Kimi K2.5/K2.6/K2.7-Code 1T — GB200 NVL72 vs GB300 NVL72 Performance per Dollar
Cost per million tokens of GB200 NVL72 (NVIDIA Blackwell) versus GB300 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.
GB200 NVL72 edges GB300 NVL72 at 60 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T — $0.07 per million tokens versus $0.08, a 18% cost-per-token gap.
Push Kimi K2.5/K2.6/K2.7-Code 1T to 102 tok/s/user and GB200 NVL72 lands at $1.18 per million tokens against GB300 NVL72's $1.04 — GB300 NVL72 pulls ahead by 13%.
GB200 NVL72: $2.65 per million tokens. GB300 NVL72: $3.01. Both at 144 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T, with GB200 NVL72 14% 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.)
Chip pricing (owning hyperscaler): GB200 NVL72 $1.86/chip/hr · GB300 NVL72 $2.31/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 | GB200 NVL72:$0.068GB300 NVL72:$0.080 | GB200 NVL72:$1.184GB300 NVL72:$1.045 | GB200 NVL72:$2.652GB300 NVL72:$3.014 |
| Concurrency | GB200 NVL72:~3340GB300 NVL72:~3377 | GB200 NVL72:~98GB300 NVL72:~135 | GB200 NVL72:~28GB300 NVL72:~29 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.