Kimi K2.5/K2.6 1T — H200 vs MI325X Performance per Dollar
Cost per million tokens of H200 (NVIDIA Hopper) versus MI325X (AMD CDNA 3) on Kimi K2.5/K2.6 1T. 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.
H200: $0.89 per million tokens. MI325X: $3.58. Both at 38 tok/s/user on Kimi K2.5/K2.6 1T, with H200 302% cheaper.
Around the middle of the 34–51 tok/s/user interactivity band — at 42 tok/s/user — H200 runs $1.01 per million tokens on Kimi K2.5/K2.6 1T while MI325X runs $4.49. H200 is the cheaper choice by 346%.
On Kimi K2.5/K2.6 1T at 47 tok/s/user, the per-million math comes out to $1.14 for H200 and $5.81 for MI325X; H200 delivers 409% more output per dollar. (Numbers reflect the default 1k/1k · int4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
GPU pricing (owning hyperscaler): H200 $1.41/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 | H200:$0.891MI325X:$3.581 | H200:$1.006MI325X:$4.490 | H200:$1.142MI325X:$5.811 |
| Concurrency | H200:~50MI325X:~11 | H200:~40MI325X:~8 | H200:~30MI325X:~5 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.