DeepSeek R1 — H100 vs MI325X Performance per Dollar
Cost per million tokens of H100 (NVIDIA Hopper) 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, H100 costs $1.20 per million tokens; MI325X costs $0.88. MI325X is 35% more cost-efficient at this operating point.
MI325X edges H100 at 50 tok/s/user on DeepSeek R1 — $1.35 per million tokens versus $1.98, a 47% cost-per-token gap.
Push DeepSeek R1 to 60 tok/s/user and H100 lands at $2.47 per million tokens against MI325X's $2.30 — MI325X pulls ahead by 7%. (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): H100 $1.17/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 | H100:$1.196MI325X:$0.883 | H100:$1.977MI325X:$1.345 | H100:$2.465MI325X:$2.296 |
| Concurrency | H100:~624MI325X:~39 | H100:~203MI325X:~19 | H100:~128MI325X:~9 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.