gpt-oss 120B — GB200 NVL72 vs H200 Performance per Dollar
Cost per million tokens of GB200 NVL72 (NVIDIA Blackwell) versus H200 (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.
At 97 tok/s/user on gpt-oss 120B, GB200 NVL72 costs $0.02 per million tokens; H200 costs $0.11. GB200 NVL72 is 519% more cost-efficient at this operating point.
GB200 NVL72 edges H200 at 155 tok/s/user on gpt-oss 120B — $0.03 per million tokens versus $0.22, a 527% cost-per-token gap.
Push gpt-oss 120B to 213 tok/s/user and GB200 NVL72 lands at $0.07 per million tokens against H200's $0.46 — GB200 NVL72 pulls ahead by 573%. (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 · H200 $1.41/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:$0.018H200:$0.113 | GB200 NVL72:$0.035H200:$0.218 | GB200 NVL72:$0.069H200:$0.461 |
| Concurrency | GB200 NVL72:~775H200:~64 | GB200 NVL72:~3072H200:~55 | GB200 NVL72:~107H200:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.