Elon Musk’s SpaceX lands $1.25trn valuation after xAI acquisition
- by SiliconRepublic
- Feb 03, 2026
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xAI had acquired X in March 2025. Moreover, last week, Musk’s electric-vehicle company Tesla said that it would invest $2bn into xAI.
Meanwhile, Musk marked up SpaceX’s valuation to $1trn, citing revenue growth from its Starlink satellite broadband service, sources told the publication. The company was recently valued at $800bn after a secondary stock sale.
Starlink currently dominates the global satellite internet service industry, with its 9,000-plus satellites in orbit and roughly 9m customers.
Looking ahead this year, SpaceX is still aiming for an IPO this year, company executives have confirmed. Musk expects to raise up to $50bn in the floatation, reports suggest, making it the largest IPO debut in history.
In a blog post on SpaceX’s website, Musk said that the merger would allow for data centres to be transported to space, to harness the near-constant solar energy from the Sun. “In the long term, space-based AI is obviously the only way to scale,” he said.
Last November, the Y Combinator-backed Starcloud-1 spacecraft became the first to launch with an Nvidia H100 GPU to space. It also took the title as the first-ever spacecraft to train a large language model.
“The basic math”, according to Musk, is that launching a “million tonnes” of satellites per year generating 100 kW of compute power per ton would add 100 GW of AI compute capacity annually, with “no ongoing operational of maintenance needs”. This, he said, is the path to launching 1 TW per year from Earth.
According to the tech-billionaire, SpaceX’s Starship rockets will begin delivering its next-generation satellites into orbit this year, with each launch expected to add more than 20-times the capacity to the constellation compared to current launches. Starship will also launch the next generation direct-to-mobile satellites this year.
“My estimate is that within two to three years, the lowest cost way to generate AI compute will be in space,” he said, adding that the cost-efficiency would allow companies to train their AI models and process data at “unprecedented” speeds and scales.
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