MiniMax M2.5/M2.7 — H100 vs MI355X Performance per Dollar
Cost per million tokens of H100 (NVIDIA Hopper) versus MI355X (AMD CDNA 4) 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.
At 60 tok/s/user on MiniMax M2.5/M2.7, H100 costs $0.53 per million tokens; MI355X costs $0.25. MI355X is 114% more cost-efficient at this operating point.
MI355X edges H100 at 79 tok/s/user on MiniMax M2.5/M2.7 — $0.49 per million tokens versus $0.92, a 87% cost-per-token gap.
Push MiniMax M2.5/M2.7 to 98 tok/s/user and H100 lands at $1.56 per million tokens against MI355X's $0.79 — MI355X pulls ahead by 97%. (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): H100 $1.17/chip/hr · MI355X $1.50/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 | H100:$0.534MI355X:$0.249 | H100:$0.920MI355X:$0.491 | H100:$1.563MI355X:$0.793 |
| Concurrency | H100:~41MI355X:~46 | H100:~18MI355X:~20 | H100:~9MI355X:~5 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.