Kimi K2.5/K2.6/K2.7-Code 1T — B200 vs B300
Head-to-head AI inference benchmark comparison of B200 (NVIDIA Blackwell) and B300 (NVIDIA Blackwell) 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.
Near the low end of the 9–173 tok/s/user interactivity band, at 50 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T: B200 runs 8178 tok/s/chip at $0.06/M tokens, B300 runs 3504 at $0.18/M. B200 is 195% cheaper per token; B200 delivers 133% more tok/s/chip.
Setting 91 tok/s/user as the target on Kimi K2.5/K2.6/K2.7-Code 1T, B200 produces 1746 tok/s/chip ($0.28 per million tokens) and B300 produces 1963 ($0.31). B200 is 13% cheaper per token; B300 delivers 12% more tok/s/chip.
At 132 tok/s/user interactivity on Kimi K2.5/K2.6/K2.7-Code 1T, B200 delivers 962 tok/s/chip at $0.50 per million tokens; B300 delivers 857 tok/s/chip at $0.72. B200 is 45% cheaper per token; B200 delivers 12% more tok/s/chip at this point. (Numbers reflect the default 8k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/chip) | B200:8178.4B300:3504.2 | B200:1745.8B300:1962.6 | B200:961.9B300:856.6 |
| Cost ($/M tok) | B200:$0.061B300:$0.179 | B200:$0.277B300:$0.315 | B200:$0.500B300:$0.724 |
| tok/s/MW | B200:4782716B300:1844337 | B200:1020964B300:1032938 | B200:562522B300:450830 |
| Concurrency | B200:~323B300:~32 | B200:~62B300:~10 | B200:~30B300:~3 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.