Core Scientific and AMD announced a 15-year $14 billion partnership adding 530 MW of AI capacity across five campuses, doubling Core Scientific's footprint to 1.1 GW.
Core Scientific has doubled its leased AI data center capacity to approximately 1.1 GW after signing a 15-year infrastructure agreement with AMD covering 530 MW across five campuses and representing more than $14 billion in potential base contracted revenue.
Announced alongside the company's second-quarter results on July 28, the agreement begins in 2027 and grants AMD exclusive rights to reserve up to an additional 2 GW of future capacity. Core Scientific said the initial deployment marks the first phase of what it expects will become a broader strategic relationship. The deployment will use Core Scientific facilities to host infrastructure built around AMD Instinct GPUs, EPYC processors, and the ROCm software platform for cloud providers, AI model developers and enterprise customers.
"Core Scientific's extensive portfolio of AI-ready data centers expands access to the infrastructure our customers need to deploy AMD AI solutions at scale," said Mathew Hein, AMD's chief strategy officer for corporate development.
According to Matt Kimball, vice president and principal analyst for data center technologies at Moor Insights & Strategy, the agreement is less about AMD becoming a data center landlord than removing one of the biggest barriers to deploying its AI accelerators. "It's not about selling accelerators at this point, it's about selling a deployment path," Kimball explained. He noted that AMD appears to be using its balance sheet to reduce deployment risk by supporting infrastructure capable of hosting high-density AI clusters, where power, liquid cooling and specialized facilities have become as important as the chips themselves.
Kimball cautioned against overstating the headline figures. The touted $14 billion represents base contracted revenue over 15 years rather than a single booking, while the additional 2 GW reflects reservation rights rather than firm customer commitments.
The AMD agreement expands Core Scientific's contracted AI portfolio to approximately 1.1 GW of leased customer power capacity, representing more than $24 billion in potential contracted revenue. As of mid-July, the company was billing customers for 437 MW of capacity, equivalent to an annualized colocation revenue run rate of approximately $635 million.
Core Scientific executives emphasized that execution will determine the next phase of AI infrastructure competition. "Value is not announced. It is delivered," CEO Adam Sullivan said during the company's earnings call. Sullivan noted that Core Scientific now has two AI customers, each committed to more than 500 MW across five campuses, providing greater customer diversification while validating the company's strategy of developing campuses before securing long-term tenants.
The company disclosed one of its clearest benchmarks for building AI infrastructure. Chief Operating Officer Matt Brown said fully delivered AI data center capacity is expected to cost approximately $11 million to $12 million per megawatt, including construction, electrical infrastructure, cooling systems, commissioning and utility integration. At that rate, the initial AMD deployment represents roughly $6 billion of infrastructure investment.
Construction is underway at the company's Pecos, Texas campus, with deliveries scheduled to begin in the first half of 2027. Development is also progressing at Hunt, Texas; Muskogee, Oklahoma; Auburn, Alabama; and Dalton, Georgia, with deployments continuing through 2028.
The expansion underscores how quickly Core Scientific has transformed its business. Colocation revenue climbed to $136.7 million in the second quarter from $10.6 million a year earlier, while digital asset self-mining revenue fell to $21.5 million as the company continued shifting power from bitcoin mining to AI workloads.
To support future growth, Sullivan said Core Scientific has identified more than 2 GW of additional development opportunities that could begin coming online between late 2028 and 2030.
For data center operators, the agreement demonstrates that competitive advantage is no longer defined solely by AI accelerators. Vendors are also competing on their ability to provide a deployment path that includes power, liquid cooling and energized capacity years before it comes online.