DeepSeek R1 — B200 vs MI325X Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) versus MI325X (AMD CDNA 3) on DeepSeek R1. 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 DeepSeek R1 at 25 tok/s/user, the per-million math comes out to $0.09 for B200 and $0.42 for MI325X; B200 delivers 350% more output per dollar.
At 35 tok/s/user on DeepSeek R1, B200 costs $0.10 per million tokens; MI325X costs $0.52. B200 is 410% more cost-efficient at this operating point.
B200 edges MI325X at 44 tok/s/user on DeepSeek R1 — $0.11 per million tokens versus $0.77, a 625% cost-per-token gap. (Numbers reflect the default 8k/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 · MI325X $1.28/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:$0.092MI325X:$0.416 | B200:$0.101MI325X:$0.518 | B200:$0.106MI325X:$0.769 |
| Concurrency | B200:~1088MI325X:~33 | B200:~892MI325X:~19 | B200:~467MI325X:~10 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.