Kimi K2.5/K2.6/K2.7-Code 1T — H200 vs MI355X Performance per Dollar
Cost per million tokens of H200 (NVIDIA Hopper) versus MI355X (AMD CDNA 4) 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.
H200 $0.97 and MI355X $0.97 per million tokens at 46 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T: effectively the same cost.
Push Kimi K2.5/K2.6/K2.7-Code 1T to 59 tok/s/user and H200 lands at $1.23 per million tokens against MI355X's $1.39 — H200 pulls ahead by 13%.
H200: $1.55 per million tokens. MI355X: $1.90. Both at 72 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T, with H200 23% cheaper. (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.)
Chip pricing (owning hyperscaler): H200 $1.22/chip/hr · MI355X $1.50/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 | H200:$0.966MI355X:$0.974 | H200:$1.230MI355X:$1.390 | H200:$1.553MI355X:$1.904 |
| Concurrency | H200:~31MI355X:~19 | H200:~19MI355X:~10 | H200:~12MI355X:~6 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.