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8-K2026-07-20· deepseek-v4-flash

HUT · Hut 8 Corp.

0001104659-26-084862

SEC filing

Summary

Hut 8 Corp. fully commercialized its 1 GW Beacon Point data center campus by signing a second 15-year, $9.8 billion lease for 352 MW, doubling its tenant's contracted capacity.

Key takeaways

Full analysis

Hut 8 Corp. announced the commercialization of the second phase of its 1 GW Beacon Point data center campus in Nueces County, Texas, through a second 15-year, $9.8 billion lease with the same high-investment-grade tenant that executed the Phase 1 lease. The transaction doubles the tenant's contracted IT capacity at the campus to 704 MW, fully utilizing the campus's 1,000 MW of utility capacity secured under an interconnection agreement with AEP Texas. The lease is structured on substantially the same triple-net terms as Phase 1, including a 3.0% annual base rent escalator, with three 5-year renewal options that could increase campus-level contract value to $50.2 billion if exercised.

The transaction underscores Hut 8's power-first development model, where the company originates sites with secured power, then contracts them to investment-grade tenants. The Beacon Point campus was initially underwritten for bitcoin mining but was pivoted to AI leasing, demonstrating flexibility. Hut 8 will deliver a second 352 MW AI factory designed to NVIDIA's DSX reference architecture, with initial data hall delivery expected in Q2 2028. Site preparation is underway, and long-lead critical equipment has been procured, with initial energization on schedule for Q1 2027.

With this lease, Hut 8's total contracted IT capacity across its AI data center portfolio rises to 949 MW (including 245 MW at River Bend), with an aggregate base-term contract value of $26.6 billion and expected average annual NOI of more than $1.75 billion. All of the company's contracted AI data center capacity is leased to or backstopped by investment-grade counterparties, providing strong credit support. The transaction validates Hut 8's disciplined approach and positions it to apply the same model to its development pipeline.