Nvidia&#x27;s $500B AI Infrastructure Financing Plan Creates Secondary Market for Aging GPUs

AI's infrastructure boom is getting more leveraged -- and harder to track

* Hyperscalers' debt issuance and Situational Awareness's unravelling have brought the increasingly leveraged foundations of the AI boom into sharp focus. * Nvidia has unveiled plans for a new AI funding push that could involve using infrastructure as an investable asset. * Some strategists say earnings expectations, rather than growing leverage, could still be a bigger concern for markets. In this article * SKHY Follow your favorite stocksCREATE FREE ACCOUNT As Nvidia partners with Wall Street firms to mobilize more than $500 billion of third-party capital for AI infrastructure, the increasingly complex financing underpinning the boom is coming under closer scrutiny. Hyperscalers and their financial backers are turning to bond markets, joint ventures, leases and other structures to fund an unprecedented infrastructure buildout. At the same time, leverage is increasing investors' AI exposure, as hedge funds and other investors use prime brokerage borrowing and derivatives to amplify returns on their bets on the boom. But the unravelling of AI-focused hedge fund Situational Awareness, after losses on its leveraged equity bets, is heightening concerns over how much is being borrowed, where it sits, how visible it is, and how quickly it could unwind, as market watchers debate whether revenues justify the scale of spending. Stock Chart IconStock chart icon Nvidia. How much is being spent on AI infrastructure? Nvidia's plan to develop platforms for AI infrastructure in partnership with Apollo, Blackstone, BlackRock, Brookfield, KKR and Goldman Sachs could involve private asset-like structures and asset-based financing. Nvidia CEO Jensen Huang told CNBC Monday that Nvidia's chips are now an "investable infrastructure asset." Some tech giants are using joint ventures and other leasing vehicles to borrow money for AI data center spending -- without the debt appearing on their balance sheets until the leases begin. Goldman Sachs analysts estimated that hyperscalers have combined lease commitments for data centers, R&D facilities, offices and equipment of $1.5 trillion, up from about $200 billion five years ago. This includes about $1 trillion of "uncommenced" lease commitments, which are not yet shown in financial statements but will result in future payments. This "can understate leverage and future liquidity needs as these obligations are eventually recognized and contractual payments come due," Goldman analysts said in the Aug. 6 note. This surge in debt issuance -- including less-visible forms of leverage -- is sharpening the focus on whether the eventual returns from AI infrastructure can justify the vast sums being spent. Lotfi Karoui, multi-asset credit strategist at PIMCO, said the AI capex cycle is, adjusted for inflation, on track to be the largest investment cycle since the 19th-century railway construction. But the ultimate scale of the buildout remains "deeply uncertain," he said in PIMCO commentary dated Aug. 11, highlighting consensus forecasts that hyperscaler capital spending alone will surpass $1 trillion per year from 2027 onward, "with no clear signs of moderation." watch now VIDEO5:3005:30 Nvidia's $500 billion financing deal: How to trade it Halftime Report Karoui said that the scale of hyperscalers' borrowing is such that they are diversifying their debt issuance beyond dollar-denominated paper, with issuers tapping euro, sterling, yen, Swiss franc and Canadian dollar markets. He added that the relative outperformance of euro-denominated bond spreads issued by Amazon and Alphabet, compared with their U.S. counterparts, potentially hints at "demand fatigue" in the dollar market relative to euro-denominated paper. He warned that the wave of AI-related issuance in the U.S. could see spreads drift higher because of the underperformance of a handful of larger AI-exposed issuers. Is AI leverage becoming a bigger market risk? Situational Awareness' collapse showed how vulnerable crowded, leveraged AI trades can be to the sharp sell-offs and rallies the sector has seen recently. The fund was unable to meet a series of margin calls from lenders after its heavily concentrated portfolio -- which included names such as SK Hynix and CoreWeave -- suffered during a recent tech sell-off and its assets fell from $45 billion to about $10 billion. Ken Griffin's larger, multi-strategy hedge fund Citadel later stepped in to buy Situational Awareness' publicly listed positions at a discount. SK Hynix and CoreWeave have since rallied. JPMorgan CEO Jamie Dimon recently told CNBC's Leslie Picker that margin debt is "pretty high," adding that it increases the risk of amplified volatility. Sahil Mahtani, director of the investment institute at Ninety One, told CNBC that elevated earnings expectations were a more immediate concern than leverage Stock Chart IconStock chart icon SK Hynix. He said expectations "of high and rising earnings in the years ahead" were "the main risk" the AI trade posed to markets. "That is primarily an expectations problem rather than a leverage problem," Mahtani said via email. He said equity concentration is "historically high" in tech-heavy markets, especially the U.S. While that may not be financial leverage, he said the concentration can act like leverage by amplifying market moves when heavily weighted stocks fall. "The big equity indices are extremely concentrated, and no one thinks anything could possibly derail them," Mahtani added, but warned that a shift from companies buying back shares to issuing more stock could remove a source of support for equity prices just as AI-related valuations are already under pressure. Mahtani said the Situational Awareness debacle reflected poor risk management, but that its broader impact had been largely contained. "Its bull run coincided with the unwind of leveraged ETF structures, primarily in East Asia. Many of these structures, particularly the single-stock structures, were only launched in H1 of this year. In that sense, it is a relatively contained case study." A spokesperson for the Alternative Investment Management Association, the global trade body for the hedge fund and alternatives industry, said leverage was a "core tool" used by hedge funds to boost returns and provide market liquidity. "The key question is not whether hedge funds use leverage, but whether its use poses a material threat to financial stability. The available evidence does not support treating hedge fund leverage as an inherent systemic risk," the spokesperson told CNBC. They said that two previous leverage-related ruptures -- the collapse of Archegos Capital Management in 2021 and the 2022 U.K. Liability-Driven Investment gilt market stress -- involved different structures and investors. "It is important not to lump very different market events together. Archegos was a family office, not a hedge fund, while the 2022 gilt episode centred on leveraged LDI strategies used by pension funds. We have seen no reason to expect the Situational Awareness episode, in itself, to trigger a fresh review of the rules governing hedge fund leverage." Choose CNBC as your preferred source on Google and never miss a moment from the most trusted name in business news.

[6]

TechSpot

Nvidia may have just built its own hyperscaler without owning a single data center

Serving tech enthusiasts for over 25 years. TechSpot means tech analysis and advice you can trust. Why it matters: Nvidia has quietly assembled every piece of a cloud giant, and it doesn't even need to own the buildings. That is the theory making the rounds, and once you see it laid out, the last two years stop looking like a chip company having a very good run and start looking like a plan. The financing arrangement Nvidia signed this month with BlackRock, Goldman Sachs, and four other Wall Street heavyweights, aimed at funneling more than $500 billion of outside capital into AI data centers, would be the last piece clicking into place. Most outlets filed it under the now usual "more AI money" headline, but there is a more interesting read. I should note, going deep into data center financing is not our usual beat. However, we do cover big tech, and Nvidia at this point is the biggest of them all, and it's not thanks to gaming GPUs. The framing that tech analyst Ryan Shrout gave to this announcement caught our attention. He pointed at a post by Clark Tang, calling it "a theory of what is happening right beneath our noses by Nvidia." We are reading these reports the same way you probably are, as tech people watching an industry rearrange itself in real time. Tang is a partner at Altimeter Capital who covers AI and semiconductors, and who is best known publicly for calling Nvidia early and being right about it. Keep that in mind, because he is arguing the bull case on a company he almost certainly has a position in. His thesis in one line: what we are watching is Nvidia speedrunning the creation of a "synthetic hyperscaler." The argument is a good one though, and there is enough data behind it to kick the tires. So what is a hyperscaler (again)? Strip away the branding and Amazon AWS, Microsoft Azure, and Google Cloud are really two businesses wearing one logo. * The first business is financial. It pools everybody's hardware spending and smooths it out, so you rent infrastructure as an operating expense instead of buying it as a capital expense. * The second is operational. It writes software that hides the hardware so thoroughly that you never have to think about the machine your code is running on. Put those two together and it works like this: buy hardware in bulk, borrow money cheaply, and then use software to slice one box across many customers so it is never sitting idle, and you get the number that has defined cloud computing for the last 15 years: an operating margin somewhere in the 35% to 40% range. But AI came along and broke that recipe. The old cloud playbook does not work on AI workloads AI training requires a single enormous cluster where every node stays in lockstep, and a single straggling node stalls everything. Inference wants tokens per watt and fast time to first token. Neither one cares how many virtual machines you can cram into a chassis, which was the entire optimization target of the cloud era. A warehouse full of cheap, redundant CPUs is a wonderful business right up until the job becomes a synchronous training run. Add a hard ceiling on available power, and the economics of the building flip. Nvidia noticed. So did the hyperscalers, and here is where Tang's argument gets interesting. The hyperscalers are massive tech companies with an established fleet of distributed data centers earning that 35% to 40% operating margin. It was in their interest to commoditize Nvidia's hardware, which carries roughly 75% gross margins, when an in-house ASIC could in theory do a similar job at a fraction of the markup. So the cloud giants built their own accelerators: Google has TPUs, Amazon has Trainium and Inferentia, Microsoft has Maia, and Meta has MTIA. They own the enterprise relationships and everyone's data sits captive on their platforms. They can also move at their own pace, which meant Nvidia's ability to push faster hardware was tied to how quickly its largest customers felt like moving. Enter "Neoclouds" This created an opening. A group of entrepreneurs looked at the fat margins the hyperscalers were earning on what was essentially stock Nvidia hardware with a software layer on top, and decided they could do that for less. Enter the neoclouds, which co-developed software with Nvidia specifically for these workloads: hot swaps, predictive maintenance, storage built for training pipelines with cheaper ingress and egress because the goal was winning workloads rather than trapping data. Bare metal, no virtualization overlays dragging clusters below Nvidia's own reference performance. And, crucially, a willingness to operate at roughly 20% margins that the big clouds would never accept. What the neoclouds could not replicate was the investment-grade balance sheet needed for the buildout. Lenders would only finance GPUs that already had a signed customer attached, which ruled out building ahead of demand. That is the constraint CoreWeave, Nebius, Lambda, Crusoe, and Nscale have all had to work around while the incumbents could simply write the check. Tang argues that advantage is eroding anyway. Google just posted its first negative free cash flow quarter and raised $50 billion in equity, and Microsoft is carrying $329 billion in leases that are signed but have not yet started. If even Google and Microsoft are stretched, the money for everyone else has to come from outside. What Nvidia has actually been building Line up what Nvidia has been shipping for the past two years and Tang's case is that they now have both halves of a hyperscaler, just distributed across other people's companies. The operational half: DSX OS and Mission Control for running GPU fleets, DSX reference designs and Omniverse digital twins as playbooks for building the facility itself, and Dynamo for inference serving. In other words, the secret sauce that used to be a hyperscaler moat, handed to any competent team with a site and power. The financial half is the part that landed last week. Nvidia signed Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR to create independent financing platforms targeting more than $500 billion of third-party capital. The pitch to those investors is that Nvidia standardized the asset (AI infrastructure) with reference designs, and that the compute is, in Jensen Huang's words, "fungible and transferable across customers and operators." That is what turns a warehouse of depreciating silicon into something an infrastructure fund can actually underwrite. But it took Nvidia a few years for this to take proper shape. The CoreWeave master agreement dates to 2023, the BlackRock AI infrastructure partnership to 2024, Brookfield's $100 billion vehicle to 2025, KKR to this year. Six financing platforms later, Tang's one-word summary of the sequence: chess. The earnings that explain why the money had to come from outside Conveniently, three neoclouds reported in the same week, and App Economy Insights put the numbers side by side. They read like a stack of evidence for exactly the problem the financing platforms are meant to solve... * CoreWeave is the purest version of the model: buy GPUs, rack them, rent them to OpenAI, Microsoft, and Meta. Revenue more than doubled to $2.6 billion, with 98% of it coming from committed contracts rather than on-demand usage. And it still lost $626 million. Note where that loss comes from: the operating loss was only $49 million, while interest on its GPU-collateralized debt came to $640 million. The business roughly breaks even on operations and the financing eats it alive. * Nebius, rebuilt as an AI cloud out of the Yandex breakup, grew revenue 454% to $582 million with gross margin up to 77%, and still posted a $176 million operating loss because depreciation alone came to $260 million as new infrastructure hit the books. However payback in new contracts is going down, and customers are prepaying more than $9 billion in 2026, which means the customers have quietly become the lenders. * Cerebras is renting its own wafer-scale silicon rather than Nvidia's, and its $477 million operating loss is mostly post-IPO stock compensation noise against a $34 million core loss. The detail that stuck with us is that Cerebras is temporarily renting back systems it had already sold in order to meet cloud demand. If you want a single image for how tight compute is right now, that is it. Put the three together and the trailing free cash flow reads negative $13.7 billion, negative $5.9 billion, and negative $0.7 billion. Demand is contracted years out. The cash goes out the door years early. That gap is what $500 billion of outside capital is for. The obvious objections Tang takes the three big criticisms head on. On circularity, his argument is that August 10 was the opposite of Nvidia financing its own demand, since six firms underwriting separately replaces Nvidia's balance sheet rather than extending it. Fair, though we would note these are memorandums of understanding, and nobody has disclosed a dollar as committed. On whether GPUs hold their value long enough to underwrite, he points to CoreWeave contracting six-year-old Nvidia A100s through 2029 and pushing a roughly 25% price increase across its fleet in July. The collateral, he argues, is aging like an aircraft rather than a smartphone. $500 billion that can only buy Nvidia reference architecture is "a moat dressed up as a risk." On the complaint that all this capital stays tethered to Nvidia and starves rival accelerators, he has the best line in the post: $500 billion that can only buy Nvidia reference architecture is "a moat dressed up as a risk." The business side of enterprise tech (and bubble talk) We are reading this as interested observers rather than infrastructure analysts. But if you have been following the memory price spikes, the data center construction boom, the AI-related layoffs, and the endless stream of vibe-coded projects and bug bounties, this is the machinery running underneath all of it. It is also where the bubble question actually lives. Not in whether the chatbots are useful, but in whether the money being committed to buildings and GPUs today gets repaid by revenue that has not arrived yet. The neoclouds are burning cash at a rate that leaves very little room for demand to wobble. And they are not the only ones building. Meta is scaling its own silicon by the gigawatt, and SpaceX has started selling access to its Colossus cluster. So do the neoclouds stay essential infrastructure partners, or do they turn out to be relief valves that get squeezed shut once mega-cap capacity finally lands? What is harder to argue with is the shape of this new thing. Nvidia has published the operating software, the facility blueprints, and the serving stack, then arranged the capital, without owning the buildings, the power contracts, or the customer relationships. The idea is to collect on the hardware regardless of which logo ends up on the door. Whatever you want to call that, it is not just a chip company anymore.

