Qwen 3.5 397B-A17B — GB200 NVL72 vs GB300 NVL72
Head-to-head AI inference benchmark comparison of GB200 NVL72 (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 67 tok/s/user on Qwen 3.5 397B-A17B: GB200 NVL72 hits 1119 tok/s/GPU, GB300 NVL72 hits 1427. Per-million costs land at $0.56 and $0.53 respectively. GB300 NVL72 is 6% cheaper per token; GB300 NVL72 delivers 28% more tok/s/GPU.
GB200 NVL72 / GB300 NVL72 on Qwen 3.5 397B-A17B at 103 tok/s/user: 448 / 569 tok/s/GPU, $1.35 / $1.27 per million tokens. GB300 NVL72 is 7% cheaper per token; GB300 NVL72 delivers 27% more tok/s/GPU.
Toward the upper edge of the 32–173 tok/s/user interactivity band, at 138 tok/s/user on Qwen 3.5 397B-A17B: GB200 NVL72 runs 201 tok/s/GPU at $3.06/M tokens, GB300 NVL72 runs 323 at $2.27/M. GB300 NVL72 is 35% cheaper per token; GB300 NVL72 delivers 61% more tok/s/GPU. (Numbers reflect the default 1k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | GB200 NVL72:1118.6GB300 NVL72:1426.7 | GB200 NVL72:447.7GB300 NVL72:568.8 | GB200 NVL72:200.6GB300 NVL72:323.0 |
| Cost ($/M tok) | GB200 NVL72:$0.557GB300 NVL72:$0.526 | GB200 NVL72:$1.350GB300 NVL72:$1.267 | GB200 NVL72:$3.057GB300 NVL72:$2.268 |
| tok/s/MW | GB200 NVL72:598208GB300 NVL72:672979 | GB200 NVL72:239399GB300 NVL72:268281 | GB200 NVL72:107251GB300 NVL72:152342 |
| Concurrency | GB200 NVL72:~79GB300 NVL72:~147 | GB200 NVL72:~19GB300 NVL72:~24 | GB200 NVL72:~6GB300 NVL72:~10 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.