Qwen 3.5 397B-A17B — B300 vs GB300 NVL72
Head-to-head AI inference benchmark comparison of B300 (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.
B300 / GB300 NVL72 on Qwen 3.5 397B-A17B at 75 tok/s/user: 2633 / 1084 tok/s/GPU, $0.25 / $0.68 per million tokens. B300 is 176% cheaper per token; B300 delivers 143% more tok/s/GPU.
Around the middle of the 32–206 tok/s/user interactivity band, at 119 tok/s/user on Qwen 3.5 397B-A17B: B300 runs 1313 tok/s/GPU at $0.49/M tokens, GB300 NVL72 runs 447 at $1.65/M. B300 is 238% cheaper per token; B300 delivers 194% more tok/s/GPU.
Setting 163 tok/s/user as the target on Qwen 3.5 397B-A17B, B300 produces 877 tok/s/GPU ($0.73 per million tokens) and GB300 NVL72 produces 208 ($3.46). B300 is 372% cheaper per token; B300 delivers 322% more tok/s/GPU. (Numbers reflect the default 1k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | B300:2633.5GB300 NVL72:1083.9 | B300:1313.4GB300 NVL72:446.9 | B300:877.3GB300 NVL72:207.7 |
| Cost ($/M tok) | B300:$0.246GB300 NVL72:$0.677 | B300:$0.487GB300 NVL72:$1.648 | B300:$0.733GB300 NVL72:$3.463 |
| tok/s/MW | B300:1386049GB300 NVL72:511290 | B300:691245GB300 NVL72:210784 | B300:461724GB300 NVL72:97959 |
| Concurrency | B300:~73GB300 NVL72:~63 | B300:~23GB300 NVL72:~16 | B300:~11GB300 NVL72:~5 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.