[7]

NYT

Wall St. Wants Another Half-Trillion Dollars for the A.I. Boom

Six giant investment firms announced a $500 billion effort to raise money for customers of Nvidia to pay for computing power. In some quarters, the words "artificial intelligence" have never been less popular, as many worry about job losses, environmental impacts and plain old uncertainty. Not so on Wall Street, where six giant asset managers, private-equity firms and banks came together on Monday to announce an effort to raise $500 billion to keep fueling the A.I. boom by financing more data centers, power plants and chips. The firms -- BlackRock, Goldman Sachs and KKR among them -- said they were working together to come up with that huge sum to lend to Nvidia's customers, including the start-ups that use the company's chips in data centers to develop and operate A.I. software. These customers, Nvidia said, have been struggling to secure financing for chips and data centers. Nvidia will connect its customers with one of the six lenders, which will provide financing that could range from loans to credit. The financing will be "at attractive rates," Nvidia said in a blog post. Executives from the lenders joined Jensen Huang, Nvidia's chief executive, for an unusual, extended interview on CNBC, where they talked up their new, seemingly insatiable desire to finance infrastructure for A.I. "It's a hefty price tag," Mr. Huang said on the air. He said "A.I. labs" and "A.I. start-ups" would have access to the financing. He did not name those companies or whether Nvidia would receive any money as part of the effort. "We need to raise this money as fast as possible," said Larry Fink, BlackRock's chief executive. He also stated: "There's quite a bit of negativity around A.I. and data centers right now, but let's be clear: This is going to be creating a huge amount of jobs." David M. Solomon, Goldman's chief executive, said the consortium was Mr. Huang's idea. The announcement punctuates a head rush on Wall Street and in Silicon Valley into anything that even vaguely resembles A.I. The stocks of tech giants and chipmakers have soared for most of this year, and a pair of the biggest names in the space, Anthropic and OpenAI, are expected to file for initial public offerings that could value them at $1 trillion apiece. But plenty of questions remain about the cost of the boom and whether there will be enough demand for computing power to support all of the data centers under construction. Indeed, Nvidia stock dipped modestly on Monday after The Financial Times reported that the company was nearing the mammoth financing deal. And while the contours of the arrangements were announced Monday afternoon, details remained scarce. A joint news release referred only to "memorandums of understanding" to "create dedicated pools of capital at significant scale." During their television interview, the lenders' executives alluded vaguely to "yield-based products" and even securitization, or the creation of bonds that would divvy up the revenue from A.I. labs into risky and less risky categories. There were several references to A.I. as a new asset class and to allowing smaller investors an opportunity to invest in debt backed by the data centers. "This is the very beginning -- like what it was when I started in the mortgage-backed securities market in the 1970s," Mr. Fink said. "I look upon this as a next future for financial engineering."

[8]

BBC

Nvidia gets $500bn from major banks for AI build out

Nvidia has teamed up with some of Wall Street's largest banks to help raise $500bn (£370bn) in capital to develop artificial intelligence (AI) infrastructure. The chipmaker said it had struck deals with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR, and that the banks were for the first time treating AI hardware and infrastructure, often referred to as "compute", as a separate asset class. "In AI, compute is revenue", Jensen Huang, chief executive of Nvidia, said. "We are bringing the world's leading long-term capital providers together to independently underwrite AI infrastructure." The financing will go towards Nvidia's own projects and those being built by its partners. Infrastructure projects backed by this fund will include the construction of new data centres to house, operate, and cool miles of stacked computer chips that process AI data and actions. This will also back new factories to manufacture the AI chips needed to power these systems. "Compute has become a critical infrastructure asset", Joe Bae and Scott Nuttall, co-cheif executives of KKR, said in a joint statement. "As we've scaled our approach to digital infrastructure, we've learned that delivery, not ambition, is the hard part." Essentially every major technology and AI company uses Nvidia's computer chips, or graphics processing units (GPUs), to power their services, AI platforms and AI chatbots. Companies using Nvidia's popular chips or GPUs include Google, Meta, Amazon, Microsoft, SpaceX, Tesla, OpenAI and Anthropic. Such companies have collectively spent over $1 trillion in just three years on AI projects and infrastructure, with much more spending expected. And their demand for Nvidia's chips and services has driven the stock market value of the company up five fold in three years. In a statement on Monday, Huang referred to Nvidia's role as a chip-maker as the company's beginning. "Today, we are helping create a new class of productive, investable infrastructure: AI factories," he said. With a new ability to tap some funding from the banks partnering with Nvidia, such banks will be able to finance more of the AI boom. Jim Zelter, president of Apollo, a lender which manages more than $800 million in assets, said: "Modern compute has emerged as a scarce, mission-critical asset class." It is also "positioned to drive significant long-term economic growth and productivity gains", Zelter added. BlackRock last month entered into an individual deal with Meta to finance and take a majority ownership stake in one data centre in Texas. Anthropic also recently entered into a deal with Macquarie Asset Management and GIC, an investment bank in Singapore, for its own build-out of AI infrastructure. The company did not specify the size of the deal, but said more financing was needed as its popular chatbot Claude had become so popular that the "demand requires significant new compute".

[9]

Goldman Sachs is courting investors on Nvidia's $500bn AI-compute financing deal

Goldman Sachs has secured the role every Wall Street firm wanted, and it is now working the phones. The bank is in talks with investors about Nvidia's $500bn AI-compute financing deal, having landed a prized mandate that effectively casts it as the lead, and for now near-sole, lender behind one of the largest infrastructure-funding efforts the industry has produced. The mandate did not appear from nowhere. Goldman has a long relationship with Nvidia, having led the chipmaker's $25bn bond sale in June 2025, and that history helped it win pole position on a scheme that sits at the centre of the current six-firm push to fund the AI build-out. Goldman's contribution stretches across its business. It is putting up junior capital and private credit through its asset-management arm, while its investment bankers work to place the debt into private-credit funds and, eventually, into public debt markets. The bank is talking to US insurers, money managers, other banks, asset managers and private-credit firms, and it plans to keep a sizeable share of the paper itself. The clever part, and the part that should give sceptics pause, is the structure. The deal is designed to create an asset-backed market for AI compute, so the debt can trade like a traditional security and funding costs can fall. That is a deliberate departure from earlier AI-infrastructure deals, which leaned heavily on vendor guarantees rather than a proper tradable market. In other words, Goldman is trying to turn Nvidia's chips into an asset class. Just as mortgages were once bundled into securities that investors could buy and sell, the plan is to package the machines humming inside data centres into instruments that behave like bonds, complete with a secondary market and, the pitch goes, lower borrowing costs for everyone downstream. The comparison is flattering to nobody old enough to remember what happened the last time a bank promised that an untested asset would trade as safely as a government bond. The wider vehicle was unveiled on 10 August. The $500bn platform is a partnership of Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR, assembled to mobilise third-party capital rather than tie up the founders' own balance sheets. Nvidia, whose market value now sits around $5.2tn, is not merely a beneficiary; Jensen Huang has said the company has the option to backstop up to $125bn, or 25%, of the potential deals. Goldman's chief executive David Solomon was disarmingly candid about how it came together. "Jensen came, approached us with the idea, and we said we'd love to talk to you about it," he told CNBC, which is roughly what any banker would say about a fee-rich mandate landing in his lap. And the fees are the point. By sitting at the centre of the AI-debt boom, Goldman collects on the origination, the structuring, the placement and whatever it holds on its own books, a spread of income streams that makes the arrangement genuinely enviable, and largely insulated, regardless of how the underlying bet on compute ultimately plays out. This is also, unavoidably, financial engineering of the kind that makes European observers nervous. The AI economy is increasingly held together by loops in which the same handful of companies fund, supply and underwrite one another, a pattern already visible when Nvidia held talks to guarantee $250bn of OpenAI data-centre debt and as its equity bets topped $40bn this year. The market has already flinched once. Nvidia's $750bn of announced AI deals recently pushed its own credit-default swaps to a record, a quiet signal that even the chipmaker's backers are pricing in the risk that the circle may not hold. Goldman's job, in effect, is to make that risk look tradable. Whether it looks safe is a question the buyers will have to answer for themselves.

[10]

NVIDIA

NVIDIA AI Factory Compute Is Becoming an Investable Asset Class

We announced partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish independent financing platforms designed to mobilize over $500 billion of third-party capital to support the buildout of AI infrastructure over time. This is a major milestone for NVIDIA and the AI industry. We have moved from an era in which companies bought chips and built data centers project by project to one in which AI factories can be financed as productive infrastructure -- with repeatable platforms, long-term institutional capital and a diverse customer base that uses compute to create revenue. AI has reached an inflection point. It is moving from research into production. AI is creating real value, and the infrastructure behind it is becoming one of the world's most productive assets. In AI, compute is revenue. A New Infrastructure Asset NVIDIA compute is not just a chip. It is a complete AI factory platform including accelerated computing, networking, systems software, AI frameworks and a global developer ecosystem. NVIDIA DSX AI factories can run the world's broadest range of AI models, modalities and algorithms -- language, vision, speech, biology, physical AI and robotics. One NVIDIA AI factory can serve many customers and many workloads. That makes it flexible and fungible. It is also built on a globally adopted architecture used across every major cloud, and by systems makers and enterprises around the world. When needs change, the factory can be used by another customer, another cloud or another operator. This broad ecosystem gives NVIDIA compute a deep market of potential users and offtakers, helping protect residual value. CUDA makes the factory better over time. Every generation of NVIDIA software improves the performance, efficiency and total cost of ownership of already- installed infrastructure. The hardware does not stand still: software innovation allows an AI factory to produce more intelligence at lower cost throughout its life, extending its useful economic value. NVIDIA A100 is a powerful example. NVIDIA introduced the Ampere-based A100 in 2020, and six years later, it remains in active commercial use for AI training, fine-tuning, inference and high-performance computing. Customers continue to commit capacity for multi-year deployments, extending A100's economic life toward a decade. The market is also demonstrating the durability of NVIDIA compute economics. One-year H100 rental pricing rose from about $1.70 per GPU-hour in October 2025 to about $2.35 per GPU-hour in March 2026. Cross-provider on-demand median pricing rose from roughly $2.00 per GPU-hour in October 2025 to $2.70 in June 2026. Blackwell capacity commands a premium, with reported B200 cloud rates spanning approximately $5.30 to $7.05 per GPU-hour. That is what makes NVIDIA AI factories different. Their value is not fixed at installation: CUDA continuously improves their output; the installed base remains productive well beyond its initial depreciation period; and the same standard architecture serves a deep, growing global market of AI workloads. These are the characteristics of an investable infrastructure asset: it produces revenue, serves a broad market, improves in performance over time and can be redeployed. Bringing Capital to AI Factories The demand for AI infrastructure is extraordinary. But access to capital is uneven. Many great AI companies, enterprises and AI clouds have demand for compute but do not yet have access to financing at the scale or cost required to build quickly. That is why we are partnering with the world's leading long-term capital providers. Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR are also among the world's leading infrastructure investors, with deep expertise in underwriting long-lived, productive assets. Together, we are creating repeatable financing platforms to help the AI ecosystem build the factories it needs. The platforms are designed to help qualified AI labs, enterprises and AI clouds access AI-factory infrastructure at scale. The more than $500 billion figure represents aggregate third-party capital that these platforms are designed to mobilize over time -- the capital is not NVIDIA revenue, a single fund or a commitment to a single customer. The financial institutions will independently assess each opportunity -- the customer, demand, utilization, cash flow and residual value. NVIDIA provides the AI factory platform. The financial institutions provide long-term capital and financing expertise. The Important Questions Is this circular financing? This initiative is designed to address that concern. We are bringing independent, long-term institutional capital into the AI infrastructure market. The demand is real: it comes from frontier AI labs, AI-native startups, enterprises, cloud providers and countries building AI services. The capital providers independently underwrite each project -- including the customer, demand, utilization, cash flow and residual value. NVIDIA provides the platform; the investors make independent financing decisions. This is the beginning of an open capital market for AI infrastructure. Why would NVIDIA support financing? In some cases, NVIDIA may provide a residual-value support mechanism for up to 25% of an opportunity, assessed carefully on a project-by-project basis. That support is limited, residual-value based and designed to complement -- not replace -- independent underwriting. This is substantially lower than other compute-financing arrangements. NVIDIA can provide support because NVIDIA compute is unique: it is fungible, universally adopted, software-upgradable and redeployable across a large ecosystem of customers. Our role is to help unlock a very large pool of independent capital while maintaining disciplined risk exposure. Can the market absorb this capacity? The question is not whether we are building data centers. The question is whether we are building productive AI factories. An AI factory turns energy and data into valuable intelligence. Its customers are broad: frontier AI labs, AI clouds, enterprises and nations. They are building AI because it has become useful -- doing valuable work across every industry. There is discipline in the model. Each financing partner will independently evaluate demand, utilization, cash flow and residual value. Capacity will be built around real customer economics. Where is the return on investment? The return is in the usefulness of AI. Companies are using AI to write software, discover drugs, design products, serve customers, automate operations and build new services. AI factories make this possible. More compute creates better AI; better AI creates more usage; more usage creates more revenue; and more revenue drives more compute. This is the virtuous cycle of the AI industrial revolution. The Infrastructure of Intelligence Every industrial revolution has been built on infrastructure: electricity, transportation, communications and computing, with every buildout enabled by external financing. AI factories are the infrastructure of the intelligence era. With these partnerships, NVIDIA and the world's leading financial institutions are creating a new way to finance the infrastructure that will power this industrial revolution. We will make AI factories more accessible to the companies, industries and nations building the future. The age of AI is here. Together, we will build the infrastructure to power it.

