DeepSeek R1 — B300 vs MI325X Performance per Dollar
Cost per million tokens of B300 (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.
At 39 tok/s/user on DeepSeek R1, B300 costs $0.15 per million tokens; MI325X costs $0.88. B300 is 473% more cost-efficient at this operating point.
B300 edges MI325X at 50 tok/s/user on DeepSeek R1 — $0.20 per million tokens versus $1.35, a 588% cost-per-token gap.
Push DeepSeek R1 to 60 tok/s/user and B300 lands at $0.32 per million tokens against MI325X's $2.30 — B300 pulls ahead by 617%. (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 · MI325X $1.10/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:$0.154MI325X:$0.883 | B300:$0.196MI325X:$1.345 | B300:$0.320MI325X:$2.296 |
| Concurrency | B300:~2628MI325X:~39 | B300:~1808MI325X:~19 | B300:~937MI325X:~9 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.