When DeepSeek launched its R1 open source model in January 2025, it stunned Silicon Valley. The idea that a small Chinese lab had created such a powerful open source model with comparatively fewer resources than their American counterparts left the tech industry’s heavy hitters baffled. Marc Andreessen called it a “Sputnik moment.” Then-Scale CEO Alex Wang described it as a “wakeup call.”

Inside OpenAI, it jolted three young researchers to realize the power of open source models. If they could build the infrastructure to optimize those models, the researchers thought, it could mean big business. “Our worldview was just very different than a lot of our OpenAI colleagues,” Yash Patil, one of the researchers, tells Forbes. “If open weight models are going to be really good, we don't see OpenAI or Anthropic having all of the data in the world to train this super-model. We more see the JPMorgans of the world using their own data to train models for the things that they care about — because they're never going to give that data away.”

Five months later, Patil, along with fellow researchers Rhythm Garg and Linden Li, left OpenAI to found Applied Compute, a startup that trains custom open source models for enterprise customers, then runs those models on the startup’s cloud. It’s been a whirlwind ever since. It raised a $20 million seed round in June 2025 and within a year had signed up big name clients like DoorDash, Nvidia and Microsoft, whose CEO Satya Nadella sat down for an interview with Patil in June about the future of enterprise AI. Then on Wednesday, Applied Compute told Forbes it’s in talks to raise $350 million in funding that would vault its valuation to $3.25 billion. The company cautioned some of those numbers could change as it finalizes the round. (The Information earlier reported some of the details of the latest fundraising.) The new valuation would be nearly double Applied Compute’s worth from just four months ago, with its valuation growing faster than YC’s fastest unicorn.

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