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Can H100 80GB SXM5 run gpt-oss-120b?

NVIDIA · 80 GB HBM3 · 3350 GB/s bandwidth · OpenAI · 120.4B (active 5.1B) · MoE · model ctx up to 128K

Yes — the H100 80GB SXM5 (80 GB HBM3) can run gpt-oss-120b. At Q4 with the default 8K context it needs ≈ 68.24 GB VRAM (weights 66.22 GB + KV cache 1.02 GB + 1 GB runtime overhead), which fits within 80 GB. Decode at Q4/8K: ≈ 418.0 tok/s (estimated, batch 1). FP16 needs ≈ 242.82 GB — does not fit on this card. Estimates come from memory-bandwidth math; rows tagged measured override estimates. Relative ranking is more reliable than absolute tok/s. Methodology.

Fit & speed by quant and context

QuantContextVRAM neededFits?tok/s (decode)
Q44K67.73 GBYes418.0 est.
Q48K default68.24 GBYes418.0 est.
Q432K71.3 GBYes418.0 est.
FP164K242.31 GBNo35.8 est.
FP168K default242.82 GBNo35.6 est.
FP1632K245.88 GBNo34.8 est.

Fits = weights + KV(ctx) + 1 GB overhead ≤ 95% of VRAM. Measured anchors are context-agnostic; the fit verdict is recomputed per context. A missing tok/s means the model is far beyond this card (offload-only territory).

VRAM breakdown at 8K context

QuantWeightsKV cacheOverheadTotal neededH100 80GB SXM5 VRAM
Q466.22 GB1.02 GB1 GB68.24 GB80 GB
FP16240.8 GB1.02 GB1 GB242.82 GB80 GB

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