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 39 tok/s/user, the per-million math comes out to $0.37 for GB300 NVL72 and $0.26 for MI355X; MI355X delivers 44% more output per dollar.
At 69 tok/s/user on MiniMax M3 428B, GB300 NVL72 costs $1.43 per million tokens; MI355X costs $0.81. MI355X is 78% more cost-efficient at this operating point.
MI355X edges GB300 NVL72 at 100 tok/s/user on MiniMax M3 428B — $2.24 per million tokens versus $3.11, a 39% 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:$0.371MI355X:$0.258 | GB300 NVL72:$1.432MI355X:$0.806 | GB300 NVL72:$3.106MI355X:$2.239 |
| Concurrency | GB300 NVL72:~287MI355X:~86 | GB300 NVL72:~30MI355X:~33 | GB300 NVL72:~7MI355X:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.