MiniMax M2.5/M2.7 — B200 vs MI300X Performance per Dollar
Cost per million tokens of B200 (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.
B200: $0.10 per million tokens. MI300X: $0.25. Both at 44 tok/s/user on MiniMax M2.5/M2.7, with B200 150% cheaper.
Around the middle of the 27–95 tok/s/user interactivity band — at 61 tok/s/user — B200 runs $0.17 per million tokens on MiniMax M2.5/M2.7 while MI300X runs $0.40. B200 is the cheaper choice by 132%.
On MiniMax M2.5/M2.7 at 78 tok/s/user, the per-million math comes out to $0.32 for B200 and $0.75 for MI300X; B200 delivers 136% more output per dollar. (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.)
GPU pricing (owning hyperscaler): B200 $1.95/GPU/hr · MI300X $1.12/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:$0.100MI300X:$0.250 | B200:$0.173MI300X:$0.402 | B200:$0.317MI300X:$0.747 |
| Concurrency | B200:~254MI300X:~63 | B200:~105MI300X:~26 | B200:~45MI300X:~11 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.