OpenAI, Oracle & SoftBank to Expand Stargate with Five New AI Data Centers
Expansions push Stargate closer to $500 billion and 10-gigawatt goal
OpenAI, Oracle, and SoftBank have jointly announced five new U.S. data center sites under Stargate Project back in January. For those who don’t know, Stargate is a $500 billion AI infrastructure program.
Well, thanks to new data centers, Stargate’s planned capacity now bumps up to 7 gigawatts, supported by more than $400 billion in investments already committed. The project is reportedly ahead of schedule to reach its 10-gigawatt target by late 2025.
As per the latest anouncement, OpenAI will build three of the new sites in partnership with Oracle in Shackelford County, Texas; Doña Ana County, New Mexico; and a site in the Midwest.
The new projects, along with a 600-megawatt expansion near Abilene, Texas, will deliver more than 5.5 gigawatts of capacity. They are also expected to generate over 25,000 on-site jobs and tens of thousands of additional roles across the country.
The other two sites will be build under SoftBank’s partnership with OpenAI. One is in Lordstown, Ohio, where construction is already underway, while the second is in Milam County, Texas, being developed with SB Energy for rapid deployment. OpenAI says that both the sites can scale up to 1.5 gigawatts within 18 months.
So, you may be woering , how these companioes come up with these locatoon, right? Well, the new facilities were chosen after a nationwide review of over 300 proposals from 30 states. They will join the
Sam Altman, CEO of OpenAI, said Stargate is about building the compute needed to unlock AI’s future. Oracle CEO Clay Magouyrk highlighted OCI’s rapid scaling, while SoftBank’s Masayoshi Son highlighted the role of energy expertise in creating sustainable infrastructure.
Last but not least, OpenAI recently also announced Stargate UK, a sovereign AI infrastructure project developed in partnership with NVIDIA and Nscale. The company says the project will bolster Britain’s computing capabilities for specialist and jurisdiction-specific use cases.
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