NVDA
Nvidia Corp
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NVDA goes to 247 this week

Cause of NVDA earnings?

Growing financing obligations could compound the pain of a downturn
By 
[Asa Fitch](https://archive.is/o/6rUhG/https://www.wsj.com/news/author/asa-fitch)
Aug. 25, 2026 5:30 am ET
Nvidia CEO Jensen Huang is increasingly tapping the company’s financial strength to keep customers buying. Manami Yamada/Reuters
[Nvidia’s](https://archive.is/o/6rUhG/https://www.wsj.com/market-data/quotes/NVDA) [NVDA -2.91%decrease; down pointing triangle](https://archive.is/o/6rUhG/https://www.wsj.com/market-data/quotes/NVDA) current financial position looks rock solid to say the least. But the financial engineering it is using to keep revenue growing introduces risks that could eventually cause real pain.
Nearly four years into an artificial intelligence boom that has brought Nvidia hundreds of billions of dollars in profit, the company is increasingly tapping its financial strength to keep customers buying its chips. Those chips have become the ubiquitous computational workhorses of the AI boom, a status quo Nvidia has an interest in maintaining.
Nvidia recently provided backstops that could put it on the hook for some $230 billion in lease obligations and residual-value deals, including a [$105 billion backstop](https://archive.is/o/6rUhG/https://www.wsj.com/articles/openai-locks-in-lease-for-huge-data-center-in-ohio-with-backing-from-nvidia-7474bb9c) for an [OpenAI](https://archive.is/o/6rUhG/https://www.wsj.com/topics/subject/openai) lease in Ohio and [potentially up to $125 billion](https://archive.is/o/6rUhG/https://www.wsj.com/tech/ai/why-wall-street-and-nvidia-are-building-an-exotic-money-pipeline-for-the-ai-boom-346ba482) in “residual-value support” for financing deals with Wall Street heavyweights. That support would likely entail Nvidia’s assuring that the value of assets backing loans won’t fall below a predetermined level.
Nvidia also [recently signed deals](https://archive.is/o/6rUhG/https://blogs.nvidia.com/blog/nvidia-unlocks-ai-compute-at-scale-capital-partners-to-power-ai-infrastructure-buildout/) with two young cloud-computing companies in Australia where it acts as a customer of last resort if they can’t find others to rent their computing power to. In exchange, Nvidia gets a share of the companies’ revenue from those assets above an agreed-upon level. The backstops give lenders confidence to extend financing with which the companies buy Nvidia’s chips.
Those promises don’t include Nvidia’s [agreement last year](https://archive.is/o/6rUhG/https://www.sec.gov/Archives/edgar/data/1769628/000176962825000047/crwv-20250909.htm) to buy unsold cloud-computing capacity from [CoreWeave](https://archive.is/o/6rUhG/https://www.wsj.com/market-data/quotes/CRWV) as part of a $6.3 billion deal. Nor do they include the equity stakes Nvidia has taken in many of the cloud companies and AI labs that it is providing backstops for, including CoreWeave. The company had $72.5 billion of public and private-company stakes at the end of its last fiscal quarter.
Nvidia can easily absorb some big impacts, with more than $80 billion of cash and marketable securities on its balance sheet as of its last fiscal quarter. It also isn’t likely that Nvidia would be liable for its entire lease backstops, which reduce over time.
But Nvidia’s venture into finance appears poised to become much deeper. The company [described its deals](https://archive.is/o/6rUhG/https://blogs.nvidia.com/blog/nvidia-unlocks-ai-compute-at-scale-capital-partners-to-power-ai-infrastructure-buildout/) with the two cloud-computing players in Australia as a “new business model,” suggesting it could act as a financial guarantor many more times over. And its financial backstops for OpenAI and the Wall Street firms create an expectation that Nvidia will lend more support to other large data center projects. 
Part of what Nvidia is doing is spreading its bets so it is less reliant on a handful of tech giants like [Amazon.com](https://archive.is/o/6rUhG/amazon.com/) and [Microsoft](https://archive.is/o/6rUhG/https://www.wsj.com/market-data/quotes/MSFT). Those companies are running out of financial steam.
Yields on AI-linked Big Tech bonds [are surging](https://archive.is/o/6rUhG/https://www.wsj.com/finance/investing/how-to-play-the-flood-of-ai-bonds-279f6ba5) because there is such a large supply of them. With no end in sight for debt issuances, borrowing costs for AI projects will likely stay high. And the tech companies are already [heavily committed to data center projects](https://archive.is/o/6rUhG/https://www.wsj.com/tech/ai/why-big-techs-ai-spending-is-3-trillion-higher-than-it-seems-e1067bb2), with $904 billion of leases not yet started and $1.52 trillion of purchase commitments largely related to AI, per their most recent financial statements.
There is thus some logic in Nvidia trying to generate sales from smaller and less-creditworthy companies. But history also provides examples of companies for whom courting less-creditworthy customers backfired spectacularly.
In the dot-com bubble, telecom-equipment leaders like Lucent Technologies, which was spun out of [AT&T](https://archive.is/o/6rUhG/https://www.wsj.com/market-data/quotes/T) in the mid-1990s, sought to court a new breed of small-time operators created following industry deregulation in the U.S.
To boost sales in a fast-growing market, Lucent extended financing to these less-creditworthy customers for purchases of its products. It guaranteed third-party loans to customers. And it made off-the-books guarantees to distributors of its products, according to an [SEC complaint](https://archive.is/o/6rUhG/https://www.sec.gov/files/litigation/complaints/comp18715.pdf%23:~:text=During%20Lucent's%20fiscal%20year%201999%20until%20the,resulted%20in%20significant%20uncertainties%20surrounding%20those%20transactions.) in 2004 that resulted in a settlement. It agreed to buy back any unsold equipment from those distributors, but improperly recognized the sales to distributors as revenue, the SEC alleged.
Lucent’s financial engineering was a major factor in its downfall. It ended up downsizing to about a third of its original workforce and merged with France’s Alcatel in 2006.
Vendor financing “helped make possible growth rates that did not seem possible,” Lisa Heffernan wrote in a 2004 book about the company’s demise. “Vendor financing,” she wrote, “opened doors that were shut for a reason.”
Nvidia, of course, is no Lucent. It is far stronger financially. All indications are that supplies of AI chips aren’t likely to catch up with demand for at least another year or two. But the scale of the financing deals it is entering into looks increasingly risky in the longer term.
“The question is, is this a trend?” said Wolfe Research analyst Chris Caso. “Does this become the principal way of financing these data centers, and the chip company provides backstops? That would be more concerning, in my view.”
The overarching problem for Nvidia is that its deals concentrate the risk it is taking on AI.
Participating in a larger slice of the industry downstream of those chips, including lease backstops, residual-value guarantees and even equity stakes in customers, compounds the risks of an eventual weakening in AI chip demand. Instead of a simple reduction in revenue and profit, a downturn scenario could stress Nvidia’s balance sheet. Reductions in the value of its investments could hit profit further.
It isn’t clear what kinds of internal controls Nvidia has to guard against getting overextended financially. Nor has the company said whether it is setting aside cash reserves as a buffer for specific financing or lease backstops. Analysts will likely ask questions about those measures when the company reports earnings on Wednesday. Investors have a lot of confidence in Nvidia’s technological prowess but might have less in its financial engineering.
Nvidia’s venture into financing could help it fulfill shifting demand. But it leaves the company with vanishingly little room for error as it tries to stay at the forefront of the AI boom.
**My take away:** AI demand is increasingly supported by financing relationships among chipmakers, hyperscalers, AI laboratories, and financial institutions. This financing allows customers to keep purchasing infrastructure even when their independent revenue may not justify the spending. The system can continue while capital remains available, but a reduction in hyperscaler spending, weak AI monetization, or rapid hardware depreciation could break the cycle and set off a tsunami across the financial system.

