Anthropic has reportedly reached a six-year agreement with AI cloud infrastructure provider Nscale, planning to pay $45 billion to lease AI computing power at the Monarch data center campus in West Virginia, corresponding to approximately 460 megawatts of power capacity. The agreement has not yet been publicly announced by either party, with details coming from informed sources.

Nscale will deploy Nvidia's next-generation Vera Rubin chips for Anthropic, with the first capacity expected to come online by the end of 2027. The deal aims to secure long-term computing power for products like Claude and Claude Code, anticipating demand growth rather than just for one-time model training.

460 megawatts is roughly equivalent to the simultaneous electricity usage of 345,000 American households; based on a rough calculation of $45 billion over six years, Anthropic's average annual commitment is about $7.5 billion. This amount may include computing power, chips, data center facilities, electricity, networking, operations, and long-term capacity reservations, rather than just a simple "electricity bill" paid to Nscale.

The complete Monarch campus that Nscale plans to build will have a total capacity of about 1.35 gigawatts, including three data center buildings and on-site power generation facilities, with an overall development cost estimated at around $71 billion, of which about $47 billion will be used to procure AI chips. The agreement with Anthropic covers the first building, while the remaining facilities are expected to gradually provide capacity starting in 2028.

This project was originally planned to be leased by Microsoft. Microsoft signed a letter of intent for the campus in March this year but withdrew in the summer, after which Anthropic became the main potential tenant; this indicates that Nscale is shifting from a single large cloud customer to a cutting-edge model company as a long-term demand anchor.

For Anthropic, securing 460 megawatts long-term helps reduce the risks of model training delays due to insufficient computing power, API limits, and obstacles to enterprise product expansion, but it also brings significant fixed costs and utilization risks: if model demand, prices, chip performance, or product revenues fall below expectations, the computing power commitment could become a cash flow pressure.

From a market mechanism perspective, the deal transfers funds from model companies to the GPU supply chain, data center construction, substations and power generation facilities, networking equipment, cooling systems, and cloud operations services. Nvidia and data center operators with access to electricity, land, financing capabilities, and long-term customer contracts will benefit; small cloud service providers lacking power and construction permits will face pressure, and competition in cutting-edge models will increasingly rely on long-term capital and infrastructure locking capabilities.

Source: Public Information