Kimi K2.5/K2.6/K2.7-Code 1T — B200 vs MI325X Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) 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.
Push Kimi K2.5/K2.6/K2.7-Code 1T to 40 tok/s/user and B200 lands at $0.94 per million tokens against MI325X's $3.46 — B200 pulls ahead by 270%.
B200: $1.05 per million tokens. MI325X: $4.28. Both at 44 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T, with B200 310% cheaper.
Toward the upper edge of the 37–51 tok/s/user interactivity band — at 48 tok/s/user — B200 runs $1.16 per million tokens on Kimi K2.5/K2.6/K2.7-Code 1T while MI325X runs $5.24. B200 is the cheaper choice by 351%. (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): B200 $1.73/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 | B200:$0.936MI325X:$3.462 | B200:$1.045MI325X:$4.284 | B200:$1.162MI325X:$5.244 |
| Concurrency | B200:~55MI325X:~9 | B200:~45MI325X:~7 | B200:~36MI325X:~5 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.