• Top OpenAI execs keep talking about the company's never-ending demand for GPUs.
• GPUs have become one of the key metrics in the AI race.
• OpenAI CEO Sam Altman already wants the company to 100x the 1 million GPUs it will have by the end of 2025.

OpenAI's C-suite can't stop talking about the company's insatiable demand for computing power.

"Every time we get more GPUs, they immediately get used," OpenAI CPO Kevin Weil recently told XPrize founder Peter Diamandis during an interview on Diamandis' "Moonshot" podcast.

Weil is just the latest OpenAI exec to sound off on the topic. OpenAI CEO Sam Altman said last month that the company will bring on more than 1 million GPUs by the end of the year. For comparison, Elon Musk's xAI disclosed that it used a supercluster of over 200,000 GPUs called Colossus to help train Grok4.

"very proud of the team but now they better get to work figuring out how to 100x that lol," Altman wrote on X in July.

Two days later, Musk's, Altman's former ally turned rival, said he wants xAI to have 50 million equivalents of Nvidia's H100 chip in the next five years.

The competition is for good reason. Jonathan Cohen, VP of Applied Research, recently said GPUs are like "currency" for AI researchers. Priscilla Chan, Mark Zuckerberg's wife and a cofounder of the couple's philanthropic organization, said the Chan Zuckerberg Initiative uses GPUs as a recruitment tool.

Weil said the necessity is really quite simple: "The more GPUs we get, the more AI we'll all use." He compared how adding bandwidth made the explosion of video possible.

"It's like the internet. Every bit that we lower latency, increase bandwidth on the internet, people do more things," he said. "Video used to be impossible. Now, video is everyday, because the capabilities are there the network can handle it."

The desire for more computing power led OpenAI to launch Stargate, CFO CFO Sarah Friar recently said. A $500 billion project, Stargate is a joint venture between OpenAI, Oracle, and SoftBank. During its unveiling at the White House in January, Altman said the project will allow the US to reach AGI, artificial general intelligence.

"It is voracious right now for GPUs and for compute," Friar told CNBC last week. "The biggest thing we face is being constantly under compute. That's why we launched Stargate. That's why we're doing the bigger builds."

On the product side alone, Weil said there are a number of areas where more GPUs can be plugged in.

"Whether it's we can take them on the product side, and use it to lower latency, or speed up token generation, or launch new products, take a product that's only available to pro users and bring it to plus users or free users, or it just means that we can run more experiments," he said.

At the same time, OpenAI has to balance researchers' requests.

"On the research side, there's basically infinite demand for GPUs within these walls, and that's why we're doing so much to build capacity," Weil said.

Silicon Valley's AI talent war just reached a compensation milestone that makes even the most legendary scientific achievements of the past look financially modest. When Meta recently offered AI researcher Matt Deitke $250 million over four years (an average of $62.5 million per year)—with potentially $100 million in the first year alone—it shattered every historical precedent for scientific and technical compensation we can find on record. That includes salaries during the development of major scientific milestones of the 20th century.

The New York Times reported that Deitke had cofounded a startup called Vercept and previously led the development of Molmo, a multimodal AI system, at the Allen Institute for Artificial Intelligence. His expertise in systems that juggle images, sounds, and text—exactly the kind of technology Meta wants to build—made him a prime target for recruitment. But he's not alone: Meta CEO Mark Zuckerberg reportedly also offered an unnamed AI engineer $1 billion in compensation to be paid out over several years. What's going on?

These astronomical sums reflect what tech companies believe is at stake: a race to create artificial general intelligence (AGI) or superintelligence—machines capable of performing intellectual tasks at or beyond the human level. Meta, Google, OpenAI, and others are betting that whoever achieves this breakthrough first could dominate markets worth trillions. Whether this vision is realistic or merely Silicon Valley hype, it's driving compensation to unprecedented levels.

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On Tuesday, OpenAI announced a partnership with Oracle to develop 4.5 gigawatts of additional data center capacity for its Stargate AI infrastructure platform in the US. The expansion, which TechCrunch reports is part of a $30 billion-per-year deal between OpenAI and Oracle, will reportedly bring OpenAI's total Stargate capacity under development to over 5 gigawatts.

The data center has taken root in Abilene, Texas, a city of 127,000 located 150 miles west of Fort Worth. The city, which serves as the commercial hub of a 19-county region known as the "Big Country," offers a location with existing tech employment ecosystem, including Dyess Air Force Base and three universities. Abilene's economy has evolved over time from its agricultural and livestock roots to embrace technology and manufacturing sectors.

"We have signed a deal for an additional 4.5 gigawatts of capacity with oracle as part of stargate. easy to throw around numbers, but this is a gigantic infrastructure project," wrote OpenAI CEO Sam Altman on X. "We are planning to significantly expand the ambitions of stargate past the $500 billion commitment we announced in January."

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Chinese firms have begun rushing to order Nvidia's H20 AI chips as the company plans to resume sales to mainland China, Reuters reports. The chip giant expects to receive US government licenses soon so that it can restart shipments of the restricted processors just days after CEO Jensen Huang met with President Donald Trump, potentially generating $15 billion to $20 billion in additional revenue this year.

Nvidia said in a statement that it is filing applications with the US government to resume H20 sales and that "the US government has assured Nvidia that licenses will be granted, and Nvidia hopes to start deliveries soon."

Since the launch of ChatGPT in 2022, Nvidia's financial trajectory has been linked to the demand for specialized hardware capable of executing AI models with maximum efficiency. Nvidia designed its data center GPU to perform the massive parallel computations required by neural networks, processing countless matrix operations simultaneously.

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On Wednesday, Nvidia became the first company in history to reach $4 trillion market valuation as shares rose more than 2 percent, reports CNBC. The GPU maker's stock has climbed 22 percent since the start of 2025, continuing a trend driven by demand for AI hardware following ChatGPT's late 2022 launch.

The milestone marks the highest market cap ever recorded for a publicly traded company, surpassing Apple's previous record of $3.8 trillion set in December. Nvidia first crossed $2 trillion in February 2024 and reached $3 trillion just four months later in June. The $4 trillion valuation represents a market capitalization larger than the GDP of most countries.

As we explained in 2023, Nvidia's continued success has been intimately tied to growth in demand for hardware that runs AI models as capably and efficiently as possible. The company's data center GPUs excel at performing billions of matrix multiplications necessary to train and run neural networks due to their parallel architecture—hardware architectures that originated as video game graphics accelerators now power the generative AI boom.

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