MiniMax M2.5/M2.7 — GB300 NVL72 vs MI300X Performance per Dollar
Cost per million tokens of GB300 NVL72 (NVIDIA Blackwell) versus MI300X (AMD CDNA 3) 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.
Near the low end of the 27–95 tok/s/user interactivity band — at 44 tok/s/user — GB300 NVL72 runs $0.10 per million tokens on MiniMax M2.5/M2.7 while MI300X runs $0.21. GB300 NVL72 is the cheaper choice by 114%.
On MiniMax M2.5/M2.7 at 61 tok/s/user, the per-million math comes out to $0.17 for GB300 NVL72 and $0.34 for MI300X; GB300 NVL72 delivers 99% more output per dollar.
At 78 tok/s/user on MiniMax M2.5/M2.7, GB300 NVL72 costs $0.42 per million tokens; MI300X costs $0.63. GB300 NVL72 is 52% more cost-efficient at this operating point. (Numbers reflect the default 1k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
Chip pricing (owning hyperscaler): GB300 NVL72 $2.31/chip/hr · MI300X $0.95/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 | GB300 NVL72:$0.099MI300X:$0.212 | GB300 NVL72:$0.171MI300X:$0.341 | GB300 NVL72:$0.417MI300X:$0.633 |
| Concurrency | GB300 NVL72:~752MI300X:~63 | GB300 NVL72:~353MI300X:~26 | GB300 NVL72:~64MI300X:~11 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.