[11]

Gizmodo

Top Wall Street Firms Reportedly Partnering With Nvidia for $500 Billion AI Investment

Some of the biggest financial firms in the world are reportedly getting ready to pour half a trillion dollars into a deal with Nvidia for AI infrastructure buildout. A consortium of Wall Street firms, including heavy hitters like Blackstone, BlackRock and Goldman Sachs, is working on a deal with Nvidia that would see the firms invest $500 billion in the AI industry, according to a Financial Times report citing six people briefed on the talks. The details of the deal aren't clear, but the FT along with reports from Bloomberg and Reuters all claim it could be announced as early as Monday. Circular dealmaking worries return The report comes on the heels of renewed fears of both Nvidia's alleged circular dealmaking and the eyewatering financial commitments the overall industry is making on the AI infrastructure buildout. Late last month, Nvidia announced a $500 billion deal with South Korean chipmaker SK Hynix. Shortly after that news was made public, various reports claimed that Nvidia would also make a $250 billion deal with OpenAI to help the AI giant finance its massive, power-hungry 10-gigawatt data center project in southern Ohio, likely to be one of the largest data centers in the world when construction finishes in 2028. If that deal materializes, it would be one of Nvidia's biggest financing deals with a customer, per Bloomberg. The $250 billion number would only cover the data center lease and debt, but the chipmaker is also reportedly discussing a separate $350 billion deal to finance AI chip purchases. The back-to-back reports are reigniting fears that Nvidia is weaving a tangled and potentially dangerous web of deal in which a handful of companies with overlapping interests have inked several multibillion-dollar investments among each other, all with the two AI darlings at the center: Nvidia and OpenAI. The financial dependencies could skew demand, concentrate risks and signal instability, experts warn, because if one deal goes down, it could create a domino effect that some say could engulf the entire American economy. Investment deals drawing more intense scrutiny These AI deals first came under intense public scrutiny after a high-profile $100 billion deal between OpenAI and Nvidia was announced in September 2025 (though the deal has failed to materialize and has reportedly been dropped). Investors were also unnerved last month when some AI hyperscalers, which are also Nvidia's largest clients and the major drivers of the AI buildout, reported considerable drops in cash flow in their earnings reports due to the hefty capital expenditures tied to AI infrastructure. Meta's free cash flow dropped almost $8 billion in one year, while Google's free cash flow turned negative for the first time in the tech giant's history. Some fear this could be a sign of recklessness in the market as companies commit huge amounts of cash to building out AI for demand that might not materialize as expected. Nvidia's future, meanwhile, depends in part on the financial health of these partners, since the chipmaker is the primary hardware supplier for their AI infrastructure buildout efforts.

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Reuters

Breakingviews - Jensen Huang takes wheel of $500 bln AI bandwagon

NEW YORK, August 11 (Reuters Breakingviews) - Nvidia's boss gathered Apollo, Goldman and others to help finance buyers of ⁠his company's GPUs. He is channeling the auto-loan market by using computing power as collateral as other funding sources thin. The chipmaker takes the driver's seat, with investors along for ⁠the ride. Full view will be published shortly. Context News* Chipmaker Nvidia said on August 10 that it ⁠had signed memorandums of understanding with Apollo Global Management, BlackRock, Blackstone, Brookfield, ⁠Goldman Sachs and KKR to help mobilize more ⁠than $500 billion to finance artificial intelligence infrastructure development. Editing by Jeffrey Goldfarb; Production by Pranav Kiran * Suggested Topics: * Breakingviews Breakingviews Reuters Breakingviews is the world's leading source of agenda-setting financial insight. As the Reuters brand for financial commentary, we dissect the big business and economic stories as they break around the world every day. A global team of about 30 correspondents in New York, London, Hong Kong and other major cities provides expert analysis in real time. Sign up for a free trial of our full service at https://www.breakingviews.com/trial and follow us on X @Breakingviews and at www.breakingviews.com. All opinions expressed are those of the authors. Jonathan Guilford Thomson Reuters Jonathan Guilford is Breakingviews' U.S. Editor, based in New York. He covers M&A and private markets. He joined Reuters Breakingviews in 2021 from Dealreporter, where he led risk arb coverage strategy from New York while covering technology, media and telecommunications. He previously covered the European healthcare services market. Karen Kwok Thomson Reuters Karen is a columnist based in New York focusing on global technology and venture capital sectors, writing stories about artificial intelligence, fintech, and semiconductor companies. She used to cover deals in the Middle East region and global metal mining sector. Prior to Breakingviews, she was a European gas and power reporter at S&P Global Platts in London and covered funds and equities at Morningstar UK. Karen also briefly worked at Bloomberg. Born and raised in Hong Kong, she is fluent in Mandarin and Cantonese.

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Wall Street giants bet Nvidia's AI chips will defy the laws of finance

Wall Street is betting that AI chips can defy one of finance's basic rules: that fast-moving technology quickly loses its value. Nvidia unveiled this week a $500bn deal under which tech groups will be able to lease semiconductors with financing from groups including Apollo Global, KKR, Brookfield, BlackRock and Goldman Sachs. The blockbuster partnership was underpinned by expectations that chip prices would remain higher for longer than many analysts had anticipated as a result of the clamour to secure the components powering the AI boom, finance executives involved in the deal told the FT. Nvidia chief Jensen Huang has said the pact will create a new asset class underpinned by chips, which would be ripe for investment from the $22tn private capital industry. Investment industry titans, including Blackstone's Jon Gray and BlackRock's Larry Fink, have similarly said that their firms are keen to deploy capital to tap into the insatiable appetite for new data centres to train and power the latest AI models. But the new funding model also comes with the risk that financiers misjudge the durability of demand for -- and the value of -- Nvidia's chips. "The whole thing is predicated on continual investment," said Ben Bajarin, a technology analyst at Silicon Valley-based Creative Strategies. "There's a risk of overbuild, that demand eases, that models improve and don't need as much compute." Unlike rental cars or commercial jets, which have a reliable pool of buyers if a customer defaults, chips' long-term value remains in question as the technology evolves quickly and demand fluctuates. For debt backed by chip leases, many lenders currently require the loans to be fully paid off within three to five years, under the assumption that the value of the underlying asset will be minimal after that. Buyers or lessees of chips also have to construct data centres, meaning anticipated revenue streams lag far behind their spending plans. Huang, however, has argued that even Nvidia's older H100 chips are holding their value longer than many forecast due to breakneck demand for computing power. In a post on X on Monday evening, Huang said the rental pricing for its recent chips had increased, and even its six-year-old A100 chips were still in use, longer than initial estimates of their lives. Nvidia's most powerful chips, which are also known as graphics processing units or GPUs, remain in high demand from AI labs training cutting-edge models, but tech groups are willing to use older hardware for simpler tasks such as answering queries. Nvidia has also extended the life of chips by regularly updating its software platform Cuda. The platform is central to Nvidia's dominance in AI processing, enabling customers to use GPUs, originally designed for graphics, to speed up AI applications. Bajarin said rampant demand for chips of all kinds was likely to bolster Nvidia's scheme in the medium term and that longer term its success would depend on continuing to lower the total cost of ownership for its products. Nvidia will also guarantee that the chips hold at least 25 per cent of their value through the lease term, putting the $5.3tn chip giant on the hook for any of their initial losses. "There is an intrinsic value to the GPU. Nvidia has a decade-long track record on what the rental unit for a GPU is," one executive participating in the $500bn Nvidia deal told the FT, referring to current rates on A100 chips. They characterised Nvidia's guarantee as "the first lost piece" of coming financings, meaning the company would absorb early losses in the value of chips beyond certain projections. Nvidia's guarantee has led private capital firms to believe that chip financing deals can be packaged into securities and sold to debt buyers such as insurance companies whose assets they manage, tapping large pools of capital inside firms such as Apollo, KKR and Brookfield. "Private capital has a unique role here," said another executive partnering with Nvidia, who predicted GPU leases would standardise pricing and create efficiencies for AI groups. Public debt investors would eventually enter the space, making the asset class easier to trade as "people begin to figure it out", they said. The structure of the deals will vary between financial companies. Some firms may create speciality finance companies for chips and structure their loans similarly to vehicles used to fund private equity buyouts, known as collateralised loan obligations. CLOs are broken up into multiple rating slices, allowing investors to choose between different risk levels. "You can capitalise the GPUs in different layers of risk, sort of like a CLO," said one executive. But others balked at that approach, with one noting that "everyone will fund it differently". The Wall Street financing could also solve another difficulty for Nvidia, relieving the pressure to finance its customers. The support from the world's largest financial institutions would mean that Nvidia could pivot away from vendor financing, through which Nvidia provides direct guarantees to help its clients raise debt in the capital markets, Vivek Arya, a research analyst at BofA Securities, said this week. Nvidia's deal with the Wall Street heavyweights was positive for the chipmaker, as "the burden sits with the consortium, not [Nvidia's] balance sheet".

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Investors question data center loan valuations after latest Nvidia financing move

The biggest names in finance gave their blessing to the AI computing buildout this week, partnering with chipmaker Nvidia to promote the company's computing capacity as an " investable asset class ." Larry Fink, CEO of BlackRock, one of Nvidia's financing partners, compared Nvidia's computing power assets to the "mortgage-backed securities market in the 1970s." The financing announcement immediately raised questions about more circular financing , but investors say the bigger issue is how exactly to value the assets that will be used as collateral for investments that are already straining the resources of capital markets . While auto loans and residential mortgages are long-established assets for the pools of debt known as asset-backed securities (ABS), instruments based on computing capacity are a lot trickier to underwrite, investors say. Little experience "The question is how to underwrite and value data center-backed loans. These metrics are hard to establish given the extraordinarily short term experience we have had with the asset class," Dan Alpert, a founding managing partner of Westwood Capital, told CNBC. Wells Fargo traders said in a Tuesday note that Nvidia's agreements with financial titans like KKR , Blackstone and Apollo amount to a form of insurance for investors who are "less familiar and comfortable with GPU collateralization," referring to graphics processing units. "One outstanding question is whether this all means that AI factory loans will eventually become repackaged into [a] collateralized loan market," like ABS, mortgage-backed securities or collateralized loan obligations, the Wells Fargo traders said. Nvidia shares dropped 3% Monday following the announcement, were little changed on Tuesday, and up about 2.7% in midday trading Monday. NVDA 5D mountain NVDA 5 day. Data centers burn through high-priced GPUs in only a few years, so the question of depreciation rates and the lifespan of data centers is top of mind for investors. There's also the issue of additional computing capacity coming online from international competitors, particularly China. "We know that these GPUs depreciate on only a five- or six-year schedule," Paul Meeks, head of technology research at Freedom Capital Markets, said. "Even within technology, it's an emerging market where we don't get the final scorecard until probably years from now." Investors are being reminded of other attempts to turn technology infrastructure booms into asset classes to attract investment. "Are data center-backed loans 'cheap' in ABS terms? Or are they the next fiber optic cable-backed loans - see Global Crossing ," Dan Alpert said, referring to a major telecommunications bankruptcy during the dot-com boom that sought to turn fiber-optic cables into investable assets. Famed investor Michael Burry said on Tuesday that the Nvidia credit agreements had "shades of Enron ." "This also has shades of Enron's effort to make wholesale power an investable class," Burry wrote on Substack. "Structuring unnatural credits to prolong momentum late in the bull phase is where the worry comes in."

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Nvidia calms its own credit market after Jensen Huang clarifies the $500bn financing plan

The chipmaker's credit-default swaps had spiked to a record on fears of circular financing. They eased once Jensen Huang recast the plan as other people's money, with Nvidia's own exposure capped. After weeks in which the cost of insuring its debt climbed to a record on worries about so-called circular financing, that cost eased once chief executive Jensen Huang spelled out how his $500bn plan to bankroll the AI build-out actually works. Nvidia's five-year credit-default swaps, in effect a wager on the odds it fails to pay its debts, jumped from around 40 basis points at the start of the month to a record near 82 in late July, the sharpest single-day move since the contract began trading. And the shares shed close to 5%, which briefly cost Nvidia its crown as the world's most valuable company. As we noted when its own credit market first flinched, traders had been unnerved by the sheer scale of Nvidia's entanglement with its customers. Nvidia has been taking equity stakes in, and offering debt guarantees to, the very companies that then spend the money on its chips, from a reported $250bn backstop for OpenAI's Ohio data centres to tens of billions in AI equity bets, all of which flatters demand for its own hardware. By Bloomberg's count Nvidia had announced some $540bn of such deals this year alone, and both the IMF and the Bank for International Settlements have flagged the pattern as a systemic risk. The $500bn platform, formalised this week with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR, mobilises third-party capital rather than Nvidia's own balance sheet, which lets AI labs, enterprises and cloud providers lease GPUs and build data centres without loading the assets onto their books. Because six finance giants are underwriting the plan, he stressed, each runs its own due diligence, and Nvidia caps its residual-value support at up to 25% on certain deals, which he argued is far lower than the typical compute-financing arrangement. The pitch rests on an audacious idea, namely that a graphics chip is now a financial asset in its own right. "This is really the first time that technology chips are an investable asset class," Jensen Huang said, describing them as revenue-generating, long-lived, fungible and flexible enough for lenders to underwrite much as they would a building. Goldman's David Solomon called it a new credit market backed by Nvidia compute, while BlackRock's Larry Fink reached all the way back to the birth of mortgage-backed securities in the 1970s for his comparison. That analogy is double-edged, though, because mortgage-backed securities also gave the world the crash of 2008. The short-seller Jim Chanos likened the structure to pre-crisis financial engineering, and Michael Burry, of Big Short fame, argues that fast-depreciating chips make the residual-value assumptions shakier than they look. The Bank of England, meanwhile, has warned about heavily leveraged AI companies and how little banks can actually see of their indirect exposure. Even so, the clarification did its job in the near term. By insisting that the $500bn is an aggregate, multi-year target rather than Nvidia revenue or a single fund, and that both the capital and most of the risk sit with outside investors, Jensen Huang gave the credit market a reason to unclench, and it duly did. For a company whose valuation now rides as much on confidence as on silicon, that was no small thing. The deeper worry, however, has not gone anywhere. The whole edifice still assumes that the infrastructure being financed will eventually earn enough to justify the trillions going into it, with Morgan Stanley alone pencilling in $3.5tn of hyperscaler spending through 2028. Jensen Huang has bought himself calmer markets by arguing that the risk is spread widely rather than concentrated in Santa Clara. Whether that is genuine prudence or simply a bigger, better-dressed version of the same loop is the question the swap traders will keep asking.

