MiniMax M2.5/M2.7 — GB200 NVL72 vs GB300 NVL72 Performance per Dollar
Cost per million tokens of GB200 NVL72 (NVIDIA Blackwell) versus GB300 NVL72 (NVIDIA Blackwell) on MiniMax M2.5/M2.7. 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: $0.06 per million tokens. GB300 NVL72: $0.07. Both at 68 tok/s/user on MiniMax M2.5/M2.7, with GB200 NVL72 17% cheaper.
Around the middle of the 31–180 tok/s/user interactivity band — at 105 tok/s/user — GB200 NVL72 runs $0.16 per million tokens on MiniMax M2.5/M2.7 while GB300 NVL72 runs $0.19. GB200 NVL72 is the cheaper choice by 18%.
On MiniMax M2.5/M2.7 at 143 tok/s/user, the per-million math comes out to $0.49 for GB200 NVL72 and $0.61 for GB300 NVL72; GB200 NVL72 delivers 25% more output per dollar. (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:$0.061GB300 NVL72:$0.072 | GB200 NVL72:$0.160GB300 NVL72:$0.189 | GB200 NVL72:$0.489GB300 NVL72:$0.611 |
| Concurrency | GB200 NVL72:~928GB300 NVL72:~1024 | GB200 NVL72:~236GB300 NVL72:~211 | GB200 NVL72:~45GB300 NVL72:~34 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.