Selected Text Overall style-controlled rows; field names adapted, ratings unchanged. · dataset CC BY 4.0 · revision e16f90232986

Total memory at 4K context
36.7 GB
Weights + KV cache + runtime overhead
Estimated generation
58–87 tok/s
Estimated first token
~1.5s

Every quantization on this machine

On small screens, each quant lists every metric below its name. On wider screens, scroll sideways for total memory, speed and fit. Keyboard: focus the table, then use the arrow keys. Quant names stay visible.

Qwen3 32B quantizations on NVIDIA H100 SXM (80GB), estimated at 4K context. Weights and total memory are shown separately.
QuantWeightsTotal memorySpeedFit
Q2_K12.3 GB14.2 GB123–184 tok/sRuns great
Q3_K_M16.0 GB17.8 GB104–156 tok/sRuns great
Q4_K_M19.8 GB21.6 GB90–135 tok/sRuns great
Q5_K_M23.2 GB25.1 GB80–120 tok/sRuns great
Q6_K26.9 GB28.8 GB71–107 tok/sRuns great
Q8_034.8 GB36.7 GB58–87 tok/sRuns great
FP1665.5 GB67.4 GB34–51 tok/sTight / slow

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