[16]

Axios

Backstopping the AI boom

Why it matters: Like it or hate it, investment in AI data centers is the engine powering the stock market and much of the growth in the economy. Catch up quick: On their own, the hyperscalers -- Alphabet, Amazon, Meta, Microsoft and Oracle -- are expected to spend roughly $800 billion this year and over $1 trillion in 2027. * But both hyperscalers and smaller players, like so-called neoclouds, are using more debt to finance the spending push. * And in recent months the bond market has periodically broken out with the yips over the size of some of these debts. The latest: That's where Nvidia's plan comes in. The chipmaker has lined up six Wall Street giants to create more than $500 billion in "dedicated pools of capital," presumably long-term institutional investors like insurers and pension funds, to finance projects for Nvidia's customers. * In some cases, Nvidia said it "may provide a residual-value support mechanism for up to 25% of an opportunity, assessed carefully on a project-by-project basis." * In other words, the chipmaker could provide some type of guarantee for some projects, potentially cutting interest rates for borrowers and helping to keep the boom going. Zoom out: Some analysts say that Nvidia putting itself on the hook for additional debt to finance still more investment in AI is a symptom of an investment boom tottering on the illogical. * "The bull case is there's infinite demand for AI, and this is going to go on forever," said Jay Goldberg, an equity analyst covering Nvidia for Seaport Global Securities. "Somebody at some point is going to say, 'Whoa. Wait a minute, what are we doing?'" * Analysts at UBS Global Wealth Management noted that Nvidia's strategy "raises further questions about AI circular financing, where suppliers help fund purchases of their own products and services." The other side: Others see a strategic imperative to the Nvidia move, which could help smaller data center entities counter the financial advantages enjoyed by deep-pocketed rivals like Amazon, Alphabet and Microsoft. * Those giants are also focused on using and even selling custom AI chips that could eventually pose a threat to Nvidia's GPUs. * Nvidia wants "customers to use their GPUs, not competitors'," said CJ Muse, an analyst covering Nvidia for Cantor Fitzgerald. "And I think they view this as another competitive moat." State of play: Stock market reaction to Nvidia's plan was mixed. * Nvidia competitors -- such as Broadcom -- sank alongside large hyperscalers like Alphabet and Amazon. (Nvidia itself was flat.) * Shares of financial players like KKR, Apollo and Blackstone rose. * So did prices of companies that make key equipment data centers need like memory chips and companies associated with construction. The bottom line: Few details are available about the plan, so we'll just have to wait and see how, or if, it will work.

[17]

The Guardian

Nvidia links with Wall Street firms for $500bn AI financing deal

Apollo, BlackRock, Goldman Sachs and KKR among those working with chipmaker to fund infrastructure Nvidia ⁠has partnered with six major Wall Street financial institutions to raise ⁠more than $500bn (£370bn) capital for artificial intelligence infrastructure. The Nvidia chief executive, Jensen Huang, said on X that the company has ⁠the option to backstop up to $125bn, or 25% of the potential deals. The move highlights how surging demand ⁠for AI computing capacity is drawing institutional investors, as governments, companies and startups race to build out datacentres. Big tech companies have signalled that spending on AI would not slow down, with combined outlays set to surpass $730bn this year. However, there has been concerns over the link between high valuations of tech companies and the need for vast investments to support their ambitions. Nvidia signed memorandums of understanding with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR for the financing platforms. The deal will create financing platforms, allowing third-party investors to treat AI "compute" as an asset class. Nvidia, which is worth $5.3tn, counts Google, Amazon, Microsoft and Facebook owner Meta among its customers. "These financing platforms will help customers access scarce compute at scale and build the AI factories that will power every industry and country in the age of AI," Huang said. "Compute has become a critical infrastructure asset," Joe Bae and Scott Nuttall, the co-chief executives of KKR, said in a joint statement. Nvidia said the arrangements would "create dedicated pools of ⁠capital at significant scale at attractive rates" for its customers. The company did not disclose the financial terms, investment commitments by individual firms or a timetable for deploying the planned $500bn.

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NVIDIA

NVIDIA Partners With Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to Establish AI Compute Infrastructure Financing Platforms to Mobilize Over $500 Billion of Third-Party Capital

These partnerships remain subject to execution of the final agreements. About NVIDIA NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing. About Apollo Apollo is a high-growth, global alternative asset manager. In our asset management business, we seek to provide our clients excess return at every point along the risk-reward spectrum from investment grade credit to private equity. For more than three decades, our investing expertise across our fully integrated platform has served the financial return needs of our clients and provided businesses with innovative capital solutions for growth. Through Athene, our retirement services business, we specialize in helping clients achieve financial security by providing a suite of retirement savings products and acting as a solutions provider to institutions. Our patient, creative, and knowledgeable approach to investing aligns our clients, businesses we invest in, our employees, and the communities we impact, to expand opportunity and achieve positive outcomes. As of June 30, 2026, Apollo had approximately $1.05 trillion of assets under management. To learn more, please visit www.apollo.com. About BlackRock BlackRock's purpose is to help more and more people experience financial well-being. As a fiduciary to investors and a leading provider of financial technology, we help millions of people build savings that serve them throughout their lives by making investing easier and more affordable. For additional information on BlackRock, please visit www.blackrock.com/corporate About Blackstone Blackstone is the world's largest alternative asset manager. Blackstone seeks to deliver compelling returns for institutional and individual investors by strengthening the companies in which the firm invests. Blackstone's over $1.3 trillion in assets under management include global investment strategies focused on real estate, private equity, credit, infrastructure, life sciences, growth equity, secondaries and hedge funds. Further information is available at www.blackstone.com. Follow @blackstone on LinkedIn, X (Twitter), and Instagram. About Brookfield Brookfield is a leading global investment firm with more than $1 trillion in assets under management. The firm owns and operates high-quality businesses and real assets that provide essential services and form the backbone of the global economy. Brookfield invests on behalf of institutions and individuals around the world across infrastructure, energy, private equity, real estate, and credit. With more than a century of operating experience and a global presence in over 30 countries, Brookfield deploys long-term capital to generate sustainable value for its clients and shareholders. Brookfield Corporation (NYSE: BN, TSX: BN) and Brookfield Asset Management (NYSE: BAM, TSX: BAM) are publicly traded in New York and Toronto. About Goldman Sachs Goldman Sachs is a leading global financial institution that delivers a broad range of financial services to a large and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world. About KKR KKR is a leading global investment firm that offers alternative asset management as well as capital markets and insurance solutions. KKR aims to generate attractive investment returns by following a patient and disciplined investment approach, employing world-class people, and supporting growth in its portfolio companies and communities. KKR sponsors investment funds that invest in private equity, credit and real assets and has strategic partners that manage hedge funds. KKR's insurance subsidiaries offer retirement, life and reinsurance products under the management of Global Atlantic Financial Group. References to KKR's investments may include the activities of its sponsored funds and insurance subsidiaries. For additional information about KKR & Co. Inc. (NYSE: KKR), please visit KKR's website at www.kkr.com. For additional information about Global Atlantic Financial Group, please visit Global Atlantic Financial Group's website at www.globalatlantic.com. NVIDIA Forward-Looking Statements Certain statements in this press release including, but not limited to, statements as to: NVIDIA bringing the world's leading long-term capital providers together to independently underwrite AI infrastructure; expectations with respect to demand for AI infrastructures; expectations with NVIDIA's strategic partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR, including the execution of final agreements and the terms and timing of the contemplated partnerships and the benefits of the financial platforms; expectations with respect to growth, performance, availability, demand, and benefits of NVIDIA's products, services and technologies, and related trends and drivers; expectations with respect to technology developments, and related trends and drivers; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the "safe harbor" created by those sections based on management's beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA's reliance on third parties to manufacture, assemble, package and test NVIDIA's products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA's existing products and technologies; market acceptance of NVIDIA's products or NVIDIA's partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA's products or technologies when integrated into systems; NVIDIA's ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company's website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances. Apollo Forward-Looking Statements This press release may contain forward-looking statements that are within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. These statements include, but are not limited to, discussions related to Apollo's expectations regarding the performance of its business, its liquidity and capital resources and other non-historical statements. These forward-looking statements are based on management's beliefs, as well as assumptions made by, and information currently available to, management. When used in this press release, the words "believe," "anticipate," "estimate," "expect," "intend" and similar expressions are intended to identify forward-looking statements. Although management believes that the expectations reflected in these forward-looking statements are reasonable, it can give no assurance that these expectations will prove to have been correct. These statements are subject to certain risks, uncertainties and assumptions, including risks relating to inflation, interest rate fluctuations and market conditions generally, international trade barriers, domestic or international political developments and other geopolitical events, including geopolitical tensions and hostilities, the impact of energy market dislocation, our ability to manage our growth, our ability to operate in highly competitive environments, the performance of the funds we manage, our ability to raise new funds, the variability of our revenues, earnings and cash flow, the accuracy of management's assumptions and estimates, our dependence on certain key personnel, our use of leverage to finance our businesses and investments by the funds we manage, Athene's ability to maintain or improve financial strength ratings, the impact of Athene's reinsurers failing to meet their assumed obligations, Athene's ability to manage its business in a highly regulated industry, changes in our regulatory environment and tax status, and litigation risks, among others. We believe these factors include but are not limited to those described under the section entitled "Risk Factors" in our annual report on Form 10-K filed with the Securities and Exchange Commission (the "SEC") on February 25, 2026, as such factors may be updated from time to time in our periodic filings with the SEC, which are accessible on the SEC's website at www.sec.gov. These factors should not be construed as exhaustive and should be read in conjunction with the other cautionary statements that are included in this press release and in our other filings with the SEC. We undertake no obligation to publicly update any forward-looking statements, whether as a result of new information, future developments or otherwise, except as required by applicable law. This press release does not constitute an offer of any Apollo fund. BlackRock Forward-Looking Statements This press release may contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act, including with respect to the potential strategic partnership referred to herein. Forward-looking statements are typically identified by words or phrases such as "trend," "potential," "opportunity," "pipeline," "believe," "comfortable," "expect," "anticipate," "current," "intention," "estimate," "position," "assume," "outlook," "continue," "remain," "maintain," "sustain," "seek," "achieve," and similar expressions, or future or conditional verbs such as "will," "would," "should," "could," "may" and similar expressions. BlackRock caution that forward-looking statements are subject to numerous assumptions, risks and uncertainties, which change over time and may contain information that is not purely historical in nature. Such information may include, among other things, projections and forecasts. There is no guarantee that any projections or forecasts made will come to pass. Forward-looking statements speak only as of the date they are made, and the parties assume no duty to and do not undertake to update forward-looking statements. Actual results could differ materially from those anticipated in forward-looking statements and future results could differ materially from historical performance. BlackRock has previously disclosed risk factors in its Securities and Exchange Commission ("SEC") reports. These risk factors and those identified elsewhere in this release, among others, could cause actual results to differ materially from forward-looking statements or historical performance. BlackRock's Annual Reports on Form 10-K, Quarterly Reports on Form 10-Q and subsequent filings with the SEC, accessible on the SEC's website at www.sec.gov and on BlackRock's website, discuss certain of these factors in more detail and identify additional factors that can affect forward-looking statements. The information contained on BlackRock's website is not a part of this press release, and therefore, is not incorporated herein by reference. Blackstone Forward-Looking Statements This release may contain forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which reflect Blackstone Inc.'s current views with respect to, among other things, its operations and the potential strategic partnership referred to herein. You can identify these forward-looking statements by the use of words such as "outlook," "indicator," "believes," "expects," "potential," "continues," "may," "will," "should," "seeks," "approximately," "predicts," "intends," "plans," "scheduled," "estimates," "anticipates," "opportunity," "leads," "forecast," "possible" or the negative version of these words or other comparable words. Such forward-looking statements are subject to various risks and uncertainties. Accordingly, there are or will be important factors that could cause actual outcomes or results to differ materially from those indicated in these statements. Blackstone Inc. believe these factors include but are not limited to those described under the section entitled "Risk Factors" in its Annual Report on Form 10-K for the year ended December 31, 2025, as such factors may be updated from time to time in its periodic filings with the United States Securities and Exchange Commission ("SEC"), which are accessible on the SEC's website at www.sec.gov. These factors should not be construed as exhaustive and should be read in conjunction with the other cautionary statements that are included in this release and in Blackstone Inc.'s periodic filings. The forward-looking statements speak only as of the date of this report, and Blackstone Inc. undertake no obligation to publicly update or review any forward-looking statement, whether as a result of new information, future developments or otherwise. Brookfield Forward-Looking Statements This press release contains "forward-looking statements" within the meaning of the U.S. Securities Act of 1933, the U.S. Securities Exchange Act of 1934, "safe harbor" provisions of the United States Private Securities Litigation Reform Act of 1995 and "forward-looking information" within the meaning of other relevant securities legislation, including applicable securities laws in Canada, which reflect our current views with respect to, among other things, our operations and financial performance (collectively, "forward-looking statements"). Forward-looking statements include statements that are predictive in nature, depend upon or refer to future results, events or conditions, and include, but are not limited to, statements which reflect management's current estimates, beliefs and assumptions and which are in turn based on our experience and perception of historical trends, current conditions and expected future developments, as well as other factors management believes are appropriate in the circumstances. The estimates, beliefs and assumptions of Brookfield are inherently subject to significant business, economic, competitive and other uncertainties and contingencies regarding future events and as such, are subject to change. Forward-looking statements are typically identified by words such as "expect", "anticipate", "believe", "foresee", "could", "estimate", "goal", "intend", "plan", "seek", "strive", "will", "may" and "should" and similar expressions. In particular, the forward-looking statements contained in this press release include statements referring to the impact of the partnership between Brookfield and NVIDIA. Although Brookfield believes that such forward-looking statements are based upon reasonable estimates, beliefs and assumptions, certain factors, risks and uncertainties, which are described from time to time in our documents filed with the securities regulators in the United States and Canada, not presently known to Brookfield or that that Brookfield currently believes are not material, could cause actual results or events to differ materially from those contemplated or implied by forward-looking statements. Readers are urged to consider these risks, as well as other uncertainties, factors and assumptions carefully in evaluating the forward-looking statements and are cautioned not to place undue reliance on such forward-looking statements, which are based only on information available to Brookfield as of the date of this press release. Except as required by law, Brookfield undertakes no obligation to publicly update or revise any forward-looking statements, whether written or oral, that may be as a result of new information, future events or otherwise. Goldman Sachs Forward-Looking Statements This press release includes "forward-looking statements" within the meaning of the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995. Forward-looking statements are not historical facts or statements of current conditions, but instead represent only Goldman Sachs' beliefs regarding future events, many of which, by their nature, are inherently uncertain and outside Goldman Sachs' control. It is possible that Goldman Sachs' actual results may differ, possibly materially, from the anticipated results indicated in these forward-looking statements. For a discussion of some of the risks and important factors that could affect Goldman Sachs's future results, see "Risk Factors" in Part I, Item 1A of Goldman Sachs' Annual Report on Form 10-K for the year ended December 31, 2025. Forward-looking statements include statements about the timing, profitability, benefits and other prospective aspects of business initiatives (including via partnerships) and the achievability of targets and goals, and statements about the opportunities presented by artificial intelligence (including potential AI infrastructure buildout and the need for capital to fund that buildout). Statements about the timing, profitability, benefits and other prospective aspects of business initiatives (including via partnerships and with respect to the opportunities presented by AI, such as the need for and the ability to create compute financing platforms at global scale) are based on Goldman Sachs' current expectations regarding its ability to effectively implement those initiatives and may change, possibly materially, from what is currently expected. See "Forward-Looking Statements" in Part I, Item 2 "Management's Discussion and Analysis of Financial Condition and Results of Operations" in Goldman Sachs' Quarterly Report on Form 10-Q for the quarter ended Jue 30, 2026 for further information about forward-looking statements. KKR Forward-Looking Statements This press release contains certain forward-looking statements pertaining to KKR, including with respect to the investment funds, and vehicles and accounts managed by KKR and Global Atlantic Financial Group. Forward-looking statements relate to expectations, estimates, beliefs, projections, future plans and strategies, anticipated events or trends and similar expressions concerning matters that are not historical facts, including with respect to KKR's involvement in the proposed transactions described herein and the transactions' effect on our business. You can identify these forward-looking statements by the use of words such as "opportunity," "outlook," "believe," "think," "expect," "feel," "potential," "continue," "may," "should," "seek," "approximately," "predict," "intend," "will," "plan," "estimate," "anticipate," "visibility," "positioned," "path to," "conviction," "enables," the negative version of these words, other comparable words or other statements that do not relate strictly to historical or factual matters. These forward-looking statements are based on KKR's beliefs, assumptions and expectations, but these beliefs, assumptions and expectations can change as a result of many possible events or factors, not all of which are known to KKR or within its control. Due to various risks and uncertainties, actual events or results may differ materially from those reflected or contemplated in such forward-looking statements. Past performance is no guarantee of future results. All forward-looking statements speak only as of the date of this press release. KKR does not undertake any obligation to update any forward-looking statements to reflect circumstances or events that occur after the date of this press release except as required by law. Information about factors affecting KKR, including a description of risks that should be considered when making a decision to purchase or sell any securities of KKR, can be found in KKR & Co. Inc.'s Annual Report on Form 10-K for the fiscal year ended December 31, 2025, filed with the SEC on February 27, 2026, and its other filings with the SEC, which are available at www.sec.gov.

