DeepSeek V4 Pro 1.6T — GB300 NVL72 vs H200 Performance per Dollar
Cost per million tokens of GB300 NVL72 (NVIDIA Blackwell) versus H200 (NVIDIA Hopper) 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.
H200 costs $1.85 per million tokens at 45 tok/s/user on DeepSeek V4 Pro 1.6T; we have no GB300 NVL72 benchmark data at this exact target.
At 87 tok/s/user on DeepSeek V4 Pro 1.6T, H200 comes in at $4.26 per million tokens. GB300 NVL72 hasn't been benchmarked at this operating point.
Only H200 has cost data at 128 tok/s/user on DeepSeek V4 Pro 1.6T — $6.36 per million tokens. GB300 NVL72 is unmeasured at this target. (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.)
GPU pricing (owning hyperscaler): GB300 NVL72 $2.65/GPU/hr · H200 $1.41/GPU/hr. Source: SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model.
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Dollar per Million Tokens | GB300 NVL72:—H200:$1.851 | GB300 NVL72:—H200:$4.262 | GB300 NVL72:—H200:$6.362 |
| Concurrency | GB300 NVL72:—H200:~20 | GB300 NVL72:—H200:~5 | GB300 NVL72:—H200:~2 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.