MiniMax M3 428B — GB300 NVL72 vs MI355X Performance per Dollar
Cost per million tokens of GB300 NVL72 (NVIDIA Blackwell) versus MI355X (AMD CDNA 4) 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 46 tok/s/user, the per-million math comes out to $0.27 for GB300 NVL72 and $0.14 for MI355X; MI355X delivers 91% more output per dollar.
At 84 tok/s/user on MiniMax M3 428B, GB300 NVL72 costs $1.00 per million tokens; MI355X costs $0.24. MI355X is 322% more cost-efficient at this operating point.
MI355X edges GB300 NVL72 at 121 tok/s/user on MiniMax M3 428B — $0.38 per million tokens versus $2.73, a 615% 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): GB300 NVL72 $2.65/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 | GB300 NVL72:$0.270MI355X:$0.141 | GB300 NVL72:$0.996MI355X:$0.236 | GB300 NVL72:$2.726MI355X:$0.381 |
| Concurrency | GB300 NVL72:~700MI355X:~138 | GB300 NVL72:~89MI355X:~44 | GB300 NVL72:~23MI355X:~19 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.