Kimi K2.5/K2.6/K2.7-Code 1T — B300 vs MI355X
Head-to-head AI inference benchmark comparison of B300 (NVIDIA Blackwell) and MI355X (AMD CDNA 4) on Kimi K2.5/K2.6/K2.7-Code 1T. Latency, throughput, and cost across LLM workloads. Use the chart controls below to switch sequences, precisions, and metrics — same interactions as the main inference chart.
B300 / MI355X on Kimi K2.5/K2.6/K2.7-Code 1T at 46 tok/s/user: 3230 / 3375 tok/s/GPU, $0.20 / $0.12 per million tokens. MI355X is 65% cheaper per token; MI355X delivers 4% more tok/s/GPU.
Around the middle of the 21–123 tok/s/user interactivity band, at 72 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T: B300 runs 2997 tok/s/GPU at $0.22/M tokens, MI355X runs 2329 at $0.18/M. MI355X is 23% cheaper per token; B300 delivers 29% more tok/s/GPU.
Setting 97 tok/s/user as the target on Kimi K2.5/K2.6/K2.7-Code 1T, B300 produces 2667 tok/s/GPU ($0.24 per million tokens) and MI355X produces 1679 ($0.24). B300 is 1% cheaper per token; B300 delivers 59% more tok/s/GPU. (Numbers reflect the default 8k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | B300:3230.2MI355X:3374.8 | B300:2996.7MI355X:2328.9 | B300:2667.2MI355X:1678.9 |
| Cost ($/M tok) | B300:$0.201MI355X:$0.122 | B300:$0.218MI355X:$0.176 | B300:$0.242MI355X:$0.244 |
| tok/s/MW | B300:1700084MI355X:1614723 | B300:1577232MI355X:1114285 | B300:1403774MI355X:803323 |
| Concurrency | B300:~34MI355X:~37 | B300:~21MI355X:~15 | B300:~14MI355X:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.