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Nvidia’s $100 billion investment in OpenAI has analysts asking about “circular financing” inflating an AI bubble

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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.



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Senate Dems’ plan to fix Obamacare premiums adds nearly $300 billion to deficit, CRFB says

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December 5, 2025

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The Committee for a Responsible Federal Budget (CRFB) is a nonpartisan watchdog that regularly estimates how much the U.S. Congress is adding to the $38 trillion national debt.

With enhanced Affordable Care Act (ACA) subsidies due to expire within days, some Senate Democrats are scrambling to protect millions of Americans from getting the unpleasant holiday gift of spiking health insurance premiums. The CRFB says there’s just one problem with the plan: It’s not funded.

“With the national debt as large as the economy and interest payments costing $1 trillion annually, it is absurd to suggest adding hundreds of billions more to the debt,” CRFB President Maya MacGuineas wrote in a statement on Friday afternoon.

The proposal, backed by members of the Senate Democratic caucus, would fully extend the enhanced ACA subsidies for three years, from 2026 through 2028, with no additional income limits on who can qualify. Those subsidies, originally boosted during the pandemic and later renewed, were designed to lower premiums and prevent coverage losses for middle‑ and lower‑income households purchasing insurance on the ACA exchanges.

CRFB estimated that even this three‑year extension alone would add roughly $300 billion to federal deficits over the next decade, largely because the federal government would continue to shoulder a larger share of premium costs while enrollment and subsidy amounts remain elevated. If Congress ultimately moves to make the enhanced subsidies permanent—as many advocates have urged—the total cost could swell to nearly $550 billion in additional borrowing over the next decade.

Reversing recent guardrails

MacGuineas called the Senate bill “far worse than even a debt-financed extension” as it would roll back several “program integrity” measures that were enacted as part of a 2025 reconciliation law and were intended to tighten oversight of ACA subsidies. On top of that, it would be funded by borrowing even more. “This is a bad idea made worse,” MacGuineas added.

The watchdog group’s central critique is that the new Senate plan does not attempt to offset its costs through spending cuts or new revenue and, in their view, goes beyond a simple extension by expanding the underlying subsidy structure.

The legislation would permanently repeal restrictions that eliminated subsidies for certain groups enrolling during special enrollment periods and would scrap rules requiring full repayment of excess advance subsidies and stricter verification of eligibility and tax reconciliation. The bill would also nullify portions of a 2025 federal regulation that loosened limits on the actuarial value of exchange plans and altered how subsidies are calculated, effectively reshaping how generous plans can be and how federal support is determined. CRFB warned these reversals would increase costs further while weakening safeguards designed to reduce misuse and error in the subsidy system.

MacGuineas said that any subsidy extension should be paired with broader reforms to curb health spending and reduce overall borrowing. In her view, lawmakers are missing a chance to redesign ACA support in a way that lowers premiums while also improving the long‑term budget outlook.

The debate over ACA subsidies recently contributed to a government funding standoff, and CRFB argued that the new Senate bill reflects a political compromise that prioritizes short‑term relief over long‑term fiscal responsibility.

“After a pointless government shutdown over this issue, it is beyond disappointing that this is the preferred solution to such an important issue,” MacGuineas wrote.

The off-year elections cast the government shutdown and cost-of-living arguments in a different light. Democrats made stunning gains and almost flipped a deep-red district in Tennessee as politicians from the far left and center coalesced around “affordability.”

Senate Minority Leader Chuck Schumer is reportedly smelling blood in the water and doubling down on the theme heading into the pivotal midterm elections of 2026. President Donald Trump is scheduled to visit Pennsylvania soon to discuss pocketbook anxieties. But he is repeating predecessor Joe Biden’s habit of dismissing inflation, despite widespread evidence to the contrary.

“We fixed inflation, and we fixed almost everything,” Trump said in a Tuesday cabinet meeting, in which he also dismissed affordability as a “hoax” pushed by Democrats.​

Lawmakers on both sides of the aisle now face a politically fraught choice: allow premiums to jump sharply—including in swing states like Pennsylvania where ACA enrollees face double‑digit increases—or pass an expensive subsidy extension that would, as CRFB calculates, explode the deficit without addressing underlying health care costs.



