MiniMax M3 428B — B200 vs MI325X Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) versus MI325X (AMD CDNA 3) on MiniMax M3 428B. 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 M3 428B at 53 tok/s/user, the per-million math comes out to $0.19 for B200 and $0.66 for MI325X; B200 delivers 251% more output per dollar.
At 96 tok/s/user on MiniMax M3 428B, B200 costs $0.38 per million tokens; MI325X costs $1.72. B200 is 359% more cost-efficient at this operating point.
B200 edges MI325X at 139 tok/s/user on MiniMax M3 428B — $0.45 per million tokens versus $3.09, a 581% 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 · MI325X $1.28/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:$0.187MI325X:$0.658 | B200:$0.376MI325X:$1.724 | B200:$0.454MI325X:$3.092 |
| Concurrency | B200:~138MI325X:~45 | B200:~45MI325X:~9 | B200:~17MI325X:~4 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.