Core Scientific, one of the largest U.S. bitcoin miners, is repurposing a major bitcoin mining site in Texas into a large-scale AI-focused data center campus, targeting about 1.5 GW of total infrastructure with roughly 1 GW intended to be rentable capacity for high-performance computing and AI clients. This shift reflects a broader strategic pivot by the company away from relying solely on bitcoin mining revenue and toward more stable, long-term leasing income from AI and cloud customers. According to company statements and local development disclosures, Core Scientific is working with a North Texas municipality to turn its existing bitcoin mining campus—about 40 miles northwest of Dallas—into a data center hub optimized for AI workloads, with an estimated $6.1 billion in property investment over time. The plan includes leasing roughly 78 acres with access to up to 394 MW of power initially, on top of broader ambitions to convert and expand its U.S. footprint toward roughly 1.5 GW of AI-ready data center infrastructure. This follows Core Scientific’s earlier deployments of high-performance computing capacity for AI startup CoreWeave, where the miner has already converted tens of megawatts of former bitcoin mining load to support GPU-heavy AI workloads. The move matters for both the crypto mining and AI infrastructure sectors. For Core Scientific, AI-oriented data centers and long-term colocation or leasing contracts offer potentially more predictable revenue than bitcoin mining, which is heavily exposed to bitcoin price cycles and halving events. At an industry level, the Texas conversion illustrates how large bitcoin miners—with existing access to substantial, often low-cost power, cooling systems, and fiber connectivity—are becoming a fast-track route to scale up AI data center capacity in power-constrained markets. It also highlights growing competition for grid resources in regions like Texas, where datacenter, crypto, and industrial loads are all vying for high-capacity interconnections.

AI-generated background, compiled from web sources — not editorial content.

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