NVIDIA · 141 GB HBM3e · 4800 GB/s bandwidth ·
OpenAI · 120.4B (active 5.1B) · MoE · model ctx up to 128K
Yes — the H200 141GB SXM5 (141 GB HBM3e) 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 141 GB. Decode at Q4/8K: ≈ 598.9 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
Quant
Context
VRAM needed
Fits?
tok/s (decode)
Q4
4K
67.73 GB
Yes
598.9est.
Q4
8K default
68.24 GB
Yes
598.9est.
Q4
32K
71.3 GB
Yes
598.9est.
FP16
4K
242.31 GB
No
159.3est.
FP16
8K default
242.82 GB
No
158.7est.
FP16
32K
245.88 GB
No
154.8est.
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).