SB Energy partners with OpenAI to build and operate 1.2GW Stargate data center

OpenAI's direct co-development of a 1.2 GW Stargate data center with SB Energy in Milam County, Texas, redefines AI infrastructure procurement. This partnership extends beyond traditional power purchase agreements, embedding OpenAI directly into the operational aspects of its energy supply for the massive facility. SB Energy secures a substantial, long-term anchor tenant for a 1.2 GW project, ensuring demand for its renewable energy development and operation capabilities. The joint build-and-operate structure mitigates supply risk for OpenAI's artificial intelligence research and deployment, guaranteeing dedicated computing power. This arrangement allows SB Energy to leverage its expertise in developing and operating solar, wind, and energy storage projects directly into a high-growth sector. The simultaneous 2026-03-10 announcement of SB Energy's acquisition of Studio 151 suggests a strategic move by SB Energy to bolster its capabilities or land bank for such large-scale projects. The undisclosed value of this Milam County, Texas, development leaves financial specifics opaque. The direct partnership in the Stargate data center development demonstrates OpenAI's critical need for dedicated, scalable computing power to support its artificial intelligence research and deployment. This 1.2 GW facility in Milam County, Texas, directly addresses the "significant computing power" requirement for OpenAI's activities. For SB Energy, a renewable energy company focused on developing and operating solar, wind, and energy storage projects, this partnership provides a substantial, long-term off-take opportunity, aligning with its aim to provide clean and reliable energy. The joint operational model allows SB Energy to integrate its expertise in sustainable energy directly into a major industrial load in the US. This 2026-03-10 announcement suggests a deepening integration between large-scale AI demand and renewable energy supply, potentially influencing future infrastructure investment models.