MiniMax M3 428B — B300 vs MI300X Performance per Dollar
Cost per million tokens of B300 (NVIDIA Blackwell) versus MI300X (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 48 tok/s/user, the per-million math comes out to $0.18 for B300 and $0.51 for MI300X; B300 delivers 184% more output per dollar.
At 82 tok/s/user on MiniMax M3 428B, B300 costs $0.31 per million tokens; MI300X costs $1.31. B300 is 316% more cost-efficient at this operating point.
B300 edges MI300X at 115 tok/s/user on MiniMax M3 428B — $0.55 per million tokens versus $1.82, a 231% 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): B300 $2.26/chip/hr · MI300X $0.95/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 | B300:$0.179MI300X:$0.509 | B300:$0.314MI300X:$1.307 | B300:$0.550MI300X:$1.819 |
| Concurrency | B300:~447MI300X:~45 | B300:~68MI300X:~10 | B300:~27MI300X:~5 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.