MiniMax M2.5/M2.7 — B200 vs MI355X Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) 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.
On MiniMax M2.5/M2.7 at 43 tok/s/user, the per-million math comes out to $0.10 for B200 and $0.11 for MI355X; B200 delivers 16% more output per dollar.
At 68 tok/s/user on MiniMax M2.5/M2.7, B200 costs $0.22 per million tokens; MI355X costs $0.36. B200 is 63% more cost-efficient at this operating point.
B200 edges MI355X at 93 tok/s/user on MiniMax M2.5/M2.7 — $0.47 per million tokens versus $0.73, a 56% cost-per-token gap. (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 · MI355X $1.48/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:$0.097MI355X:$0.112 | B200:$0.221MI355X:$0.360 | B200:$0.469MI355X:$0.731 |
| Concurrency | B200:~272MI355X:~256 | B200:~75MI355X:~35 | B200:~24MI355X:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.