Anthropic signs $35B cloud deal with Nvidia-backed provider

US artificial intelligence company Anthropic has signed a $35 billion cloud-computing agreement with Lambda, a cloud provider backed by chipmaker Nvidia, as it expands its computing capacity for AI development, the Wall Street Journal reported.

The agreement will give Anthropic access to computing infrastructure at a data center under development in Nueces County, Texas, according to the newspaper.

The facility, being developed by Hut 8, is expected to have about 350 megawatts of capacity, the Wall Street Journal reported.

The Lambda deal will bring Nvidia capacity online to meet growing demand for Anthropic’s Claude AI models, according to a source cited by the newspaper.

Nvidia is an investor in Lambda and supplies chips used by the cloud provider, according to the report. The chipmaker also holds the lease on the Texas data center.

Hut 8 announced in July that it had signed a 15-year lease with an investment-grade customer for part of its 1-gigawatt Beacon Point campus in Texas.

The base-term contract was valued at $19.6 billion, and Nvidia was later identified as the tenant, according to the report.

The Lambda agreement is part of Anthropic’s broader effort to secure computing capacity as demand grows for its Claude AI models and Claude Code coding assistant.

Anthropic has also agreed to spend $45 billion over six years to rent computing capacity from Nscale at a data center under development in West Virginia, according to the Wall Street Journal.

The facility is expected to provide 460 megawatts of capacity using Nvidia’s next-generation processors.
Anthropic has also committed more than $100 billion over 10 years to Amazon Web Services for up to 5 gigawatts of additional computing capacity, the newspaper reported.

The company uses computing resources from multiple providers and chipmakers, including Nvidia, Google and Amazon, according to the report.

The agreements come as AI companies seek data centers, electricity and advanced processors needed to train and operate increasingly powerful AI models.