Kimi K2.5/K2.6/K2.7-Code 1T · GPU comparison

Kimi K2.5/K2.6/K2.7-Code 1T — B200 vs GB300 NVL72

Head-to-head AI inference benchmark comparison of B200 (NVIDIA Blackwell) and GB300 NVL72 (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.

Throughput at 68 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T: B200 hits 785 tok/s/GPU, GB300 NVL72 hits 6017. Per-million costs land at $0.68 and $0.12 respectively. GB300 NVL72 is 457% cheaper per token; GB300 NVL72 delivers 667% more tok/s/GPU.

B200 / GB300 NVL72 on Kimi K2.5/K2.6/K2.7-Code 1T at 102 tok/s/user: 415 / 621 tok/s/GPU, $1.30 / $1.20 per million tokens. GB300 NVL72 is 9% cheaper per token; GB300 NVL72 delivers 50% more tok/s/GPU.

Toward the upper edge of the 35–169 tok/s/user interactivity band, at 136 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T: B200 runs 207 tok/s/GPU at $2.73/M tokens, GB300 NVL72 runs 223 at $3.30/M. B200 is 21% cheaper per token; GB300 NVL72 delivers 8% more tok/s/GPU. (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.)

View performance-per-dollar view →

Interpolated from real benchmark data. Edit target interactivity values below to compare at different operating points.
Metric
Interactivity (tok/s/user)
Interactivity (tok/s/user)
Interactivity (tok/s/user)
Throughput (tok/s/gpu)
B200:784.9GB300 NVL72:6016.8
B200:414.9GB300 NVL72:621.5
B200:206.7GB300 NVL72:223.1
Cost ($/M tok)
B200:$0.684GB300 NVL72:$0.123
B200:$1.303GB300 NVL72:$1.199
B200:$2.733GB300 NVL72:$3.302
tok/s/MW
B200:459022GB300 NVL72:2838109
B200:242621GB300 NVL72:293151
B200:120905GB300 NVL72:105249
Concurrency
B200:~24GB300 NVL72:~2093
B200:~8GB300 NVL72:~135
B200:~3GB300 NVL72:~30

Inference Performance

Inference performance metrics across different models, hardware configurations, and serving parameters.

Vendor:
Aggregation:
Spec Decoding: