MiniMax M3 428B — B200 vs GB200 NVL72 Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) versus GB200 NVL72 (NVIDIA Blackwell) 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 52 tok/s/user, the per-million math comes out to $0.18 for B200 and $0.38 for GB200 NVL72; B200 delivers 109% more output per dollar.
At 87 tok/s/user on MiniMax M3 428B, B200 costs $0.35 per million tokens; GB200 NVL72 costs $1.00. B200 is 187% more cost-efficient at this operating point.
B200 edges GB200 NVL72 at 122 tok/s/user on MiniMax M3 428B — $0.42 per million tokens versus $2.86, a 584% 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 · GB200 NVL72 $2.21/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:$0.183GB200 NVL72:$0.382 | B200:$0.347GB200 NVL72:$0.996 | B200:$0.419GB200 NVL72:$2.862 |
| Concurrency | B200:~142GB200 NVL72:~180 | B200:~56GB200 NVL72:~74 | B200:~24GB200 NVL72:~18 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.