GLM 5/5.1 — GB300 NVL72 vs H200 Performance per Dollar
Cost per million tokens of GB300 NVL72 (NVIDIA Blackwell) versus H200 (NVIDIA Hopper) on GLM 5/5.1. 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.
Only GB300 NVL72 has cost data at 69 tok/s/user on GLM 5/5.1 — $0.10 per million tokens. H200 is unmeasured at this target.
GB300 NVL72 costs $0.79 per million tokens at 121 tok/s/user on GLM 5/5.1; we have no H200 benchmark data at this exact target.
At 173 tok/s/user on GLM 5/5.1, GB300 NVL72 comes in at $4.24 per million tokens. H200 hasn't been benchmarked at this operating point. (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.)
Chip pricing (owning hyperscaler): GB300 NVL72 $2.31/chip/hr · H200 $1.22/chip/hr. Source: SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model.
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Dollar per Million Tokens | GB300 NVL72:$0.096H200:— | GB300 NVL72:$0.792H200:— | GB300 NVL72:$4.242H200:— |
| Concurrency | GB300 NVL72:~1221H200:— | GB300 NVL72:~166H200:— | GB300 NVL72:~23H200:— |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.