Kimi K2.5/K2.6/K2.7-Code 1T — GB300 NVL72 vs H200 Performance per Dollar
Cost per million tokens of GB300 NVL72 (NVIDIA Blackwell) versus H200 (NVIDIA Hopper) on Kimi K2.5/K2.6/K2.7-Code 1T. 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 50 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T, GB300 NVL72 comes in at $0.14 per million tokens. H200 hasn't been benchmarked at this operating point.
Only GB300 NVL72 has cost data at 85 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T — $1.52 per million tokens. H200 is unmeasured at this target.
GB300 NVL72 costs $3.14 per million tokens at 119 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T; we have no H200 benchmark data at this exact target. (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): GB300 NVL72 $2.65/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 | GB300 NVL72:$0.138H200:— | GB300 NVL72:$1.524H200:— | GB300 NVL72:$3.138H200:— |
| Concurrency | GB300 NVL72:~1324H200:— | GB300 NVL72:~95H200:— | GB300 NVL72:~34H200:— |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.