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 98 tok/s/user on Qwen 3.5 397B-A17B: B200 hits 4410 tok/s/GPU, GB300 NVL72 hits 9634. Per-million costs land at $0.12 and $0.08 respectively. GB300 NVL72 is 61% cheaper per token; GB300 NVL72 delivers 118% more tok/s/GPU.
B200 / GB300 NVL72 on Qwen 3.5 397B-A17B at 157 tok/s/user: 3050 / 3613 tok/s/GPU, $0.18 / $0.20 per million tokens. B200 is 14% cheaper per token; GB300 NVL72 delivers 18% more tok/s/GPU.
Toward the upper edge of the 40–273 tok/s/user interactivity band, at 215 tok/s/user on Qwen 3.5 397B-A17B: B200 runs 2189 tok/s/GPU at $0.24/M tokens, GB300 NVL72 runs 1757 at $0.42/M. B200 is 74% cheaper per token; B200 delivers 25% more tok/s/GPU. (Numbers reflect the default 8k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | B200:4409.5GB300 NVL72:9633.6 | B200:3050.2GB300 NVL72:3612.5 | B200:2189.5GB300 NVL72:1756.9 |
| Cost ($/M tok) | B200:$0.123GB300 NVL72:$0.077 | B200:$0.176GB300 NVL72:$0.201 | B200:$0.243GB300 NVL72:$0.422 |
| tok/s/MW | B200:2578660GB300 NVL72:4544142 | B200:1783766GB300 NVL72:1704032 | B200:1280403GB300 NVL72:828743 |
| Concurrency | B200:~22GB300 NVL72:~757 | B200:~10GB300 NVL72:~55 | B200:~5GB300 NVL72:~14 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.