哥伦比亚商学院测算：美国新增 182.7 GW 数据中心需要多少收入支撑
哥大商学院算了笔账：7700万块 GPU 要赚回 3.725 万亿，摊下来每 GPU 小时 5.5 美元，比现在租价还低，基建账能算平。
哥伦比亚商学院报告《Financing the AI Buildout》测算，2025 至 2032 年美国数据中心将新增 182.
7 GW 容量。按 GB300 NVL72 配置折算，相当于约 107 万个机架、7700 万块 GPU。
要撑起这一建设规模，需要每年 3.725 万亿美元的成熟期收入，约合每 GPU 小时 5.
5 美元（满载）。这一数字落在当前 NVIDIA 高端算力 6 至 10 美元以上的每 GPU 小时租价区间之下，说明中心情景在现有算力价格下算术上成立。
How much revenue each unit of deployed compute would need to generate for 182.7 GW of additional U.S. data-center capacity between 2025 and 2032
This Columbia Business School report "Financing the AI Buildout" ans that.
182.7 GW is its central buildout scenario which is the U.S. data-center capacity between 2025 and 2032.
Using the GB300 NVL72 configuration, that capacity works out to roughly 1.07 million racks / 77 million GPUs, which lets the author express the required $3.725 trillion of mature annual revenue as about $5.5 per installed GPU-hour at full utilization.
This required unit revenue sits within the $6–$10+ per GPU-hour for current high-end NVIDIA capacity, so the central scenario does not require some radically higher compute price to make the arithmetic work.
This report is categorized under AITOP's "Papers" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include GB300 NVL72, NVIDIA, 数据中心, AI算力.
Source attribution: curated from rohanpaul_ai (@rohanpaul_ai). Cross-source corroboration: 9 independent sources have covered this development (including IT之家, @cb_doge, Teortaxes), confirming industry-wide signal strength.
