DeepSeek V4 Pro 1.6T — B300 vs GB200 NVL72
Head-to-head AI inference benchmark comparison of B300 (NVIDIA Blackwell) and GB200 NVL72 (NVIDIA Blackwell) on DeepSeek V4 Pro 1.6T. 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 6–203 tok/s/user interactivity band, at 55 tok/s/user on DeepSeek V4 Pro 1.6T: B300 runs 7972 tok/s/GPU at $0.08/M tokens, GB200 NVL72 runs 9497 at $0.06/M. GB200 NVL72 is 26% cheaper per token; GB200 NVL72 delivers 19% more tok/s/GPU.
Setting 105 tok/s/user as the target on DeepSeek V4 Pro 1.6T, B300 produces 2197 tok/s/GPU ($0.29 per million tokens) and GB200 NVL72 produces 6644 ($0.09). GB200 NVL72 is 211% cheaper per token; GB200 NVL72 delivers 202% more tok/s/GPU.
At 154 tok/s/user interactivity on DeepSeek V4 Pro 1.6T, B300 delivers 1067 tok/s/GPU at $0.61 per million tokens; GB200 NVL72 delivers 526 tok/s/GPU at $1.17. B300 is 92% cheaper per token; B300 delivers 103% more tok/s/GPU at this point. (Numbers reflect the default 8k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | B300:7971.9GB200 NVL72:9497.1 | B300:2196.9GB200 NVL72:6644.2 | B300:1067.1GB200 NVL72:525.8 |
| Cost ($/M tok) | B300:$0.082GB200 NVL72:$0.065 | B300:$0.288GB200 NVL72:$0.093 | B300:$0.609GB200 NVL72:$1.169 |
| tok/s/MW | B300:4195758GB200 NVL72:5078682 | B300:1156280GB200 NVL72:3553038 | B300:561636GB200 NVL72:281160 |
| Concurrency | B300:~1012GB200 NVL72:~16349 | B300:~194GB200 NVL72:~2152 | B300:~32GB200 NVL72:~45 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.