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 35–113 tok/s/user interactivity band — at 54 tok/s/user — B300 runs $0.61 per million tokens on Kimi K2.5/K2.6/K2.7-Code 1T while MI355X runs $0.66. B300 is the cheaper choice by 8%.
On Kimi K2.5/K2.6/K2.7-Code 1T at 74 tok/s/user, the per-million math comes out to $0.70 for B300 and $0.80 for MI355X; B300 delivers 13% more output per dollar.
At 94 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T, B300 costs $0.72 per million tokens; MI355X costs $1.04. B300 is 45% more cost-efficient at this operating point. (Numbers reflect the default 1k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
GPU pricing (owning hyperscaler): B300 $2.34/GPU/hr · MI355X $1.48/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 | B300:$0.612MI355X:$0.658 | B300:$0.704MI355X:$0.797 | B300:$0.715MI355X:$1.040 |
| Concurrency | B300:~40MI355X:~24 | B300:~26MI355X:~14 | B300:~21MI355X:~9 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.