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Netflix–Warner Bros. deal sets up $72 billion antitrust test

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December 5, 2025

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Netflix Inc. has won the heated takeover battle for Warner Bros. Discovery Inc. Now it must convince global antitrust regulators that the deal won’t give it an illegal advantage in the streaming market. 

The $72 billion tie-up joins the world’s dominant paid streaming service with one of Hollywood’s most iconic movie studios. It would reshape the market for online video content by combining the No. 1 streaming player with the No. 4 service HBO Max and its blockbuster hits such as Game Of Thrones, Friends, and the DC Universe comics characters franchise.  

That could raise red flags for global antitrust regulators over concerns that Netflix would have too much control over the streaming market. The company faces a lengthy Justice Department review and a possible US lawsuit seeking to block the deal if it doesn’t adopt some remedies to get it cleared, analysts said.

“Netflix will have an uphill climb unless it agrees to divest HBO Max as well as additional behavioral commitments — particularly on licensing content,” said Bloomberg Intelligence analyst Jennifer Rie. “The streaming overlap is significant,” she added, saying the argument that “the market should be viewed more broadly is a tough one to win.”

By choosing Netflix, Warner Bros. has jilted another bidder, Paramount Skydance Corp., a move that risks touching off a political battle in Washington. Paramount is backed by the world’s second-richest man, Larry Ellison, and his son, David Ellison, and the company has touted their longstanding close ties to President Donald Trump. Their acquisition of Paramount, which closed in August, has won public praise from Trump. 

Comcast Corp. also made a bid for Warner Bros., looking to merge it with its NBCUniversal division.

The Justice Department’s antitrust division, which would review the transaction in the US, could argue that the deal is illegal on its face because the combined market share would put Netflix well over a 30% threshold.

The White House, the Justice Department and Comcast didn’t immediately respond to requests for comment. 

US lawmakers from both parties, including Republican Representative Darrell Issa and Democratic Senator Elizabeth Warren have already faulted the transaction — which would create a global streaming giant with 450 million users — as harmful to consumers.

“This deal looks like an anti-monopoly nightmare,” Warren said after the Netflix announcement. Utah Senator Mike Lee, a Republican, said in a social media post earlier this week that a Warner Bros.-Netflix tie-up would raise more serious competition questions “than any transaction I’ve seen in about a decade.”

European Union regulators are also likely to subject the Netflix proposal to an intensive review amid pressure from legislators. In the UK, the deal has already drawn scrutiny before the announcement, with House of Lords member Baroness Luciana Berger pressing the government on how the transaction would impact competition and consumer prices.

The combined company could raise prices and broadly impact “culture, film, cinemas and theater releases,”said Andreas Schwab, a leading member of the European Parliament on competition issues, after the announcement.

Paramount has sought to frame the Netflix deal as a non-starter. “The simple truth is that a deal with Netflix as the buyer likely will never close, due to antitrust and regulatory challenges in the United States and in most jurisdictions abroad,” Paramount’s antitrust lawyers wrote to their counterparts at Warner Bros. on Dec. 1.

Appealing directly to Trump could help Netflix avoid intense antitrust scrutiny, New Street Research’s Blair Levin wrote in a note on Friday. Levin said it’s possible that Trump could come to see the benefit of switching from a pro-Paramount position to a pro-Netflix position. “And if he does so, we believe the DOJ will follow suit,” Levin wrote.

Netflix co-Chief Executive Officer Ted Sarandos had dinner with Trump at the president’s Mar-a-Lago resort in Florida last December, a move other CEOs made after the election in order to win over the administration. In a call with investors Friday morning, Sarandos said that he’s “highly confident in the regulatory process,” contending the deal favors consumers, workers and innovation. 

“Our plans here are to work really closely with all the appropriate governments and regulators, but really confident that we’re going to get all the necessary approvals that we need,” he said.

Netflix will likely argue to regulators that other video services such as Google’s YouTube and ByteDance Ltd.’s TikTok should be included in any analysis of the market, which would dramatically shrink the company’s perceived dominance.

The US Federal Communications Commission, which regulates the transfer of broadcast-TV licenses, isn’t expected to play a role in the deal, as neither hold such licenses. Warner Bros. plans to spin off its cable TV division, which includes channels such as CNN, TBS and TNT, before the sale.

