Qwen 3.5 397B-A17B — B300 vs H200
Head-to-head AI inference benchmark comparison of B300 (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.
Throughput at 68 tok/s/user on Qwen 3.5 397B-A17B: B300 hits 2918 tok/s/chip, H200 hits 490. Per-million costs land at $0.21 and $0.69 respectively. B300 is 224% cheaper per token; B300 delivers 495% more tok/s/chip.
B300 / H200 on Qwen 3.5 397B-A17B at 106 tok/s/user: 1559 / 351 tok/s/chip, $0.40 / $0.95 per million tokens. B300 is 138% cheaper per token; B300 delivers 344% more tok/s/chip.
Toward the upper edge of the 30–182 tok/s/user interactivity band, at 144 tok/s/user on Qwen 3.5 397B-A17B: B300 runs 1036 tok/s/chip at $0.60/M tokens, H200 runs 284 at $1.19/M. B300 is 97% cheaper per token; B300 delivers 264% more tok/s/chip. (Numbers reflect the default 1k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/chip) | B300:2918.4H200:490.2 | B300:1559.2H200:351.0 | B300:1035.7H200:284.4 |
| Cost ($/M tok) | B300:$0.213H200:$0.691 | B300:$0.401H200:$0.954 | B300:$0.604H200:$1.188 |
| tok/s/MW | B300:1535980H200:357804 | B300:820613H200:256186 | B300:545081H200:207582 |
| Concurrency | B300:~87H200:~29 | B300:~31H200:~13 | B300:~15H200:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.