Kimi K2.5/K2.6/K2.7-Code 1T — MI300X vs MI325X Performance per Dollar
Cost per million tokens of MI300X (AMD CDNA 3) versus MI325X (AMD CDNA 3) on Kimi K2.5/K2.6/K2.7-Code 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.
On Kimi K2.5/K2.6/K2.7-Code 1T at 24 tok/s/user, the per-million math comes out to $2.63 for MI300X and $2.50 for MI325X; MI325X delivers 5% more output per dollar.
At 32 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T, MI300X costs $3.22 per million tokens; MI325X costs $2.72. MI325X is 18% more cost-efficient at this operating point.
MI325X edges MI300X at 40 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T — $4.03 per million tokens versus $4.44, a 10% cost-per-token gap. (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): MI300X $1.12/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 | MI300X:$2.627MI325X:$2.495 | MI300X:$3.224MI325X:$2.721 | MI300X:$4.441MI325X:$4.028 |
| Concurrency | MI300X:~20MI325X:~24 | MI300X:~12MI325X:~17 | MI300X:~7MI325X:~9 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.