英伟达：AI数据中心最多70%电力用于AI计算
在Vertiv年度EMEA活动上，英伟达负责超级计算与AI云基础设施的副总裁Rod Evans表示，一座AI数据中心从电网取电后，最多只有70%用于AI处理，其余30%属于低效损耗：其中20%损失在冷却、配电与电力转换上，另有10%损失于配置不当的机架、故障与重启。TechRadar指出，该报道标题称这一比例低至60%，而正文给出的上限为70%。英伟达与Vertiv自2026年初起合作设计新一代数据中心，双方称部分损耗可通过更优设计回收，并认为并网接电而非芯片短缺已成为AI数据中心容量的主要瓶颈。
报道中的英伟达与Vertiv高管称，制约AI数据中心容量的主要瓶颈已从芯片短缺转为电网接入，部分设施需等待数年才能获得与其容量匹配的电力。
- Nvidia claims that for each gigawatt an AI data center uses, only 70% is used for AI work
- Inefficiencies include cooling and power distribution, failures, and restarts
- While a chip shortage was considered to be the main bottleneck to AI data center capacity, it is now a facility’s connection to the grid
AI data centers are inefficient, says Nvidia, with various physical and systems issues contributing to power use beyond AI processing. This opinion, shared by data center builder Vertiv at its recent annual EMEA event, underpins future development steps, in which it plans to assemble sustainable facilities.
Vertiv and Nvidia have been collaborating since early 2026 on co-designing the next generation of data centers, with Vertiv providing power and infrastructure management for Nvidia’s GPUs.
With a maximum of 70% of electricity drawn from the grid used for AI processing, the remaining 30% represents inefficiencies that optimized data center designs for the future should reduce.
That's not efficient
Although the various inefficiencies affecting AI data centers may not come as a surprise, the scale of them might. According to Nvidia – via its Vice President of Supercomputing, AI Cloud Infrastructure, and AI/HPC for EMEA Rod Evans – that 30% consists of infrastructure and system issues.