MiniMax M2.5/M2.7 — H200 vs MI300X Performance per Dollar
Cost per million tokens of H200 (NVIDIA Hopper) 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.
H200: $0.19 per million tokens. MI300X: $0.21. Both at 44 tok/s/user on MiniMax M2.5/M2.7, with H200 11% cheaper.
Around the middle of the 27–95 tok/s/user interactivity band — at 61 tok/s/user — H200 runs $0.39 per million tokens on MiniMax M2.5/M2.7 while MI300X runs $0.34. MI300X is the cheaper choice by 16%.
On MiniMax M2.5/M2.7 at 78 tok/s/user, the per-million math comes out to $0.56 for H200 and $0.63 for MI300X; H200 delivers 13% 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.)
Chip pricing (owning hyperscaler): H200 $1.22/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 | H200:$0.192MI300X:$0.212 | H200:$0.395MI300X:$0.341 | H200:$0.559MI300X:$0.633 |
| Concurrency | H200:~83MI300X:~63 | H200:~29MI300X:~26 | H200:~16MI300X:~11 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.