July 6, 2026|By LDS Team

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Long-duration infrastructure contracts materially change where and how organizations secure large-scale training and inference capacity, which affects cost, reliability, and vendor selection for MLOps teams. According to TeraWulf's press release, Anthropic executed a 20-year lease for a purpose-built AI infrastructure campus at the Justified Data site in Hawesville, Kentucky, a deal TeraWulf says is expected to generate roughly $19 billion of contracted revenue over the initial term. The press release states the campus will accommodate about 401 MW of critical IT load, with initial capacity expected in the second half of 2027 and full capacity by early 2028. Reuters and CNBC report TeraWulf also agreed to sell its 50.1% stake in the Abernathy joint venture to a group led by Fluidstack, monetizing about $450 million of prior investment, and that TeraWulf shares rose in early trading after the announcement.

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What happened

According to TeraWulf's July 6 press release, TeraWulf has executed a 20-year lease with Anthropic for a purpose-built AI infrastructure campus at the Justified Data site in Hawesville, Kentucky. The press release states the lease is expected to generate approximately $19 billion of contracted revenue over the initial lease term and that the campus will accommodate about 401 MW of critical IT load. The company said initial capacity is expected to be placed into service in the second half of 2027, with the campus ramping to full 401 MW by early 2028. The release also says the lease is expected to be supported by an investment-grade credit.

Per TeraWulf's release and reporting by Reuters and CNBC, TeraWulf simultaneously agreed to sell its 50.1% ownership interest in the Abernathy joint venture to an investor group led by Fluidstack, monetizing roughly $450 million of invested capital at a premium and freeing capital for wholly owned infrastructure projects. Reuters and CNBC reported that TeraWulf shares rose sharply in early trading after the announcement, with premarket jumps reported by CNBC and a Reuters story noting share gains that morning. Local coverage in the Courier-Journal highlights the site's history as a former Century Aluminum smelter and reports both estimated local tax benefits and community concerns over environmental and infrastructure impacts.

Editorial analysis - technical context

From a technical perspective, 401 MW of critical IT load is sufficient to host multiple exascale-class training clusters or very large inference farms. Industry-pattern observations note that campuses with integrated long-term power procurement, substations, and high-density cooling enable operators and tenants to run sustained high-PUE workloads and oversized GPU pod deployments that are difficult to assemble in smaller colocation facilities. For practitioners, that means access to predictable, colocated high-density racks and bulk power, which can reduce the operational complexity of scaling training runs that demand sustained power and thermal headroom.

Editorial analysis - business and market context

Reporting by TeraWulf and major business outlets frames the transaction as part of TeraWulf's shift from crypto-mining toward AI infrastructure development. Industry observers have increasingly tracked large AI tenants securing long-duration capacity as a way to stabilize costs and ensure supply for model training. For market-facing teams and SREs, the rise of specialized AI campuses expands choices: hyperscalers, cloud providers, and third-party campus operators are now overlapping product sets for long-term capacity and power arrangements.

Context and significance

Large, multi-hundred-megawatt campuses materially increase regional electricity demand and typically require long-term power contracts or on-site generation. Local reporting notes projected economic benefits such as tax contributions, while also recording community and environmental concerns, per the Courier-Journal. Observers following data-center buildouts will watch how power sourcing, permitting, and grid upgrades proceed, since those are common gating items that affect actual project timelines.

What to watch

Industry context

Key indicators to monitor include:

• •confirmation of power purchase agreements or on-site generation commitments
• •permitting and interconnection milestones that would validate the 2027-2028 schedule reported by TeraWulf
• •whether Anthropic discloses additional tenancy details or capacity milestones
• •whether other AI labs sign comparable long-duration deals, which would indicate a broader shift toward contracted campus capacity. Market teams should also track how the Abernathy JV sale proceeds are redeployed, as TeraWulf states the proceeds are intended to fund wholly owned infrastructure expansion per the company release

Editorial analysis

For ML engineers and infrastructure teams, long-term, high-capacity leases reshape procurement choices and capacity planning. Enterprises and labs that secure multi-year bulk power and rack capacity can lock in predictable throughput for large-scale training runs and inference fleets, while operators that sell such capacity change the market dynamics for spot versus contracted compute.

For practitioners building or buying ML infrastructure, the practical takeaway is that long-duration, high-density campuses lower uncertainty for very large workloads but come with lock-in tradeoffs. Teams should balance the benefits of predictable capacity and power economics against contractual flexibility, geographic latency, and the operational model of colocated campuses versus cloud or on-prem alternatives.

Key Points

• 1Long-term, high-capacity leases reduce supply volatility, making multi-PB training schedules and large inference fleets easier to provision for ML teams.
• 2A 401 MW campus with multi-year contracts shifts cost and risk from spot markets to contracted operators, altering cloud vs. colocation comparisons.
• 3Regional grid and permitting progress will be the critical path for actual capacity delivery; practitioners should watch interconnection and PPA milestones.

Scoring Rationale

This is a large, multi-year infrastructure commitment that materially affects available AI compute capacity and procurement dynamics for large model training and inference. The scale and contracted revenue make it a notable market signal for AI infrastructure supply.