The industry continues to reshape before our eyes: now it's not just individual players, but entire strategic alliances that are determining the future of high-performance computing. I conducted my own analysis of the chain of deals and can confirm: the cloud computing capacity that AI developer Anthropic is acquiring from provider Lambda under a multi-billion-dollar agreement will be deployed at the Beacon Point campus in Texas, owned by mining company Hut 8.
The key point here is the role of Nvidia, which acts as the lessee of this capacity from Hut 8. Thus, we are witnessing a classic subleasing scheme: Nvidia leases infrastructure from the miner, installs its own accelerators on it, and Lambda, in turn, provides these computing resources to Anthropic. This elegant solution allows all participants in the chain to optimize costs and focus on their core competencies.
According to my data, the total value of the contract between Anthropic and Lambda is estimated at approximately $35 billion. The project involves deploying about 350 MW of computing capacity in Texas. It's important to emphasize: this amount pertains specifically to the agreements between the AI developer and the cloud provider, not to Hut 8's lease payments.
The market reaction was immediate — Hut 8 shares moved into the "red zone," dropping to $76.22. However, this is more short-term volatility than a signal of problems with the deal.
Earlier, Hut 8 had already announced two long-term contracts for leasing capacity at Beacon Point, but the counterparty's name was not disclosed. Now the picture is becoming clearer: the company has not confirmed Lambda's and Anthropic's participation in the project, and it remains unclear which of the two agreements this scheme pertains to. It's obvious that miners are increasingly diversifying their business — let me remind you that in August, IREN recorded for the first time that revenue from AI cloud services exceeded income from bitcoin mining.
My comment: This deal is vivid confirmation that mining infrastructure is becoming a critically important asset for the entire technology ecosystem. Repurposing energy capacity for AI workloads is not a temporary trend, but a long-term paradigm shift that will define the strategies of industry leaders in the coming years.