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Starcloud\u2019s latest funding round values the space compute company at $1.1 billion, making it one of the fastest startups to reach unicorn status after graduating from Y Combinator.<\/p>\n
The company\u2019s Series A, which closed 17 months after its demo day presentation, was led by Benchmark and EQT Ventures. It\u2019s another sign of the interest in outsourcing data centers to orbit as resource and political obstacles slow their development on Earth, but the business model depends<\/a> on unproven technology and significant capital expenditure.<\/p>\n Starcloud has now raised a total of $200 million, and launched its first satellite with an Nvidia H100 GPU in November 2025. The company will launch a more powerful version, Starcloud 2, later this year with multiple GPUs, including an Nvidia Blackwell chip and an AWS server blade, as well as a bitcoin mining computer.<\/p>\n The company will also begin developing a data center spacecraft designed to launch from Starship, the reusable heavy lift rocket being built by Elon Musk\u2019s SpaceX. Starcloud 3, as the spacecraft is named, will be a 200 kilowatts, three-ton spacecraft that fits the \u201cpez dispenser\u201d system SpaceX designed to deploy its Starlink satellites from Starship.<\/p>\n CEO and founder Philip Johnston said he expects that will be the first orbital data center that is cost-competitive with terrestrial data centers, with costs on the order of $.05 per kw\/hour of power \u2014 if commercial launch costs land around $500 per kilogram.<\/p>\n The challenge is that Starship isn\u2019t flying yet; Johnston says he expects commercial access to open up in 2028 and 2029. That\u2019s the reality facing all the big space data center projects: powerful space computers will be cost-prohibitive until a new generation of rockets starts launching at a high operational cadence, something that might not happen until the 2030s.<\/p>\n \u201cIf it ends up being delayed, we\u2019ll just carry on launching the smaller versions on Falcon 9,\u201d Johnston said. \u201cWe\u2019re not going to be competitive on energy costs until Starship is flying frequently.\u201d<\/p>\n Techcrunch event<\/p>\n \n\t\t\t\t\t\t\t\t\tSan Francisco, CA<\/span> \u201cThere\u2019s kind of two business models,\u201d Johnston explains: One is selling processing power to other spacecraft on orbit; the company\u2019s first satellite, for example, analyzes data collected by Capella Space\u2019s radar spacecraft. Then, in the future when launch costs go down, more powerful distributed data centers could potentially pull work from their terrestrial counterparts.<\/p>\n That gets at how new this industry really is. When Nvidia CEO Jensen Huang unveiled the company\u2019s Vera Rubin Space-1 chip modules at his company\u2019s annual GPU Technology Conference last week, he didn\u2019t note that none had been produced or shared with the company\u2019s development partners.\u00a0<\/p>\n In fact, the number of advanced GPUs on orbit is numbered in the dozens, while Nvidia is estimated to have sold nearly 4 million to terrestrial hyperscalers in 2025.\u00a0<\/p>\n Or consider that SpaceX\u2019s Starlink communications network, the largest satellite network in orbit with 10,000 spacecraft, produces something around 200 megawatts<\/em> of energy, while data centers with more than 25 gigawatts<\/em> of power are currently under construction in the U..S, according to Cushman and Wakefield.\u00a0<\/p>\n Johnston argues that his company is well ahead of the competition, with the first terrestrial GPU deployed in orbit. It was used to train an AI model in orbit, a first, according to Starcloud, and run a version of Gemini. Beyond the performance, Johnston says Starcloud now has valuable data about what it takes to run a powerful chip in space. <\/p>\n \u201cAn H100 is probably not the best chip for space, to be honest, but the reason we did it is we wanted to prove that we could run state of the art terrestrial chips in space,\u201d he told TechCrunch. That hard-won knowledge \u2014another GPU, an Nvidia A6000, failed during launch \u2014 will influence future designs.<\/p>\n There is a laundry list of technical challenges to be solved, including efficient power generation and cooling the hot-running chips. Starcloud-2 will have the largest deployable radiator flown on a private satellite; he expects at least two additional versions of that spacecraft will head to orbit, Johnston said.<\/p>\n Then there is the challenge of synchronization. The largest datacenter workloads, often for training, require hundreds or thousands of GPUs to work in tandem. Doing that in space will either require fantastically large spacecraft, or powerful and reliable laser links between spacecraft flying in formation. Most companies working on this technology expect those workloads to come long after simpler inference tasks take place on orbit.<\/p>\n
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