Nvidia’s announcement earlier this week that it is investing $100 billion into OpenAI to help fund its massive data center build out has added to a growing sense of unease among investors that there is a dangerous financial bubble around AI, and that the revenues and earnings math underpinning the valuations of both public and private companies in the sector just doesn’t add up.
While Nvidia’s latest announcement is by far the largest example, the AI chipmaker has engaged in a series of “circular” deals in which it invests in, or lends money to, its own customers. Vendor financing exists to some degree in many industries, but in this case, circular transactions may give investors an inflated perception of the true demand for AI.
In past technology bubbles, revenue “roundtripping” and tech companies financing their own customers have exacerbated the damage when those bubbles eventually popped. While the share of Nvidia’s revenues that are currently being driven by such financing appears to be relatively small, the company’s dominance as the world’s most valuable publicly-traded company means that its stock is “priced for perfection” and that even minor missteps could have outsized impact on its valuation—and on financial markets and perhaps even the wider economy.
The extent to which the entire AI boom is backstopped by Nvidia’s cash isn’t easy to answer precisely, which is also one of the unsettling things about it. The company has struck a number of investment and financing deals, many of which are too small individually for the company to consider “material” and report in its financial filings, even though collectively they may be significant.
In addition, there are so many interlocking rings of circularity—where Nvidia has invested in a company, such as OpenAI, that in turn purchases services from a cloud service provider that Nvidia has also invested in, which then also buys or leases GPUs from Nvidia—that disentangling what money is flowing where is far from easy.
Tangled webs of investment
Two of the most prominent examples of Nvidia’s web of circuitous investments are OpenAI and Coreweave. In addition to the latest investment in OpenAI, Nvidia had previously participated in a $6.6 billion investment round in the fast-growing AI company in October 2024. Nvidia also has invested in CoreWeave, which supplies data center capacity to OpenAI and is also an Nvidia customer. As of the end of June, Nvidia owned about 7% of Coreweave, a stake worth about $3 billion currently.
The benefits that companies get from a Nvidia investment extend beyond the cash itself. Nvidia’s equity stakes in companies such as OpenAI and Coreweave enable these companies to access debt financing for data center projects at potentially significantly lower interest rates than they would be able to access without such backing. Jay Goldberg, an analyst with Seaport Global Securities, compares such deals to someone asking their parents to be a co-signer on their mortgage. It gives lenders some assurance that they may actually get their money back.
Startups financing data centers have often had to borrow money at rates as high as 15%, compared to 6% to 9% that a large, established corporation such as Microsoft might have to pay. With Nvidia’s backing, OpenAI and Coreweave have been able to borrow at rates closer to what Microsoft or Google might pay.
Nvidia has also signed a $6.3 billion deal to purchase any cloud capacity that CoreWeave can’t sell to others. The chipmaker had previously agreed to spend $1.3 billion over four years on cloud computing with CoreWeave. Coreweave, meanwhile, has purchased at least 250,000 Nvidia GPUs so far—the majority of which it says are H100 Hopper models, which cost about $30,000 each—which means Coreweave has spent about $7.5 billion buying these chips from Nvidia. So in essence, all of the money Nvidia has invested in Coreweave has come back to it in the form of revenue.
Nvidia has struck similar cloud computing deals with other so-called “neo-cloud” companies. According to a story in The Information, Nvidia agreed this summer to spend $1.3 billion over four years renting some 10,000 of its own AI chips from Lambda, which like Coreweave runs data centers, as well as a separate $200 million deal to rent some 8,000 more over an unspecified time period.
For those who believe there’s an AI bubble, the Lambda deal is clear evidence of froth. Those Nvidia chips Lambda is renting time on back to Nvidia? It bought them with borrowed money collateralized by the value of the GPUs themselves.
