Qwen 3.5 397B-A17B — GB300 NVL72 vs H200
Head-to-head AI inference benchmark comparison of GB300 NVL72 (NVIDIA Blackwell) and H200 (NVIDIA Hopper) 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.
Near the low end of the 32–182 tok/s/user interactivity band, at 69 tok/s/user on Qwen 3.5 397B-A17B: GB300 NVL72 runs 1334 tok/s/GPU at $0.56/M tokens, H200 runs 485 at $0.81/M. GB300 NVL72 is 43% cheaper per token; GB300 NVL72 delivers 175% more tok/s/GPU.
Setting 107 tok/s/user as the target on Qwen 3.5 397B-A17B, GB300 NVL72 produces 533 tok/s/GPU ($1.35 per million tokens) and H200 produces 349 ($1.11). H200 is 22% cheaper per token; GB300 NVL72 delivers 53% more tok/s/GPU.
At 145 tok/s/user interactivity on Qwen 3.5 397B-A17B, GB300 NVL72 delivers 286 tok/s/GPU at $2.57 per million tokens; H200 delivers 282 tok/s/GPU at $1.39. H200 is 85% cheaper per token; GB300 NVL72 delivers 2% more tok/s/GPU at this point. (Numbers reflect the default 1k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | GB300 NVL72:1333.9H200:485.3 | GB300 NVL72:533.4H200:348.8 | GB300 NVL72:286.3H200:282.0 |
| Cost ($/M tok) | GB300 NVL72:$0.563H200:$0.807 | GB300 NVL72:$1.351H200:$1.108 | GB300 NVL72:$2.568H200:$1.387 |
| tok/s/MW | GB300 NVL72:629190H200:354252 | GB300 NVL72:251625H200:254569 | GB300 NVL72:135068H200:205835 |
| Concurrency | GB300 NVL72:~113H200:~28 | GB300 NVL72:~21H200:~13 | GB300 NVL72:~9H200:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.