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: $0.33 per million tokens. MI300X: $0.31. Both at 53 tok/s/user on MiniMax M2.5/M2.7, with MI300X 6% cheaper.
Around the middle of the 39–95 tok/s/user interactivity band — at 67 tok/s/user — H200 runs $0.61 per million tokens on MiniMax M2.5/M2.7 while MI300X runs $0.50. MI300X is the cheaper choice by 23%.
On MiniMax M2.5/M2.7 at 81 tok/s/user, the per-million math comes out to $0.92 for H200 and $0.84 for MI300X; MI300X delivers 10% 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): H200 $1.41/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 | H200:$0.331MI300X:$0.311 | H200:$0.607MI300X:$0.495 | H200:$0.924MI300X:$0.843 |
| Concurrency | H200:~91MI300X:~41 | H200:~41MI300X:~19 | H200:~21MI300X:~9 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.