MiniMax M2.5/M2.7 — B200 vs GB200 NVL72 Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) versus GB200 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.
Push MiniMax M2.5/M2.7 to 68 tok/s/user and B200 lands at $0.06 per million tokens against GB200 NVL72's $0.06 — B200 pulls ahead by 4%.
At 105 tok/s/user on MiniMax M2.5/M2.7, B200 and GB200 NVL72 land within ~1% on cost per million tokens ($0.16 vs $0.16) — call it a tie at this operating point.
Toward the upper edge of the 31–180 tok/s/user interactivity band — at 143 tok/s/user — B200 runs $0.42 per million tokens on MiniMax M2.5/M2.7 while GB200 NVL72 runs $0.49. B200 is the cheaper choice by 16%. (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): B200 $1.73/chip/hr · GB200 NVL72 $1.86/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 | B200:$0.059GB200 NVL72:$0.061 | B200:$0.162GB200 NVL72:$0.160 | B200:$0.420GB200 NVL72:$0.489 |
| Concurrency | B200:~831GB200 NVL72:~928 | B200:~106GB200 NVL72:~236 | B200:~18GB200 NVL72:~45 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.