Bernstein breaks down AI infrastructure costs: up to $39.5 billion investment per gigawatt.

PANews October 10 news: A Bernstein research report shows that using different AI accelerator architectures, the capital expenditure required to build a 1GW data center is approximately $34.6 billion to $39.5 billion. Among them, Nvidia's Vera Rubin architecture has the highest construction cost, while OpenAI's self-developed ASIC architecture Jalapeno is relatively lower. Bernstein significantly lowered its cost estimate for a single Nvidia Rubin NVL72 rack from the previous $9.1 million to $7.52 million, a decrease of about 17%, mainly reflecting adjustments to expectations for HBM prices and NAND storage capacity. The research report also points out that the main economic burden of AI data centers is not electricity costs, but the massive capital expenditure and the depreciation it generates.