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    Home»US News

    Nvidia’s AI moat is shifting from chips to capital

    AdminBy AdminAugust 18, 2026 US News
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    Jensen Huang, chief executive officer of Nvidia Corp., speaks to members of the media following the company’s “Japan AI Ecosystem” reception in Tokyo, Japan, on Thursday, July 16, 2026.

    Kiyoshi Ota | Bloomberg | Getty Images

    Nvidia’s massive head start in artificial intelligence turned the chipmaker into the world’s most valuable company. Now, almost four years into the generative AI boom, competitors like Advanced Micro Devices and Google have chipped away at Nvidia’s technology lead, pushing the company to take advantage of its other great asset: capital.

    Following last week’s pact with Wall Street firms to pursue $500 billion worth of financing for Nvidia’s graphics processing units, Nvidia said on Monday that it’s providing up to $105 billion for a giant OpenAI data center in Ohio, offering a backstop of sorts should the ChatGPT creator see its fortunes turn.

    For Nvidia, the strategy involves fueling the AI boom by whatever means necessary, recognizing that demand for critical infrastructure is seemingly insatiable but that a handful of companies — the hyperscalers — account for an outsized amount of purchases. With its quarterly free cash flow up 18-fold over the past three years to $48.5 billion in the latest period, Nvidia is using the strength of its balance sheet and credit rating to ensure there’s no dramatic slowdown following 12 straight quarters of revenue growth above 55%.

    “They remain dominant, but they’re very paranoid about making sure they don’t lose ground,” said Ram Bala, associate professor of AI and analytics at Santa Clara University’s Leavey School of Business.

    Nvidia declined to comment.

    In a note to clients on Monday, analysts at Cantor brushed off concerns that Nvidia is effectively buying revenue through its financial maneuvering. They reiterated their buy rating and said the latest agreement is a “clear signal that the current AI investment cycle will be elongated and durable.”

    “We view this less as circular and more facilitating the coming AI buildout while at the same time creating additional competitive moats that will continue to enable NVDA to remain THE AI leader,” the analysts wrote.

    Nvidia is swimming in money. Its cash generation is so great that the company said in May that it was increasing its quarterly dividend to 25 cents a share from a penny, and announced a new $80 billion stock buyback plan. The company pledged “to return roughly 50% of free cash flow to shareholders this year.”

    One way the company has been putting its cash pile to work is through equity investments in companies across the AI ecosystem, including some businesses — like model developers and neoclouds — that spend heavily on Nvidia’s chips and systems. Nvidia held $30.2 billion in marketable equity securities as of the most recent quarter, up from $12.9 billion a year earlier.

    In February, Nvidia invested $30 billion in OpenAI, which relies on training capacity from Vera Rubin, the chip giant’s most advanced system. Monday’s agreement included a $1.5 billion investment in SB Energy, a SoftBank affiliate that’s building and managing the data center at the PORTS-Pike Technology Campus in Pike County, Ohio, through a 20-year lease to OpenAI.

    In addition to the SB Energy investment, Nvidia said it’s putting its financial support behind about 4 gigawatts of development at the Ohio site for portions of lease and power and “a specified residual-value commitment,” as data centers open between 2028 and 2030.

    Expanding access

    Nvidia CEO Jensen Huang acknowledged the significance of the company’s financial prowess in a post on X about the agreement.

    “Frontier AI labs have extraordinary demand for training and inference compute, but many are growing faster than their balance sheets and long-term credit profiles can support,” Huang wrote. “They may have strong customer demand and rapidly growing revenue yet still lack the decades-long infrastructure contracts and investment-grade financing capacity needed to secure the AI factory infrastructure independently.”

    A week prior, Huang was on set at CNBC surrounded by six of Wall Street’s leading financiers to announce the arrival of Nvidia graphics processing units as a new asset class. In signing a memorandum of understanding with firms including Goldman Sachs, Apollo Global Management, Blackstone and BlackRock, Huang indicated that the next phase of the AI buildout will be funded in part by third-party backers, who can start investing in GPUs the way they do real estate.

    “These are revenue-generating assets now,” Huang told CNBC. “They’re productive, they’re long-lived, they’re fungible, they’re flexible.”

    Key to obtaining financing for prospective borrowers will be a dedication to Huang’s systems, with Nvidia obtaining the option of backstopping 25% of every loan. It’s another way to get more of Nvidia’s technology into the market, as competition builds from Google and AMD, as well as from specialized chipmakers like Cerebras.

    In the second quarter, Google began recognizing revenue from TPU system sales, contributing to the cloud unit’s 82% growth. AMD, meanwhile, reported more than 100% growth in its data center business, and the company expects its first rack-scale system, called Helios, to ship later this year.

    Paul Meeks, head of technology research at Freedom Capital Markets, said the stepped-up competition eats into Nvidia’s ability to yield “outrageous margins,” and incentives the company to diversify its strategy.

    “Part of their thinking is let’s broaden our reach,” Meeks said. “We just can’t ride this one horse, which is GPUs.”

    AI bulls say that Nvidia is just responding to demand, and point out that the shortage in the market today is on the capacity side. There are plenty of numbers to back that up, as Anthropic told investors over the weekend that its annualized revenue run rate hit $65 billion in July, up sevenfold from a year earlier. OpenAI’s run rate recently reached $40 billion.

    Matthew Vegari, head of research at Clearwater Analytics, said in an email that, based on the market dynamics, the “narrative around the AI trade’s circuitous, ‘house of cards’ structure strikes us as somewhat misguided.”

    “We might one day be at overcapacity,” he wrote. “But that day isn’t today.” 

    — CNBC’s Samantha Subin and Jonathan Vanian contributed to this report

    WATCH: AI is not a new asset class, it’s the entire market, says Clockwise Capital CIO

    AI chips aren't a new asset class, they're the entire market
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