CoreWeave, a publicly traded neocloud that rents out computing power for AI, has seen its stock price fall to a 12-month low, and Elon Musk is flexing $40 billion in debt for buying computing capacity and predicting that “200+ neoclouds are going to see guppy-level death and consolidation.” It’s not exactly the ideal week to announce a Series A for a neocloud.
General Compute co-founder and CEO Finn Puklowski is unfazed. He’s bullish on CoreWeave’s chances, and thinks Musk is just talking his book to drive down the prices of the GPUs he wants to buy. Fears of a chip-led collapse are “massively overstated. I have people calling me up every single week asking me to do TPUs, GPUs, any chip, to get them more compute.”
Just as important, he says, Anthropic’s bullish S-1 is “settling fears for today.”
General Compute has found a niche building its cloud out of specialized inference chips built by Nvidia rivals. The company struck a $400 million deal to purchase new chips from SambaNova—the first debt financing of inference chips—and now has added Positron and Cerebras to its portfolio of chip suppliers.
A deal with a large customer worth $100 million in annual recurring revenue has paved the way for the company to raise $100 million in Series A funding led by Blackbird Ventures and Abstract Ventures. Valued at $60 million after a May seed round, General Compute is now worth $800 million post-money to its investors.
The startup’s strategy is to zig where others zag. It focused on chips built for inference while everyone else chased GPUs. And instead of taking on a complex effort to build huge data centers, it uses smaller power sources, rents space in other companies’ data centers, and converts former bitcoin-mining sites into places that run AI models.
That approach means General Compute isn’t going to catapult into the top ranks of neoclouds or compete with hyperscalers any time soon. But it’s also not subject to the constraints that come with building data centers from scratch. When General Compute has chips, it will have someplace to plug them in. Puklowski expects the company to deploy 75 megawatts of computing capacity in 2027, and he suspects he will have access to 200 megawatts of power—“more than we can probably fund and get hardware for.”
Still, the plan has a limit. Puklowski’s financing work isn’t done—”capital is going to be a full-time job for me, both on debt and equity,” he told TechCrunch.
The startup has found key customers in cloud companies that specialize in offering developers high-speed inference; General Compute provides the bare metal, or raw servers with no software layered on top, for them to bring their offerings to market. James Palmer, a principal at Blackbird who co-led the round, said his firm’s confidence in General Compute comes in part from an investment in Baseten, an inference cloud company.
“We’ve been proximate to their journey over the last 10 months and observing the wild growth story that [Baseten] has gone on, and the demand for open weight inference, and for companies owning their own intelligence,” Palmer told TechCrunch. When it comes to General Compute, he said, “Cerebras, Positron, SambaNova, all need distribution partners who can take them to scale, who can navigate the complexity of the physical world.”
Executives at all three chipmakers sang General Compute’s praises to TechCrunch, each noting the importance of the company’s focus on making the economics of AI cloud compute work. “Everyone in this market is selling speed,” Rodrigo Liang, SambaNova’s CEO and co-founder, said. “The real question is whether you can make money doing it.”
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Tim Fernholz is a journalist who writes about technology, finance and public policy. He has closely covered the rise of the private space industry and is the author of Rocket Billionaires: Elon Musk, Jeff Bezos and the New Space Race. Formerly, he was a senior reporter at Quartz, the global business news site, for more than a decade, and began his career as a political reporter in Washington, D.C. You can contact or verify outreach from Tim by emailing [email protected] or via an encrypted message to tim_fernholz.21 on Signal.