Kimi K2.5/K2.6/K2.7-Code 1T — B300 vs MI355X Performance per Dollar
Cost per million tokens of B300 (NVIDIA Blackwell) 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.
Near the low end of the 11–123 tok/s/user interactivity band — at 38 tok/s/user — B300 runs $0.15 per million tokens on Kimi K2.5/K2.6/K2.7-Code 1T while MI355X runs $0.10. MI355X is the cheaper choice by 38%.
On Kimi K2.5/K2.6/K2.7-Code 1T at 67 tok/s/user, the per-million math comes out to $0.23 for B300 and $0.17 for MI355X; MI355X delivers 36% more output per dollar.
At 95 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T, B300 costs $0.34 per million tokens; MI355X costs $0.24. MI355X is 41% more cost-efficient at this operating point. (Numbers reflect the default 8k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
Chip pricing (owning hyperscaler): B300 $2.26/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 | B300:$0.145MI355X:$0.105 | B300:$0.228MI355X:$0.167 | B300:$0.336MI355X:$0.238 |
| Concurrency | B300:~51MI355X:~102 | B300:~19MI355X:~17 | B300:~9MI355X:~9 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.