Starcloud Becomes First to Train LLMs in Space Using NVIDIA …

NVIDIA-backed startup Starcloud has successfully trained and run LLMs from space for the first time, a step toward orbital data centres as demand for computing power and energy grows on Earth. 

The Washington-based company’s Starcloud-1 satellite, launched last month with an NVIDIA H100 GPU, has completed training of Andrej Karpathy’s nano-GPT on the complete works of Shakespeare and run inference on Google DeepMind’s open Gemma model. 

“We just trained the first LLM in space using an NVIDIA H100 on Starcloud-1! We are also the first to run a version of Google’s Gemini in space!” wrote Philip Johnston, founder and CEO of Starcloud, in a post on LinkedIn. 

“This is a significant step on the road to moving almost all compute to space, to stop draining the energy resources of Earth and to start utilising the near limitless energy of our Sun!” he added. 

In a post on X, Starcloud CTO Adi Oltean said that getting the H100 operational in space required “a lot of innovation and hard work” from the company’s engineering team. He added that the team executed inference on a preloaded Gemma model and aims to test more models in the future. 

Founded in 2024, Starcloud argues that orbital compute could ease mounting environmental pressures linked to traditional data centres, whose electricity consumption is expected to more than double by 2030, according to the International Energy Agency. 

Facilities on Earth also face water scarcity and rising emissions, while orbital platforms can harness uninterrupted solar energy and avoid cooling challenges.

The startup, part of NVIDIA ’s Inception program and an alumnus of Y Combinator and the Google for Startups Cloud AI Accelerator, plans to build a 5-gigawatt space-based data centre powered entirely by solar panels spanning four kilometres in width and height. Such a system would outperform the largest US power plant while being cheaper and more compact than an equivalent terrestrial solar farm, according to the company’s white paper.

A New Era of Solar-Powered Intelligence in Orbit

Besides Starcloud, Google, SpaceX and Jeff Bezos’ Blue Origin are also pursuing space-based data centres. 

Google recently announced Project Suncatcher, which explores placing AI data centres in orbit. The initiative involves satellites equipped with custom tensor processing units and linked through high-throughput free-space optical connections to form a distributed compute cluster above Earth.

Google CEO Sundar Pichai described space-based data centres as a “moonshot” in a recent interview. He said the company aims to harness uninterrupted solar energy near the sun, with early tests using small machine racks on satellites planned for 2027 and potential mainstream adoption within a decade.

Elon Musk, meanwhile, announced in November 2025 that SpaceX would build orbital data centres using next-generation Starlink satellites, calling them the lowest-cost AI compute option within five years. He said Starlink V3 satellites could scale to become the backbone of orbital compute infrastructure.

According to a recent report, SpaceX is preparing for an initial public offering in 2026 to raise more than $25 billion at a valuation exceeding $1 trillion. According to Bloomberg News, SpaceX plans to use the IPO proceeds to build space-based data centres and purchase the chips needed to run them. Musk discussed the idea during a recent event with Baron Capital.“

Starship should be able to deliver around 300 GW per year of solar-powered AI satellites to orbit, maybe 500 GW. The ‘per year’ part is what makes this such a big deal,” he said in a post on X on November 20. “Average US electricity consumption is around 500 GW, so at 300 GW/year, AI in space would exceed the entire US economy just in intelligence processing every 2 years.”

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