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 $0.17 for B200 and $0.57 for MI325X; B200 delivers 240% more output per dollar.
At 96 tok/s/user on MiniMax M3 428B, B200 costs $0.33 per million tokens; MI325X costs $1.48. B200 is 344% more cost-efficient at this operating point.
B200 edges MI325X at 139 tok/s/user on MiniMax M3 428B — $0.40 per million tokens versus $2.66, a 559% 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.)
Chip pricing (owning hyperscaler): B200 $1.73/chip/hr · MI325X $1.10/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 | B200:$0.166MI325X:$0.565 | B200:$0.333MI325X:$1.481 | B200:$0.403MI325X:$2.657 |
| Concurrency | B200:~138MI325X:~45 | B200:~45MI325X:~9 | B200:~17MI325X:~4 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.