Kimi K2.5/K2.6/K2.7-Code 1T — B200 vs GB200 NVL72 Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) versus GB200 NVL72 (NVIDIA Blackwell) 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.
Near the low end of the 24–180 tok/s/user interactivity band — at 62 tok/s/user — B200 runs $0.13 per million tokens on Kimi K2.5/K2.6/K2.7-Code 1T while GB200 NVL72 runs $0.06. GB200 NVL72 is the cheaper choice by 103%.
On Kimi K2.5/K2.6/K2.7-Code 1T at 102 tok/s/user, the per-million math comes out to $0.30 for B200 and $0.40 for GB200 NVL72; B200 delivers 34% more output per dollar.
At 141 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T, B200 costs $0.92 per million tokens; GB200 NVL72 costs $0.82. GB200 NVL72 is 13% more cost-efficient at this operating point. (Numbers reflect the default 8k/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): B200 $1.95/GPU/hr · GB200 NVL72 $2.21/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 | B200:$0.132GB200 NVL72:$0.065 | B200:$0.297GB200 NVL72:$0.397 | B200:$0.921GB200 NVL72:$0.817 |
| Concurrency | B200:~208GB200 NVL72:~1229 | B200:~80GB200 NVL72:~199 | B200:~5GB200 NVL72:~27 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.