[19]

Wall Street giants partner with Nvidia on $500bn AI financing deal

The world's largest financial groups are working with Nvidia to assemble a $500bn funding package for AI infrastructure development, in one of Wall Street's most ambitious lending efforts to date. A consortium of groups including Apollo Global, Blackstone, BlackRock's Global Infrastructure Partners unit, Brookfield Asset Management, Goldman Sachs and KKR is entering a partnership with Nvidia to invest in the AI build-out, five people briefed on the talks told the FT. The deal could be announced as soon as Monday, the people said. The partnership underscores Nvidia's growing efforts to raise capital for itself and its clients to continue assembling the chips, power production and data centres at the heart of the AI boom. It also shows how Nvidia is building relationships with the giants of the private capital industry, which are collectively preparing to invest trillions of dollars of their insurance, retail and institutional investor assets into AI infrastructure. In recent years, private capital groups such as Apollo and Blackstone have structured AI infrastructure deals to assist companies like Anthropic finance their heavy spending on chips and data centres. Apollo, Blackstone, Brookfield, BlackRock, Goldman and KKR did not immediately respond to requests for comment. Neither did Nvidia respond to requests for comment.

[20]

Quartz

Goldman Sachs courts investors for Nvidia $500B AI financing deal

U.S. insurers, money managers, and banks are expected to form the core investor base for the deal, which Nvidia announced earlier this week Goldman Sachs $GS has been approaching a range of potential participants -- among them banks, insurers, asset managers, and private credit firms -- about joining Nvidia $NVDA's $500 billion AI infrastructure financing initiative, according to Reuters, citing unnamed sources familiar with the matter. The Wall Street bank secured a central role as the sole lender in the deal alongside alternative asset management firms Blackstone and Apollo. Through its asset management arm, Goldman can offer junior capital and private credit financing, and it can also help funnel debt into private credit funds and public debt markets. Goldman Sachs Chairman and Chief Executive Officer David Solomon said on CNBC that Nvidia founder and CEO Jensen Huang brought the idea to the bank. "Jensen came, approached us with the idea, and we said we'd love to talk to you about it," Solomon told CNBC. The bank's role reflects years of ties with Nvidia. Goldman Sachs has advised the chipmaker on several transactions and on technology financing deals in which Nvidia was an investor, according to Reuters, citing Dealogic. Goldman was Nvidia's sole financial adviser on its $6.9 billion purchase of Mellanox Technologies in 2019 and also counted among the lead underwriters when Nvidia issued bonds in June. Nvidia announced partnerships earlier this week with six major financial institutions -- Apollo, BlackRock $BLK, Blackstone, Brookfield, Goldman Sachs, and KKR -- to establish compute financing platforms aimed at mobilizing more than $500 billion in third-party capital for AI infrastructure buildout over time. The arrangements were formalized through memorandums of understanding and remain subject to final agreements, the company said. Huang said the partnerships are intended to support customers including frontier AI labs, enterprises, and cloud providers. The structure of the financing differs from earlier AI infrastructure deals. Earlier deals relied on vendor guarantees -- for instance, Broadcom $AVGO backed roughly $30 billion of senior debt tied to Anthropic's AI chip financing with a residual-value guarantee. Under the Nvidia deal, Huang said the company has the option to backstop up to $125 billion, or 25% of the potential deals. According to Reuters, the aim is to establish a functioning asset-backed market around AI compute capacity, where the resulting debt instruments could be bought and sold similarly to conventional securities -- potentially reducing borrowing costs and opening the door to a wider range of investors. Bank of America $BAC analyst Vivek Arya wrote in a note that the arrangement "appears to be a pivot away from vendor-financing," adding that "the burden sits with the consortium, not (Nvidia's) balance sheet." At roughly $5.2 trillion in market capitalization, Nvidia currently ranks as the most valuable company trading on U.S. public markets.

[21]

Fortune

Nvidia found a new way to keep the AI boom funded: your retirement money | Fortune

Nvidia has been arguably the No. 1 profiteer of the AI boom, selling the picks and the shovels of the trade. But now it wants Wall Street to figure out how to keep paying for them. On Monday, Nvidia announced partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR to create financing platforms intended to mobilize more than $500 billion for AI infrastructure. The money will largely come from "third-party investors," allowing Nvidia customers to finance chips and data centers while keeping Nvidia's own risk limited and off the balance sheet. Details of the arrangements, like the extent of each deal, are still unknown. But analysts have been watching for a deal like this -- that treats AI compute into an infrastructure asset, like a toll road or power plant -- that produces cash flows and therefore can support debt. As of now, many have feared the chips instead look like a rapidly depreciating, and thus depleting, pile of graphics processors that will need more and more capital to finance. "We have moved from an era in which companies bought chips and built data centers project by project to one in which AI factories can be financed as productive infrastructure," Nvidia CEO Jensen Huang wrote Tuesday. In Huang's formulation, the premise is simple: "In AI, compute is revenue." Underneath that transformation is a second one: who is actually paying for the AI boom. A year ago, most of Big Tech could claim it was financing AI from its enormous cash flows, accrued from decades of executing software-level thin margins and massive profits. But now debt is taking over. Goldman Sachs estimates AI-related financing now accounts for nearly one-quarter of all gross U.S. investment-grade issuance, while AI investment itself is approaching $600 billion this year. So Nvidia's getting ahead of the whole debacle to find the next pool of money. The chain is straightforward. An independent financing vehicle can raise money to buy Nvidia GPUs and data-center infrastructure. An AI company then leases that compute or commits to using it, creating a stream of payments against whichthe vehicle can borrow. Apollo, KKR, and their peers can structure or manage that debt and place it with the enormous pools of institutional money -- mostly insurance and retirement capital -- that they oversee. Bloomberg columnist Matt Levine distilled the long-term vision into three steps: Put more private investments into ordinary people's retirement accounts, raise "a gazillion dollars" of private-credit and infrastructure funds, and use that money to build the data centers that AI will rent. There is a reason those pools of money are attractive. Data centers are expensive, long-lived, and long-standing projects that require financing over many years. Insurers and pension funds, conveniently, have long-dated obligations -- annuities that may pay for decades, or retirement benefits owed decades into the future -- and therefore look for long-duration assets whose cash flows can be matched against those liabilities. Private-credit and infrastructure managers act as the middlemen, turning projects like data centers into debt those institutions can hold. Nvidia, however, has said it's putting something of its own behind the bet: Huang said the company may provide residual-value support of up to 25% for some projects -- effectively promising some protection against the possibility that the chips backing a financing are worth much less in the future than lenders expected. Ben Thompson, who writes the technology strategy publication Stratechery, calls that "in a certain sense, a price cut": Nvidia is using its own profits to reduce customers' cost of capital and make Nvidia-based data centers easier to finance. And that is where the deal gets more interesting. The AI boom started with some of the richest corporations in history spending their own cash. Then came bonds. Now Nvidia is helping Wall Street turn compute itself into an investable asset capable of drawing on insurance floats, pension funds, and other long-duration savings. Wall Street sees it as a positive sign. Morgan Stanley's Joseph Moore said the arrangement alleviates concerns about circular financing because third-party investors would provide most of the capital, while Nvidia would participate only to a limited extent. Bank of America's Vivek Arya mostly agreed and added Nvidia's chips are unusually financeable because GPUs can be moved among operators and CUDA software can extend their own useful lives. But Thompson's concern is those pools of cash institutions have are fundamentally different from venture capital or tech stocks: They are designed, at least in part, to seek safety. "It's one thing to spend all of your free cash flow; it's another thing to tap the debt markets," he writes. "And, beyond that, it's a completely new nerve-racking thing to bring safety-seeking assets to bear."

[22]

CNBC Daily Open: Big Tech wants to tap Wall Street's big wallets

Nvidia also launched its first open-source model, named Nemotron 3.5 Lightning. This is the first model since CEO Jensen Huang joined most of his tech peers in urging the U.S. government to support open models. In the AI gold rush, Nvidia already sells the picks and shovels. Now it wants Wall Street to help finance the mine. Nvidia had announced a tie-up with six powerhouses on Wall Street, who said they're willing to raise $500 billion (and potentially more) for the construction and build-out of new AI factories, as chipmakers and hyperscalers race to meet seemingly endless demand. So there's a fundamental shift: AI infrastructure has become a new asset class. However, this path is not without risks. Key to CEO Jensen Huang's plan is one crucial assumption: that Nvidia's graphics processing units will hold their value over time, behaving more like traditional hard assets than fast-depreciating consumer electronics. Ben Emons, founder of FedWatch Advisors, told CNBC the single biggest threat to Nvidia's financing model comes from China, which is rapidly ramping up domestic compute capacity and could choose to flood the market with low-cost silicon in a price war. If Chinese production pushes hardware prices into a freefall, the collateral backing hundreds of billions in private loans could erode far faster than the terms of the debt itself, leaving investors exposed to losses, according to Emons. Nvidia is finding a way to continue growing, though. The company announced its first open source AI model since Huang defended open-source models in AI in July. The model, known as Nemotron 3.5 Lightning, is "lightweight" and can run on a single graphics processing unit on a PC, according to Nvidia. For Nvidia, open-source AI is a boon for chip sales, because the models still need to run on GPUs, and the lower prices can serve to boost usage over proprietary models from the likes of OpenAI and Anthropic.