Besides its large investments in OpenAI and Coreweave, AI chipmaker also holds multi-million dollar stakes in several other publicly-traded companies that either purchase its GPUs or work on related chip technology. These include chip design firm Arm, high-performance computing company Applied Digital, cloud services company Nebius Group, and biotech company Recursion Pharmaceuticals. (Nvidia also recently purchased a 4% stake in Intel for $5 billion. Like Arm, Intel makes chips that in some cases are alternatives to Nvidia’s GPUs, but which for the most part are complementary to them.)
Earlier this month, Nvidia also pledged to invest £2 billion ($2.7 billion) in U.K. AI startups, including at least £500 million in Nscale, a U.K.-based data center operator that will, presumably, be using some of that money to purchase Nvidia GPUs to provision the data centers it is building. Nvidia also said it would invest in a number of British startups, both directly and through local venture capital firms, and some of that money too, will likely come back to OpenAI in the form of computing purchases, either directly, or through cloud service providers, who in turn will need to buy Nvidia GPUs.
In 2024, Nvidia invested about $1 billion in AI startups globally either directly or through its corporate venture capital arm NVentures, according to data from Dealroom and The Financial Times. This amount was up significantly from what Nvidia invested in 2022, the year the generative AI boom kicked off with OpenAI’s debut of ChatGPT.
How much of this money winds up coming right back to Nvidia in the form of sales is again, difficult to determine. Wall Street research firm NewStreet Research has estimated that for every $10 billion Nvidia invests in OpenAI, it will see $35 billion worth of GPU purchases or GPU lease payments, an amount equal to about 27% of its annual revenues last fiscal year.
Echoes of the dotcom era
That kind of return would certainly make this sort of customer financing worthwhile. But it does raise concerns among analysts about a bubble in AI valuations. These kinds of circular deals have been a hallmark of previous technology bubbles and have often come back to haunt investors.
In this case, the lease arrangements that Nvidia is entering into with OpenAI as part of its latest investment could prove problematic. By leasing GPUs to OpenAI, rather than requiring them to buy the chips outright, Nvidia is sparing OpenAI from having to take an accounting charge for the high depreciation rates on the chips, which will ultimately help OpenAI’s bottom line. But it means that instead Nvidia will have to bear this depreciation costs. What’s more, Nvidia will also take on the risk of being stuck with an inventory of GPUs no one wants if demand for AI workloads don’t match Nvidia CEO Jensen Huang’s rosy predictions.
To some market watchers, Nvidia’s latest deals feel all-too-similar to the excesses of past technology booms. During the dot com bubble at the turn of the 21st Century, telecom equipment makers such as Nortel, Lucent, and Cisco lent money to startups and telecom companies to purchase their equipment. Just before the bubble burst in 2001, the amount of financing Cisco and Nortel had extended to their customers exceeded 10% of annual revenues, and the amount of financing the top five telecom equipment makers had provided to customers exceeded 123% of their combined earnings.
Ultimately, the amount of fiber-optic cabling and switching equipment installed far exceeded demand, and when the bubble burst and many of those customers went bust, the telecom equipment makers were left holding the bad debt on their balance sheets. This contributed to a greater loss of value when the bubble burst than would have otherwise been the case, with networking equipment businesses losing more than 90% of their value over the ensuing decade.
Worse yet were companies such as fiber-optic giant Global Crossing that engaged in direct “revenue roundtripping.” These companies cut deals—often at the end of a quarter in order to hit topline forecasts—in which they paid money to another company for services, and then that company agreed to purchase equipment of exactly equal value. When the bubble burst, Global Crossing went bankrupt, and its executives ultimately paid large legal settlements related to revenue roundtripping.
It is memories of these kinds of transactions that have caused analysts to at least raise an eyebrow at some of Nvidia’s circular investments. Goldberg, the Seaport Global analyst, said the deals had a whiff of circular financing and were emblematic of “bubble-like behavior.”
“The action will clearly fuel ‘circular’ concerns,” Stacy Rasgon, an analyst with Bernstein Research, wrote in an investor note following Nvidia’s announcement of its blockbuster investment in OpenAI. It’s a long way from a concern to a crisis, of course, but as AI company valuations get higher, that distance is starting to close.
