Google jumps, Nvidia and AMD fall on report that the search giant is in talks to sell “billions of dollars” of its custom AI chips to Meta

Google is climbing in premarket trading while Nvidia and Advanced Micro Devices have dropped on the heels of a report from The Information that has the search giant muscling in on the chip designers’ turf.

Per the report, Meta is in discussions with Google to spend “billions of dollars” to use its AI chips in the social media company’s data centers starting in 2027, and to begin renting access to Google chips from its cloud business next year.

Historically, Google has rented access to these chips through its cloud business rather than supplied them directly to third parties. The report suggests that insiders believe a more direct foray could allow the company to grab a market share in chips amounting to about 10% of Nvidia’s annual revenue.

Google’s AI chips — TPUs, or tensor processing units — are having a moment. These semiconductors were used to train its latest GenAI model, Gemini 3, which has received rave reviews, and are cheaper to use than Nvidia’s offerings. That’s sent the stock to record highs, surpassing Microsoft in market value along the way.

According to The Information, Meta is even mulling using TPUs for training, considered a much more demanding task, rather than just inference alone.

Shares of Nvidia have slumped more than 4% as of 8:30 a.m. ET. AMD, which sell GPUs for use in data centers, is down more than 5% by the same point. Google has moved 4% in the other direction, while Broadcom, the custom chip specialist that partnered with Google to design these TPUs, is also up about the same amount.

During Nvidia’s conference call last week, CEO Jensen Huang was asked about the competitive threat posed by custom chips. He responded by talking up the difficulty of inference (“How could thinking be easy?”). That’s a not-too-subtle nod to the idea that his company’s GPUs will be the more effective solution compared to more cost-effective options. He also touted the company’s CUDA software as a selling point because it’s more commonly used, therefore making it easier for buyers to go on and sell AI computing capacity.

Google has aimed to make its JAX software easier for developers over time by making its TPUs operable via open-source software tied to PyTorch (invented by Meta), overhauling how errors are reported and introducing an extension that makes it easier to write custom code, among others.