[23]

Euronews

What Nvidia's $500 billion Wall Street deal signals about the AI boom

Nvidia and six of the world's largest investment firms announced plans last week to channel more than $500 billion (€433bn) into AI infrastructure, an arrangement designed to let tech companies build data centres without loading the cost onto their own balance sheets. Nvidia has recruited Wall Street to bankroll its own customers. The US chipmaker said last week it had signed memorandums of understanding with Wall Street's largest asset managers, including Apollo Global Management, Blackstone, BlackRock, Brookfield Asset Management, Goldman Sachs and KKR to raise upwards of half a trillion dollars for AI companies to borrow against, money that will buy its chips and build the servers that run them. The six firms will set up what Nvidia calls "compute financing platforms," drawing on institutional money, insurance funds and private credit. Borrowers can use the proceeds for the chips as well as servers, networking equipment, buildings and power supply. Nvidia has the option to guarantee up to a quarter of any given deal, which lowers the interest rate its customers pay while leaving most of the credit risk with the lenders. CEO Jensen Huang said he approached only these six companies and none refused. Keeping that spending off their own books is precisely the point, and the fact that such a structure is needed at all tells investors a great deal about where the constraints in the AI boom now lie. The financial engineering rests on a single reclassification. Graphics processing units (GPUs) have always been treated as equipment that loses value quickly, superseded whenever a faster generation arrives. Nvidia is effectively asking lenders to treat them instead as long-lived infrastructure, closer to a toll road or a power plant, that can be borrowed against for years. "These are revenue-generating assets now," Huang said, describing them as productive, long-lived and transferable between customers. Why the money had to come from somewhere else The timing reflects a squeeze that has been building all year. Microsoft, Amazon, Alphabet, Meta and other hyperscalers whose cloud platforms host most of the world's AI workloads have together guided roughly $720 billion (€624bn) to $745 billion (€646bn) of capital spending in 2026, an increase of about 77% on last year. What analysts expect the hyperscalers to spend in 2027 alone has more than doubled in the space of a year, from a consensus of $480 billion (€416bn) in August 2025 to $1.08 trillion (€943bn) this month, a rise of about 127%, according to Bank of America. The pattern has repeated at every stage. Analysts who already considered last year's investment unsustainable then watched the hyperscalers guide higher at the start of 2026, revise those figures upward again through the year, and pencil in larger sums still for next year and 2028. Moody's has warned that spending on this scale is eating into free cash flow and pushing tech groups into heavier borrowing. Alphabet recorded negative free cash flow of $5.9 billion (€5.1bn) in a quarter when it spent $44.9 billion (€38.9bn) on projects. That is the pressure the structure of Nvidia's Wall Street deal relieves. Debt raised through these "compute financing platforms" sits with the financing vehicles rather than on a hyperscaler's own accounts and also has Nvidia's backing, which protects credit ratings and leaves room for conventional borrowing elsewhere. For smaller operators the effect is larger still as companies such as CoreWeave and Nebius, which lack investment-grade ratings and pay dearly for credit, gain access to capital on terms previously reserved for the giants. What the market actually read into it The reaction was more ambivalent than the headline number suggests, and came weeks after a July selloff driven by doubts over whether AI spending will pay for itself. Essentially, equity investors saw a bottleneck being cleared while credit investors saw something else: the cost of insuring Nvidia's own debt against default rose after the news and has roughly doubled since late May. Their doubt concentrates on the reclassification previously mentioned. "Chips depreciate fast and lose value the moment a newer generation arrives," warned Nigel Green of financial advisory firm deVere Group, noting that lending against them only works if the collateral holds its value. Critics also point out that Nvidia is helping finance purchases of its own products, deepening the circularity that already worries the sector. Goldman Sachs CEO David Solomon called it "a pivotal moment of a historic AI investment cycle." Whether it proves pivotal in the direction Solomon means depends on a question nobody can yet answer: what will the value of a current GPU be in five years?

[24]

PC Gamer

Nvidia reckons new $500 billion investment should allay fears AI companies are just funded by the same pot of cash moving around in one big circle. Reassured yet?

This week, Nvidia announced it will be receiving "over $500 billion of third-party capital" from banks and investment companies. And now, in a blog post explaining how 'AI factory' compute is "becoming an investable asset class", Nvidia has answered the question, "Is this circular financing?" The company says: "This initiative is designed to address that concern. We are bringing independent, long-term institutional capital into the AI infrastructure market. "The demand is real: it comes from frontier AI labs, AI-native startups, enterprises, cloud providers and countries building AI services. The capital providers independently underwrite each project -- including the customer, demand, utilization, cash flow and residual value. NVIDIA provides the platform; the investors make independent financing decisions. "This is the beginning of an open capital market for AI infrastructure." BlackRock CEO Larry Fink reportedly said, "We need to raise this money as fast as possible... This is going to be creating a huge amount of jobs." Let me get the positivity out of the way with first: Yes, it's good that Nvidia is addressing the concern that the AI market finances itself circularly, by having AI companies fund other AI companies and vice versa with the same pot of money going around and around. Alright, that's the positive sorted -- on to the negative. First, of course Nvidia can say so now, after months of circular financing has already occurred. Now that it's opening up to widescale financing beyond the AI industry itself, it must be a lot easier for it to talk about. But where was this recognition six months ago? Second, in the world of bigwig investment, it's hard to ever fully distance yourself from circularity. BlackRock, for instance, alongside Microsoft and Nvidia, has previously bought almost 80 AI facilities in a $40 billion deal. So I doubt funds already wrapped up in AI investments will balk too much at getting Nvidia a bunch of money for more AI building, as some of that will presumably trickle back in their direction, too. Third, it's kind of unsurprising that big hedge funds like BlackRock would want to keep the AI hype going given the economy itself is arguably now somewhat dependent on it. Most economic analysis seems to agree that the AI industry is indeed a (giant) bubble, and that when it pops it could spell very bad news for the economy in general. To wit, New York Times financial columnist Andrew Ross Sorkin says of this $500 billion partnership: "Mark Monday on your calendar. It's a date we may look back on years from now as either the inflection point in the AI boom -- or the moment it got so leveraged that a crisis began to form." Finally, while it might be good that Nvidia has acknowledged concerns about the AI industry's financial circularity, it's far from clear that a $500 billion investment from Wall Street adds more solidity to the market. We have to remember that these investments are made on the promise of AI actually returning on investment, something we've seen little evidence of so far. To my eyes, it looks a lot like tech CEOs gritting their teeth and crossing their fingers that the bubble doesn't pop before AI makes some miraculous, superintelligent breakthrough that grants an exponential ROI. And if that's the case, this $500 billion investment might mean more of an "open capital market" for AI, but it could still just be buying time before the inevitable *pop*.

[25]

NBC

Nvidia partners with Wall Street giants to raise $500 billion for AI buildout

Nvidia said on Monday it has partnered with six major financial institutions to launch compute financing platforms aimed at raising over $500 billion in third-party capital for AI infrastructure. The move highlights how surging demand for AI computing capacity is drawing institutional investors, as governments, companies and startups race to build out data centers to support AI workloads. Big Tech companies have signaled that spending on AI would not slow down, with combined outlays set to surpass $730 billion this year. Nvidia signed memorandums of understanding with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR for the financing platforms. The initiative is intended to broaden access to Nvidia-based infrastructure among frontier AI developers, enterprises, governments and cloud providers, while creating longer-duration, usage-linked investment opportunities for large asset managers and private capital firms. "These financing platforms will help customers access scarce compute at scale and build the AI factories that will power every industry and country in the age of AI," Nvidia CEO Jensen Huang said. Nvidia said the arrangements would "create dedicated pools of capital at significant scale at attractive rates" for its customers. The company did not disclose the financial terms, investment commitments by individual firms or a timetable for deploying the planned $500 billion. The Financial Times had reported the development first on Monday, later confirmed by Reuters.

[26]

Six finance giants back Nvidia's $500bn plan to fund the AI buildout

Six of finance's biggest names are building 'compute financing platforms' around Nvidia hardware, a new stage in the debt-fuelled AI buildout. Nvidia has recruited six of the largest names in finance to help turn its chips into something a bank can lend against. The company announced partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to build what it calls "compute financing platforms", structures designed to mobilise over $500bn of third-party capital for AI infrastructure. The idea is to create dedicated pools of capital at scale, and at attractive rates, for Nvidia's customers, meaning the frontier AI labs, enterprises and cloud operators buying its hardware. In effect, Nvidia is helping to build a financing pipeline around its own product, which is why the move reads as a more formal turn in the circular financing binding the AI economy together. At the centre of the pitch is a reframing of what a GPU is. Nvidia is presenting its compute as "an investable asset", one it says carries the lowest token cost, the highest revenue, the longest operational life and a rich CUDA-based software ecosystem. The argument is that a graphics processor is no longer just kit that depreciates in a rack, but collateral with a predictable return, so lenders can treat it much as they would a toll road or a power plant. Chief executive Jensen Huang made the case in similar terms. "Nvidia compute is uniquely suited for this role," he said. "It is broadly adopted, flexible across models and workloads, fungible and transferable." Goldman Sachs, for its part, described its role as "creating a market for credit backed by Nvidia compute", language that makes the ambition plain: a tradable asset class with the chips as the underlying security. The partners each bring a different slice of capital. Apollo offers a flexible long-term base, BlackRock connects long-term money to essential infrastructure, KKR combines long-duration capital with infrastructure expertise, and Brookfield, whose reach already extends to a $100bn data campus, would scale the "AI factories" that house the hardware. No individual project names or amounts were disclosed, and the $500bn figure is an aggregate potential over time rather than a committed sum. That caveat matters, because so far only memorandums of understanding have been signed. Final agreements are still pending, which means the headline number describes an intention rather than money that has actually changed hands, and MOUs of this kind can quietly shrink or stall in the long gap between announcement and closing. The structure is striking for another reason. It formalises a pattern that has already made investors uneasy, since Nvidia sits on multiple sides of these arrangements: it sells the chips, vouches for their resale value, and now helps assemble the capital to buy them. It is worth remembering that Nvidia's own $750bn of AI deals rattled its credit market earlier, a sign that even the company's backers are alert to how tightly these commitments are wound. The deeper worry is leverage. Most of the half a trillion dollars in view would be debt, and layering it onto an infrastructure boom is exactly the dynamic regulators have flagged. Indeed, the BIS has warned an AI bust could hit credit markets as hard as 2008, precisely because so much of the buildout now rests on borrowed money and interlocking promises. And "compute as collateral" only holds while demand does. If AI revenue softens, the asset underpinning all this credit could reprice quickly, leaving leveraged buyers exposed and lenders holding chips worth less than the loans against them. Huang calls the hardware fungible and transferable, though a glut would test how fungible it really is. For now, Nvidia has done something subtle but consequential. It has enlisted Wall Street to underwrite the demand for its own products, and if the agreements firm up, the AI buildout gains a vast new source of fuel, even as the debt beneath it grows harder to see through.

[27]

Axios

Nvidia wants the AI revolution to be securitized

Zoom in: Much of that money is likely to come via GPU securitizations -- spreading out the exposure across insurance companies, pension systems, sovereign wealth funds, and more. The big picture: Wall Street is betting America's economy on unwavering compute demand. * Not just this deal, but also a spate of similar financing arrangements that presume no AI lab will build a vastly more efficient mousetrap. * Or that data center growth won't be significantly restricted by political pressures. Or quantum computing advancements. Or something else we can't yet see, such as an unexpected increase in rare metals production that could flip chip scarcity into surplus. * It's not blind faith. There are some solid economics here, including how older NVIDIA chips have demonstrated collateral value. But it's also not a sure thing -- exuberance can be both rational and risky. Deal details: The participating firms are Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR. * Each firm will evaluate opportunities on a case-by-case basis, and submit allocation requests to Nvidia (which "may provide a residual-value support mechanism for up to 25%"). * Expect many of them to create internal allocation mechanisms, spreading out the opportunities within their own business units. Some firms will invest off balance sheet, some will leverage their insurance arms, some will invest out of credit funds, etc. * Waldemar Szlezak, KKR's head of digital infrastructure, tells me his firm has been speaking to Nvidia for over a year, but that "this iteration really picked up steam over the last month or so." Back in time: There are lots of positive historical comparisons here, in terms of massive industrial buildouts backed by credit. Railroad systems. Airplane fleets. Automotive (in fact, this whole thing feels a bit like new-school GMAC). * That said, securitization trends can begin with good intentions and then cause calamity. * Particularly when there is structural circularity, which has become a hallmark of the AI boom. Worthy of your time: Nvidia CEO Jensen Huang on Tuesday published a LinkedIn post, making his case for the investability of AI compute. The bottom line: The revolution will be securitized.

[28]

SiliconANGLE

Did Nvidia's Jensen Huang just make the AI buildout too big to fail?