All are waiting for NVDA earnings and focusing on chip stocks, and the money has already started flowing to other sectors.

In the next movie, after NVDA earnings Michael Burry will solemnly approach a white board in his office and write:
“-99% Im a fuckin stupid dickwad”

buying NVDA shares, buying cheap NVDA puts
cant lose

Arguing with a woman is like gambling on NVDA earnings... you will lose every time!

NVDA ER Debit Spread

I’m crying so hard why would you take so much risks 😭😭😭😭
I’m praying for NVDA earnings to be a catalyst but idk brother…

Gonna buy some NVDA puts right at close tomorrow for a guaranteed payout lol

There was a giant transaction on TAN last week, the solar tracking etf. Since then it's done nothing. it makes me wonder if someone knows something about NVDA earnings and some funding that may go towards alternate energy sources for data centers

Given that NVDA has been selling off prior to results, there’s a decent case to be made that maybe NVDA wouldn’t dip too much post results and instead go up. All will be known in a matter of hours

I heard Doritos is releasing a Jalapeño chip to challenge NVDA?

IV crush fucks the buying side. I’ve been selling 8/28 200p when NVDA was in the $19x range.
I’m happily looking forward to this Friday to keep the entire premium on it. Last ER I was able to sell some $235 calls that were about ATM through earnings. Not doing so this time as I was expecting a much bigger run up by now but the short puts are cooking.

I’m no subject matter expert, but I immediately notice that this is an /inference/ chip, not a GPU. The promotional materials try to distract from that distinction by pointing out that Jalapeño is a general inference chip, not specifically optimized for OpenAI models. But it is specialized for inference operations, just not to any particular model. So any comparison to Rubin or Blackwell is definitely not apples to apples. Nvdia does have its own inference chip—that’s what it purchased (licensed?) Groq for—and its inference chip is in full production (but not yet released). So what we have here, as per the usual arrangement, is OpenAI releasing a questionable press release/product announcement hours before its competitor takes the spotlight to steal the thunder. Now I certainly expect there will be talk of the Groq chip on the earnings call and it’s true that if the Groq chip isn’t significantly better than Jalapeño, that’s not good news for NVDA. But color me skeptical.

indian analysts jacked up the revenue estimate above NVDA guidance, how can u do that?

NVDA earnings

Because it's dilution announcement is priced in and their last Q was absolutely bonkers. Memory is in and NVDA going to raise NBIS tomorrow with it

NVDA puts at these strikes will eat your soul before August.

NVIDIA (NVDA) Price Target Raised to $352.00 at Raymond James Financial