Qwen 3.5 397B-A17B — B200 vs GB300 NVL72
Head-to-head AI inference benchmark comparison of B200 (NVIDIA Blackwell) and GB300 NVL72 (NVIDIA Blackwell) on Qwen 3.5 397B-A17B. 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 113 tok/s/user on Qwen 3.5 397B-A17B: B200 hits 7828 tok/s/chip, GB300 NVL72 hits 19296. Per-million costs land at $0.06 and $0.03 respectively. GB300 NVL72 is 85% cheaper per token; GB300 NVL72 delivers 146% more tok/s/chip.
B200 / GB300 NVL72 on Qwen 3.5 397B-A17B at 182 tok/s/user: 5087 / 10297 tok/s/chip, $0.10 / $0.06 per million tokens. GB300 NVL72 is 51% cheaper per token; GB300 NVL72 delivers 102% more tok/s/chip.
Toward the upper edge of the 44–320 tok/s/user interactivity band, at 252 tok/s/user on Qwen 3.5 397B-A17B: B200 runs 3039 tok/s/chip at $0.16/M tokens, GB300 NVL72 runs 5122 at $0.13/M. GB300 NVL72 is 28% cheaper per token; GB300 NVL72 delivers 69% more tok/s/chip. (Numbers reflect the default 8k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/chip) | B200:7828.4GB300 NVL72:19295.9 | B200:5086.7GB300 NVL72:10296.9 | B200:3038.5GB300 NVL72:5122.2 |
| Cost ($/M tok) | B200:$0.061GB300 NVL72:$0.033 | B200:$0.095GB300 NVL72:$0.063 | B200:$0.163GB300 NVL72:$0.127 |
| tok/s/MW | B200:4578039GB300 NVL72:9101834 | B200:2974687GB300 NVL72:4857028 | B200:1776909GB300 NVL72:2416149 |
| Concurrency | B200:~21GB300 NVL72:~1030 | B200:~7GB300 NVL72:~459 | B200:~4GB300 NVL72:~91 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.