Nvidia Corp. is no longer just selling technology. It is helping create a financial asset class around artificial intelligence compute. In our last Breaking Analysis, we argued that AI can be technologically transformative and still produce a capital bubble. Our thesis was simply that the bubble pops if deployable supply grows faster than monetizable demand - and financing stops bridging the gap. Nvidia Chief Executive Jensen Huang has just attacked that weak link directly. Nvidia announced partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish financing platforms designed to mobilize more than $500 billion for AI infrastructure. This is not a funded $500 billion pool today. The final agreements still have to be completed. But the goal is quite clear. Specifically, Nvidia is trying to turn AI compute into collateral - and the AI factory into a repeatable, financeable infrastructure asset. That makes AI much more than a chip story. If the memorandum of agreement turns into solid agreements, it intertwines AI with credit, leverage, customer contracts, productive monetization, cash flow and the residual value of aging silicon. And if this market scales as we believe it will, the same assumptions about AI demand will connect semiconductor suppliers, neoclouds, data-center developers, utilities, private-credit funds, infrastructure investors and governments. A failure in one part of that system may no longer stay contained. Did Jensen just make the AI buildout too big to fail? Not yet. But he may be making it too interconnected to fail quietly. Welcome to this Breaking Analysis No. 322. In this episode, we will briefly explain how compute-backed credit works, why Nvidia's residual-value support is an important tell sign, what CoreWeave Inc. and Nebius Group NV earnings prints reveal about the current demand and economics picture; and whether this new capital market reduces the AI bubble risk or simply moves it downstream. Because independent capital can extend the buildout. But independent capital is not independent demand. The big news Let's begin with exactly what Nvidia did and didn't announce. Nvidia signed memorandums of understanding with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish independent financing platforms designed to mobilize more than $500 billion of third-party capital over time. That is obviously a major announcement. But it is not $500 billion of Nvidia revenue. It is not one funded pool. It is not an immediate commitment to specific customers or projects. And the final agreements have not yet been completed. So the headline number is exciting but the mechanics are more important to understand. Specifically, today, many AI factories are financed one company and one project at a time. Builders use some combination of corporate debt, customer prepayments, asset-backed loans, equity and vendor financing. Nvidia is essentially trying to make that process repeatable. The idea is to bring long-duration institutional capital into the market and underwrite AI factories against customer commitments, utilization, cash flow and the expected residual value of the installed compute. The most notable phrase in the announcement came from Goldman Sachs: "Create a market for credit backed by Nvidia compute." That is the transition we need to better understand. Nvidia wants its systems to be treated as more than technology equipment. It wants the compute to serve as collateral - and the AI factory to become an investable infrastructure asset class. If this works, capital can move away from individual company balance sheets and into infrastructure funds, private credit, insurance capital and other institutional pools. That could potentially reduce the cost of capital and broaden access to AI infrastructure. But it does not eliminate risk. It does change who holds the risk, how the risk is financed and how widely the exposure is distributed. Don't think of this as a program designed to sell more GPUs. It is that. But it's much more. Nvidia is attempting to build a capital market around its architecture by making AI infrastructure an investable asset. And this is the key to understanding this prospective deal: The AI chip cycle is becoming a credit cycle. The next question is how an AI factory actually becomes a financeable asset - and what investors are being asked to underwrite. Big money sharks enter the silicon game To understand what Nvidia is building, let's put our banker hats on and think like a finance lender. This proposed structure is similar to the financing used for power plants, aircraft fleets or large infrastructure projects. Institutional investors provide debt and equity to a dedicated financing vehicle - often called a special-purpose vehicle, or SPV. That SPV uses the capital to buy or lease the Nvidia systems, secure the site and power, and build the AI factory. But the physical infrastructure is only one part of the asset. The complete asset includes the Nvidia platform, the customer contract, the site, the power connection, the expected monetization profile and the residual value of the equipment after the first contract ends. The customer agreement - or what's called an "offtake contract" is super important. The lender wants to know four things: 1) Who is obligated to pay? 2) How long is the commitment? 3) Is the contract take-or-pay - meaning the buyer either takes a minimum amount of product or pays for the shortfall if they don't take delivery? And 4) Can the customer cancel, delay acceptance or renegotiate the price? Once the factory is operating, usage revenue has to cover power, cooling, maintenance, operating costs, debt service and the return required by the equity investors. And then there is the residual-value question. When the first customer contract ends, can the cluster be leased to another customer? In other words, does it have enough value to be redeployed to inference or a different workload? And what is that value? This is why Nvidia emphasizes that its systems are fungible, transferable and improved over time through CUDA. Those salient characteristics are intended to support a longer economic life and give lenders confidence that the equipment still has value if the original customer leaves. So from an underwriters perspective - they don't care about AI hype. They only care if this specific AI factory generates enough predictable cash flow - and retains enough recovery value - to support the capital structure? This is how compute becomes collateral. Capital funds the factory. Customers rent the output... and lenders underwrite utilization, cash flow and recovery value. And this framework also tells us exactly where the risk moves if demand, pricing or residual value fails to live up to expectations This all may sound like infrastructure finance - like leasing IBM mainframe computers in the 80s and 90s. But once these loans and leases begin to be pooled and distributed, the model starts to resemble something more like asset-backed credit - and eventually, perhaps, securitization. This is not MBS There's lots of talk in the media about how this is like mortgage backed securities. We need to be careful with the MBS analogy. It is useful - but it can get ahead of the actual facts. What Nvidia announced is not securitization today. We are not seeing pools of AI-factory loans being divided into tranches, rated and sold into a broad secondary market. Nvidia has announced financing platforms and dedicated pools of institutional capital. The final agreements are still pending. This is not MBS, yet anyway. What we are seeing is a steady movement. The first stage is project finance. A lender finances a specific AI factory against a customer contract, a site, available power and forecasted cash flow. The lender underwrites that individual project. The second stage is equipment leasing and secured debt. Here, the compute systems and the customer contracts help support the borrowing. We have clear evidence that this is already happening. CoreWeave has financed high-performance-computing infrastructure through syndicated term loans, including financing supported by shorter-duration customer contracts. Nebius completed a $775 million asset-backed facility secured by deployed GPUs and contracted cash flows from an investment-grade customer. The third stage is portfolio finance. Instead of financing a one-off AI factory, investors pool multiple projects across customers, operators and geographies. That diversification - and the operating data created over time - can make the asset class easier to underwrite. That appears to be the direction of Nvidia's institutional platforms. Then, potentially, comes securitization. If transaction volume grows and the assets develop a reliable and proven performance history, loans or leases could eventually be pooled, divided into senior and junior risk tranches and distributed to a broader investor base. But that is a possible future state - not what was announced. The mortgage-backed-securities analogy helps us understand pooling, tranching and distribution. It also gives us the warning: financial diversification can conceal economic concentration if every loan depends on the same demand assumptions and collateral values. Frequent-flyer securitizations is an example that shows how unusual future cash flows can support borrowing when investors believe those cash flows are durable. Aircraft leasing is probably the closest operating analogy. Here you have standardized assets, multiple potential customers, recurring lease revenue and strong residual value after the first contract ends. Even that comparison however has limits. An aircraft can be flown to another customer. A complete AI factory remains tied to power, cooling, networking, software and a physical site. So the key question is not whether Wall Street can package this risk - Wall Street can package almost anything. The more important question is whether packaging the financing actually diversifies the underlying economics. Pooling projects does not diversify the risk if every project depends on the same customers, the same Nvidia architecture and the same utilization assumptions. And that brings us to the most revealing part of the announcement: Nvidia's willingness to provide residual-value support. What does Jensen's 'backstop' really mean? Let's look at Nvidia's willingness to support this arrangement and what it actually tells us. CEO Jensen Huang announced that Nvidia has the option to backstop up to $125 billion - or 25% - of this massive $500 billion-plus AI infrastructure financing initiative Key issue: Does the backstop bring confidence - or indicate that lenders still require credit de-risking? The answer is both. Many media reports interpreted the term "backstop" in a negative light. But what they fail to convey is that the backstop is at Nvidia's option. In other words, if the financier feels the deal is too risky, Nvidia has the option of absorbing up to 25% of that risk. But if Nvidia doesn't feel the project is viable it can choose not to provide the backstop and the deal blows up. This underscores the most important stress test in the entire financing model. As we explained earlier, Nvidia's premise is that its compute is not disposable technology equipment - rather it's an investable asset. But lenders ask a different set of questions. If the original customer leaves, can another customer take the capacity quickly - without costly migration, reconfiguration, export-control issues or data-gravity friction? Can CUDA improvements offset the performance and power-efficiency advantages of newer generations? Are the potential offtakers truly diverse - or are many projects ultimately dependent on the same frontier labs, hyperscalers and sovereign buyers? And most importantly, does the capacity generate enough cash after power, cooling, site expense, maintenance, operations, debt service and refinancing costs? Some early evidence supports part of Jensen's argument. CoreWeave says a typical five-year contract can repay the asset-level debt used to build the cluster. It also recently contracted A100 capacity through 2029 at what it described as an attractive price - even though the A100 architecture was introduced in 2020. Coreweave says its prior-generation Ampere and Hopper fleets also remain largely sold out. That is significant evidence that older Nvidia infrastructure can retain commercial value. But it is not yet a full-cycle stress test. Those residual values are being seen during a period when supply remains constrained and rental pricing is unusually strong. The real test comes after a capacity-surplus cycle - when newer systems are broadly available, rental prices normalize and customers have more alternatives. That is the key distinction at the bottom of this slide: Functional life is not the same as economic residual value. A GPU can remain technically useful and still fail to earn enough future cash flow to support its carrying value or capital structure. Independent underwriting only creates discipline if lenders are willing to reject projects that are of marginal value or too risky. Now if Nvidia must provide residual-value support, that does not mean the asset thesis is wrong. It means the market has not yet accepted the thesis without credit enhancement. The next question is what happens if capital becomes tighter - and the upfront payment starts to matter more than lifetime total cost of ownership - in other words, if I can't fund the initial capital outlay, I don't care if Nvidia's perf/watt is better. What the neocloud earnings prints tell us Now let's test Nvidia's asset-class thesis against actual data. If compute-backed credit is going to become a durable market, the neoclouds are a good proving ground, right? And at the moment, that proving ground is flashing green - but mainly on the front half of the cycle. Let's start with CoreWeave. The company reported $2.6 billion of quarterly revenue, up 112%, and ended the quarter with $104.2 billion of backlog. That figure did not include more than $25 billion of additional customer commitments signed shortly after quarter-end. Management says near-term capacity is effectively sold out, with multiple buyers competing for each GPU brought online. Pricing and expected contribution margins on recent contracts are also rising. More than half of CoreWeave's backlog is already attached to contracts where delivery has begun, and management expects that figure to exceed two-thirds by year-end. That is important because backlog is beginning to convert into installed, revenue-producing capacity. Nebius provides similar evidence from a different operating model. It signed four AI-cloud deals averaging more than $1 billion each. Customer prepayments cover roughly 50% to 60% of the associated capex, and management says it could sell its entire planned 2027 capacity today if it chose to do so. Its capacity auction also cleared 15% above its previous record price, showing that scarcity - not surplus - still clearly defines the current market. We are also seeing preliminary support for Nvidia's residual-value thesis. CoreWeave recently signed an A100 contract extending into 2029. As we said, that architecture was introduced in 2020. Its Ampere and Hopper lines also remain largely sold out. And the financing market is responding. CoreWeave raised approximately $18 billion during the quarter and more than $32 billion cumulatively. Its latest structures support shorter-duration customer contracts. Nebius completed a $775 million asset-backed facility secured by deployed GPUs and contracted cash flows. Inference is also emerging as a second monetization vector. CoreWeave's managed-inference booked ARR increased from $1 million to more than $100 million within several months, and the company expects at least $250 million by year-end. So the current evidence validates four things: Demand is real; Pricing power remains strong; Capacity is being productively utilized; And the assets are increasingly financeable. But it does not yet validate the complete economic cycle. CoreWeave still reported $9.4 billion of quarterly capex, $640 million of interest expense and a $626 million net loss. Nebius is relying heavily on customer prepayments, asset-backed debt and continued external capital while guiding to $20 billion to $25 billion of annual capex. Neither company has yet demonstrated that it can fund a complete hardware-replacement cycle from organic free cash flow after scarcity pricing normalizes. And as we've suggested, the neoclouds need to diversify - and many are doing so - otherwise they'll simply be a low margin reseller of Nvidia hardware. Coreweave's acquisition of Weights and Biases to build out its software stack and Crusoe's moves into diversified infrastructure like storage are examples of this diversification. We would expect that to continue over time as a hedge if and when supply and demand come into equilibrium. Nonetheless. The key test remains the following: Can the next generation of infrastructure be funded from the cash produced by the current generation - without depending on another large debt raise, equity issuance, customer prepayment or vendor backstop? So our conclusion is the quarter validates demand, pricing, utilization and financeability. It does not yet validate full-cycle returns on invested capital. And that distinction determines whether compute-backed credit becomes a durable infrastructure asset class - or simply finances the next stage of the buildout before the market-clearing test we talked about last week, arrives. Updating our bubble probabilities This brings us back to the AI bubble forecast we published last week. We should not change a probability outlook simply because Nvidia announced memorandums of understanding. The $500 billion is not yet funded capital, and the final agreements still have to be completed. So the right side of this slide is conditional: What happens if these deals close, attract capital and begin financing AI factories at scale? The immediate effect is to reduce the probability of an early financing-led break. We previously assigned a 10% probability to a broad break beginning in 2027. Under the conditional case shown here, that falls to 5%. The 2028 probability declines from 25% to 20%. That is not because the underlying economics have suddenly been proven. It is because institutional capital can bridge the gap while HBM, packaging, power and sites remain constrained - and while customers continue absorbing available capacity. The recent CoreWeave and Nebius results support that delayed-reckoning scenario. Demand clearly remains strong. Pricing remains elevated. Capacity is being absorbed. And the financing market is becoming more willing to lend against contracted compute cash flows. But more available capital does not eliminate the market risk. It postpones the clearing test we discussed last week. As more projects receive financing, more hardware gets ordered, more sites are built and more capacity eventually becomes energized. That increases the amount of infrastructure that must ultimately find productive workloads and generate sufficient cash flow. So we think the risk shifts later. Our 2029 probability falls modestly from 35% to 30%, but it remains a major test year as more of the current buildout reaches productive deployment. The 2030 probability rises from 20% to 30%. In other words, the risk window becomes 2029 through 2030, rather than one specific year. That is when utilization, rental pricing, refinancing and residual values are more likely to face a genuine full-cycle test. The probability of a soft landing - or a series of rolling, segment-level corrections after 2030 - also rises modestly in our view. But there is one important caution from Ben Thompson's recent analysis. The financing cycle can turn before the operating cycle. Clusters can still be sold out and rental pricing can remain strong while lenders begin widening spreads, reducing advance rates, requiring more equity or applying larger residual-value haircuts. So even this conditional distribution assumes the new platforms remain open and willing to finance projects on attractive terms. The paradox is this: More capital makes an early break less likely - but it can make the eventual utilization and residual-value test even more critical. That changes the likely mechanism of a correction if it occurs. Instead of the buildout stopping because companies cannot finance construction, the eventual break could come through weaker productive utilization, lower rental pricing, residual-value markdowns and refinancing pressure after more capacity reaches the market. So Nvidia may be reducing near-term financing risk. But it may also be increasing the stakes of the later market-clearing event we discussed last week. As financing bridges gaps, the focus shifts to profitable workloads Let's bring the argument together. Nvidia is trying to solve the capital bottleneck. If the financing platforms in the announced MOUs come to fruition and work, more AI factories can be funded. More GPUs can be purchased. More sites can be built. And companies with real compute demand can gain access to capital at a lower cost. That reduces the risk of builders running out of money before the infrastructure becomes productive. But it does not solve the full bubble problem. It moves the decisive event downstream. The next constraint becomes creditworthy customer demand. Then productive utilization. Then residual value. Then cash flow. Remember - Independent capital does not create independent demand. The lenders may be different, but the projects may still depend on the same frontier labs, hyperscalers, sovereign buyers and assumptions about AI adoption. And that creates a systemic concern. If many institutional portfolios own loans backed by the same Nvidia systems, the same customer contracts and the same utilization forecasts, the financing may look diversified while the underlying economic risk remains concentrated. The key warning signal is not lower GPU rental prices by themselves. Lower prices could expand demand and create a healthy volume cycle (Jevons Paradox). The alarm goes off if three things happen together: Rental prices fall; Productive utilization weakens; And financing terms tighten. At that point, residual values get marked down, lenders reduce advance rates, borrowers need more equity and refinancing becomes harder. We can take a lesson from 1986 when congress rescinded the investment tax credit (the ITC). At that time, mainframe residual values suffered a steep collapse when the tax advantages for leasing incentives dried up. It coincided with a huge technological shift toward less expensive microprocessor-based systems and marked the downfall of IBM as the leading company in the technology industry. The point is, a financing cycle can turn before the GPUs go idle. This is the Ben Thompson comment we believe is most worth highlighting. When capital is abundant, buyers optimize around total cost of ownership (i.e. perf/watt). When capital becomes scarce, the upfront purchase price, required equity check and time to cash flow become more important. If I can't write the initial check I don't care about the TCO. So this move by Jensen potentially addresses the funding question for now. And the critical point becomes: Can the factory earn enough to justify the funding? Updating the bubble scorecard Let's close with how this move by Jensen affects our the current scorecard. The announcement is a profound validation of AI infrastructure as an emerging asset class. Nvidia has brought together six of the world's largest institutional-capital providers to establish financing platforms designed to mobilize more than $500 billion over time. But the announcement also makes this dashboard more important - not less important. Why? Because the question shifts from How much capital is being committed to: Does that capital convert into productive utilization, durable cash flow and an asset that retains value through a complete cycle? Right now, the green signals shown above are quite constructive. Demand is broadening. Near-term capacity remains effectively sold out. Pricing and contribution margins remain solid. New capacity is entering revenue-producing workloads. And the financing market is demonstrating that it will lend against Nvidia infrastructure and contracted compute cash flows. That is why we believe the near-term bubble risk has declined. But the yellow signals tell us that the difficult underwriting tests are still ahead. Backlog must become energized, accepted and billable capacity. Older systems must retain value after scarcity pricing begins to normalize. Credit markets must remain open if spreads widen, advance rates decline or lenders require larger equity checks. And if capital tightens, buyers may care less about lifetime TCO and more about the upfront acquisition cost and time to cash flow. Then we have the red signals. Neither CoreWeave nor Nebius has yet demonstrated free cash flow after the full burden of capital expenditures and interest at the scale being contemplated. And neither has completed an entire hardware-replacement cycle funded organically from the cash generated by the prior generation. That is a decisive test of whether this becomes a durable infrastructure asset class. By the way, Microsoft is currently the only hyperscaler promising positive cash flow. So our current read is: Lower probability of a broad 2027 break; A stronger delayed-reckoning case; And a wider primary risk window in 2029 and 2030. The likely break path also moves downstream. In other words, it becomes less about an immediate inability to finance construction and more about productive utilization, GPU rental pricing, residual-value haircuts and refinancing once substantially more capacity reaches the market. That is why we say the bubble is deferred but not disproven. Could the AI bubble mimic the sports franchise bubble where valuations have gone up perpetually. Maybe. But look... independent capital can fund more factories. But independent capital is not independent demand. Jensen may not have made the AI buildout too big to fail. But he may be making it too interconnected to fail quietly. As always, we'll be watching and updating our scenarios as needed.

