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Nvidia equity investments hit $99bn in two years
Nvidia equity investments reached $99bn in July, up from $7bn a year earlier and $2.2bn the year before that. Roughly half of it sits in private companies, many of which buy its chips. Its finance chief calls the arrangement a flywheel, and Michael Burry calls it overreaching. Nvidia sells the chips that the AI industry runs on. It now also owns $99bn of the industry. The figure sits in the company's own quarterly filing. CNBC's Kai Nicol-Schwarz pulled it out. Nvidia equity investments stood at $99bn as of 26 July. A year earlier the figure stood at about $7bn. Two years earlier, $2.2bn. That is a fourteenfold rise in twelve months, and a forty-fivefold rise in twenty-four. The company has committed more than $40bn to financing deals during 2026 alone, and reported a further $25bn of investment commitments still outstanding. Half of it is in companies you cannot sell out of Business Insider broke down the composition, which is the part the headline number hides. Roughly $48bn sits in publicly traded stocks and other marketable securities. Another $48bn sits in private companies and other non-marketable holdings. About $3bn is in equity-method investments. The public half is legible. Nvidia's disclosed US stock positions as of 30 June included $30bn in Intel, from an investment that cost $5bn, and $21bn in SpaceX. CoreWeave, Coherent, Synopsys and Nokia each sat between $2bn and $5bn. The private half is not. It covers frontier labs and cloud providers that funding rounds price rather than markets. Nobody can exit those on a bad morning. Where the money went Chief financial officer Colette Kress told analysts the company has put nearly $50bn into frontier AI labs. The largest single commitment was $30bn into OpenAI in February, part of that company's $110bn round. The neoclouds, which buy Nvidia GPUs and rent access to them, took $2bn each: CoreWeave in January, Nebius in March. Nokia took $1bn. Since March the company has committed at least $6.5bn to photonics and optical firms, with $2bn each going to Lumentum, Coherent and Marvell. The pace has not slowed. In the past week alone, Nvidia confirmed it is buying Hugging Face for $12.93bn. It also turned up as a backer in Nscale's pre-IPO round. And The Information reports it is in talks to supply roughly half the capital for a $6bn raise at Thinking Machines Lab. Three deals, one week, across a chip platform, a cloud and a model lab. One distinction is worth holding on to. Hugging Face is an acquisition, not a stake. Buying a company consolidates it. Taking a minority position buys influence and a mark on the balance sheet. The $99bn counts the stakes, not the takeovers, so the takeovers sit on top of it. The company's explanation is a flywheel Nvidia says the investments enhance its growth opportunities, cultivate its ecosystem and strengthen its competitive position. Kress put it more directly on the earnings call. Frontier labs have extraordinary demand for compute, she said. But they outgrow their own balance sheets and credit profiles, and they cannot secure AI factory infrastructure alone. Nvidia, in her phrase, is needed to help power this flywheel. Analysts describe the same mechanism in less flattering terms. Naveen Chhabra of Forrester told CNBC that injecting capital into infrastructure financiers, specialised clouds and model labs gives those startups the balance-sheet strength to buy tens of thousands of Nvidia GPUs. Ian Fogg of CCS Insight put the control question plainly. Equity investments help companies innovate, he said, but they also give Nvidia a degree of influence over whether that innovation takes an Nvidia-shaped path. The optics investments show the same logic at the component layer. Chhabra argues that funding Coherent and its peers keeps their tooling and design work optimised for Nvidia's architecture. That raises switching costs and defends the CUDA software moat against AMD, and against the custom chips the cloud providers are building themselves. Not everyone reads it as a flywheel Michael Burry, who made his name shorting the mortgage market, says Nvidia is overreaching. His objection is that it finances and invests in the customers for its own chips. Mark Cuban has called it truly scary how much the AI boom now depends on Nvidia funding, in his words, everyone and anyone. Neither is a disinterested observer, and neither has produced a number. But the structure they are describing is the one Kress described approvingly, seen from the other side. There is a counterexample worth putting alongside them. When CoreWeave took its $2bn, it said the proceeds would go to land, power, infrastructure, research and hiring rather than to buying Nvidia chips. Money that arrives as equity does not have to come back as an order. The number against the business Some scale. Nvidia reported $96.2bn of revenue in its fiscal second quarter, up 106%. Net income reached $59.7bn. So the equity portfolio is now worth slightly more than the company turns over in a full quarter. It is not the largest such portfolio in technology. Alphabet held $232bn at the end of June, including $94bn of SpaceX shares, and Amazon is also above $100bn. What is unusual is the speed. Alphabet built its position over two decades. Nvidia built most of this one since the summer of 2024. The valuations underneath it are doing work too. The Intel stake is up sixfold on paper. Nvidia stock has gone from under $15 at the start of 2023 to $228, a market capitalisation of $5.5tn, and rising tech valuations lift the holdings alongside it. Which is the part worth watching. Nvidia sells to its own portfolio. The same boom that drives those sales also sets the prices at which the portfolio is carried. That is two exposures to one cycle rather than one. Nvidia has disclosed the number, and disclosure is the easy part. What it does not answer is what happens to the private half of that $99bn if the marks stop going up.
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Nvidia is the central bank of AI. But will its loans prove sound?
