• Google's AI chip business is turning into a TPU-shaped headache for Nvidia.
• A blockbuster deal with Oracle will put Google's TPUs inside another hyperscaler.
• Is the market underestimating the potential of Google's chip business?

Earlier this year, Nvidia CEO Jensen Huang downplayed the threat of other companies building competing AI chips, including Google.

"Without Anthropic, why would there be any TPU growth at all?" he said in an interview with podcaster Dwarkesh Patel, referring to Google's custom chips. "It's 100% Anthropic."

That is no longer the case.

On Tuesday, Google and Oracle announced a blockbuster deal that will see Google's TPUs, short for Tensor Processing Units, made available to Oracle cloud customers from next year. As the companies underscored in a joint announcement, it's the first time Google's TPUs have been offered on a hyperscaler's platform beyond its own.

Anthropic isn't the only one Nvidia should be worried about. OpenAI has a job listing for a software engineer to optimize its models for TPUs, and The Information reported Tuesday that OpenAI plans to buy TPUs from Google.

Meanwhile, several analysts have predicted Google's TPU business is about to explode as more companies hedge their bets with a multichip strategy — providing an opening for Google and others to further move onto Nvidia's turf.

Despite this, Nvidia's chip business still eclipses everyone else's, including Google, which is also a big customer of Nvidia's GPUs. Yet Google's AI chips, which the company began building more than a decade ago to power search and other products, might be poised for takeoff.

On Wednesday, during Google's third-quarter earnings call, chief financial officer Anat Ashkenazi said the company expects a "meaningful revenue ramp in 2027" in TPU sales.

Cloud chief Thomas Kurian also said on the call that TPU sales were a "meaningful contributor" to the company's Q3 financials.

In its IPO paperwork filed this week, Anthropic said it planned to spend $114.5 billion on Google compute between April 2026 and July 2033. While it didn't specify how much of that would go to TPUs specifically, it estimated spending between $125 billion and $150 billion on TPU capacity from Google and other providers.

In the same filing, Anthropic said it's also using Amazon's Trainium chips and AMD's GPUs, as well as chips from Nvidia and Google.

All told, this might be Nvidia's nightmare scenario coming true. If companies are increasingly using a multichip strategy, it could hamper Nvidia's pricing power.

Google declined to comment, and Nvidia and OpenAI did not respond to requests for comment.

TPU takeoff?

Google's TPU business may only be getting started.

In notes published this month, Japanese banking group Mizuho projected TPU revenue of $28 billion for 2026 and $67 billion in 2027. Mizuho said Google could see that number reach as high as $100 billion in 2028, while TD Cowen's John Blackledge projected it could reach $138 billion, accounting for 34% of Google Cloud's 2028 revenue.

That number is still dwarfed by Nvidia, which reported $96.2 billion in revenue in the previous quarter alone, and the market reacted with a shrug on Wednesday as its share price stayed flat.

Some analysts, though, think the market is underestimating Google, especially as more companies look to reduce their reliance on Nvidia's GPUs.

"We believe Google's TPU hardware business is emerging as a materially larger opportunity than what is currently reflected in consensus estimates," Mizuho analysts wrote in a note published October 18, adding that selling TPUs outright — rather than renting them from Google's own data centers — could ease Google's aggressive capex spending.

And even if that spending continues to soar — and right now, there are no signs the foot is coming off the accelerator — analysts at Bank of America said Google's cash-splashing looks "relatively efficient" compared to its peers, as TPUs continue to power the company's own AI efforts.

For Google, it's the payoff of a decade-plus investment in silicon that was originally designed to make Search smarter. It could also act as something of a buffer against damage to its core search business as AI agents eat Google's lunch, Mizuho also said this month.

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• Anthropic is touting its ability to use different AI chips in its initial public offering filing.
• Analysts say a multichip strategy could weaken Nvidia's pricing power.
• Switching chips is hard and expensive, putting it out of reach for smaller players.

Anthropic is hedging its bets by using multiple chips to handle its AI work — a strategy that could eventually erode Nvidia's dominance.

The AI lab says it manages compute "as a single, fungible pool from multiple strategic partners" — with software that can direct its work to different chips depending on where they're most productive, according to Anthropic's S-1 filing, which came out Monday as the company prepares to go public.

Anthropic says it uses hardware from four chip families: Amazon Trainium, Google TPUs, Nvidia GPUs, and AMD GPUs.

That flexibility, which Anthropic said "took years and significant investment to build," could make major AI companies less dependent on Nvidia over time and give them more negotiating leverage, analysts said.

"The real exposure could be Nvidia's pricing power," said Patrick Moorhead, founder and CEO of Moor Insights & Strategy, "because a customer that can shift work across four platforms negotiates very differently than one that can't."

Ashish Nadkarni, an analyst at IDC, added that a multichip approach also makes Anthropic less vulnerable to fluctuations in Nvidia's chip supply.

Breaking Nvidia's grip isn't easy

Although Anthropic's chip mix isn't new, the company is now pitching it as a core advantage to investors, Moorhead said.

The threat has its limits. Switching between chips is still difficult — especially when it comes to training AI models as opposed to running them, Moorhead said — and only the biggest AI companies have the resources to do it.

Anthropic also continues to spend billions on Nvidia compute, Moorhead said.

Gil Luria, head of technology research at D.A. Davidson, said that while other major companies like OpenAI likely take a multichip approach, it may not be worth the effort and investment for smaller players.

Brad Gastwirth, global head of research and market intelligence at Circular Technology, said Anthropic's strategy doesn't represent a major near-term threat. Having more chip options doesn't erase Nvidia's advantages in performance, networking, and software, he said.

There's a broader risk for Nvidia if AI compute becomes more of a commodity.

Citadel CEO Ken Griffin has warned that if supply overtakes demand, it could drive down rental prices.

"GPUs, like airlines, have a very low marginal cost to run," he told Bloomberg last week. "The moment you have overcapacity, pricing goes into freefall."

Nvidia did not immediately respond to a request for comment from Business Insider.

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