Even if antitrust reviews just focus on streaming, Netflix believes it will ultimately prevail, pointing to Amazon.com Inc.’s Prime and Walt Disney Co. as other major competitors, according to people familiar with the company’s thinking. 

Netflix is expected to argue that more than 75% of HBO Max subscribers already subscribe to Netflix, making them complementary offerings rather than competitors, said the people, who asked not to be named discussing confidential deliberations. The company is expected to make the case that reducing its content costs through owning Warner Bros., eliminating redundant back-end technology and bundling Netflix with Max will yield lower prices.



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The rise of AI reasoning models comes with a big energy tradeoff

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December 5, 2025

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Nearly all leading artificial intelligence developers are focused on building AI models that mimic the way humans reason, but new research shows these cutting-edge systems can be far more energy intensive, adding to concerns about AI’s strain on power grids.

AI reasoning models used 30 times more power on average to respond to 1,000 written prompts than alternatives without this reasoning capability or which had it disabled, according to a study released Thursday. The work was carried out by the AI Energy Score project, led by Hugging Face research scientist Sasha Luccioni and Salesforce Inc. head of AI sustainability Boris Gamazaychikov.

The researchers evaluated 40 open, freely available AI models, including software from OpenAI, Alphabet Inc.’s Google and Microsoft Corp. Some models were found to have a much wider disparity in energy consumption, including one from Chinese upstart DeepSeek. A slimmed-down version of DeepSeek’s R1 model used just 50 watt hours to respond to the prompts when reasoning was turned off, or about as much power as is needed to run a 50 watt lightbulb for an hour. With the reasoning feature enabled, the same model required 7,626 watt hours to complete the tasks.

The soaring energy needs of AI have increasingly come under scrutiny. As tech companies race to build more and bigger data centers to support AI, industry watchers have raised concerns about straining power grids and raising energy costs for consumers. A Bloomberg investigation in September found that wholesale electricity prices rose as much as 267% over the past five years in areas near data centers. There are also environmental drawbacks, as Microsoft, Google and Amazon.com Inc. have previously acknowledged the data center buildout could complicate their long-term climate objectives. 

More than a year ago, OpenAI released its first reasoning model, called o1. Where its prior software replied almost instantly to queries, o1 spent more time computing an answer before responding. Many other AI companies have since released similar systems, with the goal of solving more complex multistep problems for fields like science, math and coding.

Though reasoning systems have quickly become the industry norm for carrying out more complicated tasks, there has been little research into their energy demands. Much of the increase in power consumption is due to reasoning models generating much more text when responding, the researchers said. 

The new report aims to better understand how AI energy needs are evolving, Luccioni said. She also hopes it helps people better understand that there are different types of AI models suited to different actions. Not every query requires tapping the most computationally intensive AI reasoning systems.

“We should be smarter about the way that we use AI,” Luccioni said. “Choosing the right model for the right task is important.”

To test the difference in power use, the researchers ran all the models on the same computer hardware. They used the same prompts for each, ranging from simple questions — such as asking which team won the Super Bowl in a particular year — to more complex math problems. They also used a software tool called CodeCarbon to track how much energy was being consumed in real time.

The results varied considerably. The researchers found one of Microsoft’s Phi 4 reasoning models used 9,462 watt hours with reasoning turned on, compared with about 18 watt hours with it off. OpenAI’s largest gpt-oss model, meanwhile, had a less stark difference. It used 8,504 watt hours with reasoning on the most computationally intensive “high” setting and 5,313 watt hours with the setting turned down to “low.” 

OpenAI, Microsoft, Google and DeepSeek did not immediately respond to a request for comment.

Google released internal research in August that estimated the median text prompt for its Gemini AI service used 0.24 watt-hours of energy, roughly equal to watching TV for less than nine seconds. Google said that figure was “substantially lower than many public estimates.” 

Much of the discussion about AI power consumption has focused on large-scale facilities set up to train artificial intelligence systems. Increasingly, however, tech firms are shifting more resources to inference, or the process of running AI systems after they’ve been trained. The push toward reasoning models is a big piece of that as these systems are more reliant on inference.

Recently, some tech leaders have acknowledged that AI’s power draw needs to be reckoned with. Microsoft CEO Satya Nadella said the industry must earn the “social permission to consume energy” for AI data centers in a November interview. To do that, he argued tech must use AI to do good and foster broad economic growth.



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