gpt-oss 120B — GB200 NVL72 vs H100 Performance per Dollar
Cost per million tokens of GB200 NVL72 (NVIDIA Blackwell) versus H100 (NVIDIA Hopper) on gpt-oss 120B. Owning-hyperscaler TCO normalized by output tokens — performance per dollar across LLM workloads. Pick the more cost-efficient SKU at every target interactivity level. Use the chart controls below to switch sequences, precisions, and metrics — same interactions as the main inference chart.
GB200 NVL72 edges H100 at 117 tok/s/user on gpt-oss 120B — $0.03 per million tokens versus $0.14, a 328% cost-per-token gap.
Push gpt-oss 120B to 166 tok/s/user and GB200 NVL72 lands at $0.04 per million tokens against H100's $0.26 — GB200 NVL72 pulls ahead by 591%.
GB200 NVL72: $0.07 per million tokens. H100: $0.49. Both at 216 tok/s/user on gpt-oss 120B, with GB200 NVL72 593% cheaper. (Numbers reflect the default 1k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
GPU pricing (owning hyperscaler): GB200 NVL72 $2.21/GPU/hr · H100 $1.30/GPU/hr. Source: SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model.
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Dollar per Million Tokens | GB200 NVL72:$0.032H100:$0.139 | GB200 NVL72:$0.038H100:$0.262 | GB200 NVL72:$0.070H100:$0.487 |
| Concurrency | GB200 NVL72:~264H100:~64 | GB200 NVL72:~2684H100:~17 | GB200 NVL72:~102H100:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.