DeepSeek V4 Pro 1.6T — B200 vs GB200 NVL72 Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) versus GB200 NVL72 (NVIDIA Blackwell) on DeepSeek V4 Pro 1.6T. Owning-hyperscaler TCO normalized by output tokens — performance per dollar across LLM workloads. Pick the more cost-efficient SKU at every target interactivity level. Use the chart controls below to switch sequences, precisions, and metrics — same interactions as the main inference chart.
At 64 tok/s/user on DeepSeek V4 Pro 1.6T, B200 costs $0.07 per million tokens; GB200 NVL72 costs $0.06. GB200 NVL72 is 24% more cost-efficient at this operating point.
GB200 NVL72 edges B200 at 111 tok/s/user on DeepSeek V4 Pro 1.6T — $0.08 per million tokens versus $0.26, a 204% cost-per-token gap.
Push DeepSeek V4 Pro 1.6T to 157 tok/s/user and B200 lands at $0.78 per million tokens against GB200 NVL72's $0.99 — B200 pulls ahead by 27%. (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.)
Chip pricing (owning hyperscaler): B200 $1.73/chip/hr · GB200 NVL72 $1.86/chip/hr. Source: SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model.
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Dollar per Million Tokens | B200:$0.070GB200 NVL72:$0.057 | B200:$0.258GB200 NVL72:$0.085 | B200:$0.778GB200 NVL72:$0.990 |
| Concurrency | B200:~560GB200 NVL72:~9943 | B200:~166GB200 NVL72:~1815 | B200:~7GB200 NVL72:~41 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.