Critics compare Nvidia's billions in customer financing to 1990s telecom gear makers, warning of massive losses if artificial intelligence demand cools down. It took 30 years for Nvidia, an American firm whose chips power much of the world's artificial intelligence, to reach a valuation of $US1 trillion ($1.4 trillion). Getting to $US2 trillion took only nine more months. It passed the $US5 trillion mark less than two years later. It is now the world's most valuable company, worth about $US5.4 trillion. Next year, its sales are expected to almost double. Some analysts predict it will generate $1 trillion in annual revenue by 2029. It is not just chip making that has spurred Nvidia's stunning growth, however. Its boss, Jensen Huang, has also resorted to financial engineering to boost demand for its wares. In mid-August, for example, Nvidia agreed to provide a backstop worth up to $US105 billion for a vast data centre in Ohio that will use lots of its chips.
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Nvidia equity investments reached $99bn in July 2024, up from just $2.2bn two years earlier. Roughly half sits in private AI companies that buy its chips, including a $30bn stake in OpenAI. While Nvidia calls it a growth flywheel, critics like Michael Burry warn the chip giant is overreaching by financing its own customers.
Nvidia equity investments have surged to $99bn as of July 2024, marking a dramatic escalation in the chip giant's financial strategies beyond AI chip manufacturing
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. The figure represents a fourteenfold increase from approximately $7bn a year earlier and a forty-fivefold jump from $2.2bn two years prior1
. This aggressive expansion positions Nvidia not just as a hardware provider but as a major financial stakeholder across the AI ecosystem. The company has committed more than $40bn to financing deals during 2026 alone, with a further $25bn in investment commitments still outstanding1
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Source: Financial Review
Roughly $48bn of Nvidia's portfolio sits in publicly traded stocks and marketable securities, while another $48bn resides in private companies and non-marketable holdings that cannot be easily liquidated
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. About $3bn is held in equity-method investments1
. Among disclosed positions as of June 30, Nvidia held $30bn in Intel from an initial $5bn investment, $21bn in SpaceX, and stakes worth $2bn to $5bn each in CoreWeave, Coherent, Synopsys and Nokia1
.Chief Financial Officer Colette Kress revealed that Nvidia has deployed nearly $50bn into frontier AI labs, with the largest single commitment being $30bn into OpenAI as part of that company's $110bn funding round in February
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. This strategic positioning in frontier AI labs reflects Nvidia's approach to cultivating demand for its products at the source of AI innovation. Cloud providers building AI infrastructure investments have also received significant capital. CoreWeave secured $2bn in January, while Nebius received a similar amount in March1
. Nokia took $1bn, and since March, the company has committed at least $6.5bn to photonics and optical firms including $2bn each to Lumentum, Coherent and Marvell1
.The investment pace continues accelerating. In a single week, Nvidia confirmed its $12.93bn acquisition of Hugging Face, backed Nscale's pre-IPO round, and entered talks to supply roughly half the capital for a $6bn raise at Thinking Machines Lab
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. In mid-August, Nvidia agreed to provide a backstop worth up to $105bn for a massive data center in Ohio that will use its chips2
. These moves span the entire AI value chain from chip platforms to cloud infrastructure to model development labs.Nvidia frames its strategy as a self-reinforcing flywheel that powers growth across the AI ecosystem. Kress explained on earnings calls that frontier labs have extraordinary compute demand but outgrow their balance sheets and credit profiles, making it impossible to secure AI factory infrastructure alone
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. By injecting capital, Nvidia enables these startups to purchase tens of thousands of its GPUs, according to Forrester analyst Naveen Chhabra1
.Ian Fogg of CCS Insight notes that while equity investments help companies innovate, they also give Nvidia influence over whether that AI innovation takes an Nvidia-shaped path
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. The optics investments illustrate this logic at the component level. Chhabra argues that funding Coherent and similar firms keeps their tooling and design work optimized for Nvidia's architecture, raising switching costs and defending the CUDA software moat against AMD and custom chips that cloud providers are building themselves1
.Related Stories
Critics view Nvidia's role as the central bank of AI with growing concern. Michael Burry, famous for shorting the mortgage market before the 2008 crisis, says Nvidia is overreaching by financing and investing in customers for its own chips
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. Mark Cuban has called it "truly scary" how much the AI boom now depends on Nvidia funding "everyone and anyone"1
. Some observers compare Nvidia's billions in customer financing to 1990s telecom gear makers, warning of massive losses if artificial intelligence demand cools down2
.The structure creates a circular dependency where Nvidia finances the companies that buy its products. However, CoreWeave's case offers a counterpoint. When CoreWeave received its $2bn investment, the company stated proceeds would fund land, power, infrastructure, research and hiring rather than purchasing Nvidia chips
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. Money arriving as equity doesn't automatically return as an order, suggesting the relationship may be more nuanced than critics claim.
Source: The Next Web
The investment strategy accompanies extraordinary financial performance. Nvidia reported $96.2bn in revenue during its fiscal second quarter, up 106% year-over-year, with net income reaching $59.7bn
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. The equity portfolio now equals roughly the company's quarterly revenue. It took Nvidia 30 years to reach a $1 trillion valuation, only nine more months to hit $2 trillion, and less than two years after that to pass $5 trillion2
. The company is now the world's most valuable, worth approximately $5.4 trillion, with sales expected to nearly double next year and some analysts predicting $1 trillion in annual revenue by 20292
. Whether this growth trajectory proves sustainable or mirrors past technology bubbles remains the critical question facing investors and the broader AI industry.Summarized by
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