Qwen 3.5 397B-A17B — GB200 NVL72 vs H200
Head-to-head AI inference benchmark comparison of GB200 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.
GB200 NVL72 / H200 on Qwen 3.5 397B-A17B at 64 tok/s/user: 1239 / 510 tok/s/GPU, $0.51 / $0.77 per million tokens. GB200 NVL72 is 52% cheaper per token; GB200 NVL72 delivers 143% more tok/s/GPU.
Around the middle of the 28–173 tok/s/user interactivity band, at 101 tok/s/user on Qwen 3.5 397B-A17B: GB200 NVL72 runs 464 tok/s/GPU at $1.30/M tokens, H200 runs 363 at $1.07/M. H200 is 21% cheaper per token; GB200 NVL72 delivers 28% more tok/s/GPU.
Setting 137 tok/s/user as the target on Qwen 3.5 397B-A17B, GB200 NVL72 produces 206 tok/s/GPU ($2.98 per million tokens) and H200 produces 299 ($1.29). H200 is 131% cheaper per token; H200 delivers 45% more tok/s/GPU. (Numbers reflect the default 1k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | GB200 NVL72:1239.3H200:510.5 | GB200 NVL72:463.7H200:363.4 | GB200 NVL72:205.8H200:298.9 |
| Cost ($/M tok) | GB200 NVL72:$0.506H200:$0.767 | GB200 NVL72:$1.297H200:$1.072 | GB200 NVL72:$2.983H200:$1.292 |
| tok/s/MW | GB200 NVL72:662711H200:372593 | GB200 NVL72:247968H200:265257 | GB200 NVL72:110068H200:218175 |
| Concurrency | GB200 NVL72:~113H200:~32 | GB200 NVL72:~20H200:~15 | GB200 NVL72:~7H200:~9 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.