[29]

Quartz

Nvidia partners with Wall Street firms on $500B AI financing

The chipmaker signed MOUs with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR to treat AI compute as a financeable asset class Nvidia $NVDA announced partnerships Monday with six major financial institutions to establish compute financing platforms aimed at mobilizing more than $500 billion in third-party capital for AI infrastructure buildout over time. Nvidia formalized the arrangements through memorandums of understanding with Apollo, BlackRock $BLK, Blackstone, Brookfield, Goldman Sachs $GS, and KKR. Through the arrangements, each firm will assemble capital pools at rates Nvidia characterized as attractive, with intended beneficiaries spanning frontier AI labs, enterprises, and cloud providers. The partnerships remain subject to execution of final agreements, the company said. "These financing platforms will help customers access scarce compute at scale and build the AI factories that will power every industry and country in the age of AI," Nvidia founder and CEO Jensen Huang said in a statement. The initiative reframes Nvidia's compute hardware as long-term infrastructure worthy of institutional financing -- putting it in the same category as commercial real estate or toll roads rather than gear that loses value on a depreciation schedule, according to CNBC. Huang said the chips qualify as "revenue-generating assets" and ticked off four characteristics that make them financeable: they are "productive," "long-lived," "fungible," and "flexible." Executives from all seven companies appeared together in a live interview on CNBC to discuss the announcement. Goldman Sachs chairman and CEO David Solomon said in the release that the firms are looking to "create a market for credit backed by NVIDIA compute." Solomon said that Huang approached the Wall Street group with the idea for the financing project. BlackRock chairman and CEO Larry Fink said in the release that the partnership "brings together NVIDIA's leadership in accelerated computing with BlackRock's ability to connect long-term capital to essential infrastructure." Fink said that some funds have already been raised and that BlackRock will be "raising quite a bit more." He characterized the effort as the start of the "next future for financial engineering," comparing it to the creation of mortgage-backed securities in the 1970s. Blackstone president and COO Jon Gray drew an analogy to residential lending on CNBC, arguing that AI compute deserves to be treated as a "financeable asset class" just as mortgage lenders underwrite homes; he added that AI usage across Blackstone's portfolio companies has grown sevenfold in the current year. The announcement builds on a period of mounting scrutiny over whether the AI buildout can sustain its pace. Investors have been questioning whether the AI economy's capital expenditure cycle will generate returns on a timetable that satisfies near-term financial expectations. The financing partnerships are structured to let Nvidia's customers acquire hardware without tapping their own balance sheets, which could ease some of that pressure by shifting debt to institutional and private capital providers. Nvidia did not disclose individual financial commitments from each firm or a timetable for deploying the planned capital, the company said.

[30]

Fortune

Nvidia taps Wall Street for $500 billion funding commitment | Fortune

The coalition, which also includes Goldman Sachs Group Inc. and KKR & Co., will "create dedicated pools of capital at significant scale at attractive rates for Nvidia customers," according to a statement Monday. Nvidia Chief Executive Officer Jensen Huang said in a CNBC interview that he approached only the six firms for the commitment, and none turned him down. The effort comes with a huge headline figure but few details on the timing and structure of the financing, or how much the plan goes beyond the string of AI deals that are already driving a large chunk of Wall Street's biggest transactions. Executives indicated that it will focus on debt financing to provide access to compute for Nvidia's largest customers and that there are already many deals in the works that would qualify toward this commitment. "We are bringing the world's leading long-term capital providers together to independently underwrite AI infrastructure," Huang said in the statement. "These financing platforms will help customers access scarce compute at scale and build the AI factories that will power every industry and country in the age of AI." Nvidia has already signed hundreds of billions of dollars' worth of deals with companies across the AI ecosystem, stoking concerns from some investors that the chipmaking giant is inflating demand and valuations across the industry through the circular nature of such agreements. Its graphics processing units, the best hardware for accelerating AI work, are by far the biggest expense items in the data center buildout. "In effect, they made Nvidia's product cheaper without really cutting GPU prices," said Felix Wang, managing director of global technology at Hedgeye Risk Management. "But it also makes future demand more sensitive to credit conditions, credit volatility, and raises a lot of questions on what we consider to be real demand." The firm is now publicly tapping the biggest private markets firms to provide funding for its customers amid the trillions of dollars that are expected to be needed for the data centers, power stations and chips that will power the next era of AI. The money will all be third-party capital, Huang said in the CNBC interview, which also featured executives from each of the six Wall Street firms. BlackRock CEO Larry Fink said on CNBC the future deals will offer "high credit quality" and allow attractive yields in debt for investors who are "overinvested in equities." "It's a big infrastructure build, and the capital markets are signaling that there's lots of capital available to support it," Goldman Sachs CEO David Solomon said, adding that his firm is trying to find different ways of "getting the capital to the right places to extend this or accelerate this." The deals will use compute power as collateral for the debt, which will take the form of private offerings as well as bonds by special-purpose entities, according to a person familiar with the matter. Those vehicles could issue as much as tens of billions of dollars in debt at a time and then lease the compute to Nvidia's clients, said the person, who asked not to be identified discussing private plans. Such deals are set to start coming to market within months, the person said. The compute is also liquid, which means financing could be reallocated to different buyers of the compute, helping reduce the risk to debt investors. As the only bank in the partnership, Goldman Sachs is positioning itself to be the lead bookrunner on the public debt deals coming to market for the deal. It will also gather investment returns from debt distributed through its asset-management arm, which oversees more than $4 trillion in assets. "AI isn't necessarily a bubble, but the market needs an earnings reality check," said Terri Spath, founder and chief investment officer of Zuma Wealth. "We're very bullish on the earnings power of AI -- where we exercise some caution is the price that investors pay for that growth." Nvidia's Financing Demands In a post on X, Huang characterized Nvidia's compute as "an investable infrastructure asset" and noted that the company may provide some financing support of "up to 25% of an opportunity." "Our role is to help unlock a very large pool of independent capital while maintaining disciplined risk exposure," he wrote. Nvidia had already been in talks to backstop as much as $250 billion to help OpenAI lease computing power from the $500 billion, 10-gigawatt data center hub that SB Energy, a SoftBank Group Corp. subsidiary, is developing in Ohio, Bloomberg reported last month. It would easily be among the chipmaker's biggest financing deals with a customer. Nvidia was also in discussions to finance $350 billion of OpenAI's purchases of its chips for the project, people familiar with the situation said at the time, asking not to be identified because the talks were private. Wall Street firms have similarly poured hundreds of billions of dollars into financing the worldwide AI data center boom, directly investing in sites and buying the companies that operate them. Two years ago, firms including BlackRock, Microsoft Corp. and the United Arab Emirates' MGX investment vehicle formed what's now known as the AI Infrastructure Partnership to bankroll data centers. Nvidia committed to supporting the coalition. Nvidia has accelerated its investments and partnerships with tech and AI companies in recent months despite growing concerns about its "circular" deals. In addition to the OpenAI financing talks, the company last month expanded a partnership with South Korean conglomerate SK Group and said the companies will be doing more than $500 billion in business with each other. It also made a "substantial" investment in Safe Superintelligence Inc., the AI startup co-founded by former OpenAI chief scientist Ilya Sutskever.

[31]

Why Jensen Huang's $500 billion AI financing plan faces a big risk from China

Jensen Huang built the world's most valuable company by pioneering the specialized computer chips behind the artificial intelligence boom. To keep his vision for the future within reach, the Nvidia founder is now attempting a different kind of engineering: convincing Wall Street investors that those chips are long-term financial assets akin to commercial real estate or toll roads. His bet hinges on outpacing AI developments in China. This week, Nvidia unveiled agreements with six of the world's largest asset managers, BlackRock, Blackstone, Apollo, KKR, Brookfield and Goldman Sachs. The goal was to assemble a $500 billion pipeline to finance the construction of data centers and GPU clusters for companies that lack the credit rating or cash to buy millions of dollars of silicon outright. Key to his plan, which Huang announced during a CNBC segment flanked by the leaders of all six Wall Street firms, is one crucial assumption: that Nvidia's graphics processing units will hold their value over time, behaving more like traditional hard assets than fast-depreciating consumer electronics. "Nvidia's AI factory platform is really an investable asset, an infrastructure asset," Huang said. "The reason for that is because it's productive, it's revenue generating, it is fungible, it's used by just about every cloud service provider, it runs every AI model." In standard asset-backed finance, a bank lends money because if a borrower defaults, the bank can repossess the asset -- like a building, a warehouse or a cargo ship -- and sell it to get their money back. Those physical assets have established secondary markets and can last decades. But the productive lifespan of cutting-edge GPUs is far from settled. While new chips power frontier model training, after a few years they are relegated to lower-margin inference work -- a shift that directly impacts their resale and collateral value. "Depreciation is the one key risk here," said Ben Emons, founder of FedWatch Advisors, who structured similar asset-backed loans for IndyMac before joining Pimco as a portfolio manager. Nvidia chips "could depreciate faster than expected," he said.

[32]

Axios

Nvidia, Wall Street partner on $500B AI financing

Why it matters: The gargantuan financing package illustrates the mushrooming scope and costs of the infrastructure needed to keep the AI economy humming. The big picture: Nvidia announced Monday that it is partnering with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to assemble more than $500 billion in financing at "attractive rates" for "the buildout of AI infrastructure over time." * The move comes after recent reports that Nvidia was in talks to guarantee financing for a quarter-trillion-dollar AI data center for OpenAI, one of its key customers. It was not immediately clear if the OpenAI backstop was part of this deal. Friction point: The move could reignite fears about the circular nature of AI financing -- in which a supplier like Nvidia provides financing or investment capital to some of its major customers. * The fear is that if one major company runs into trouble, it could have a ripple effect through the AI ecosystem. What they're saying: Nvidia CEO Jensen Huang -- who has dismissed fears of a circular AI bubble -- said in a statement that the financing deal is necessary to "help customers access scarce compute at scale."

[33]

Nvidia lines up Wall Street for a $500bn AI package

Six of the biggest names in private capital are in talks to put $500bn behind Nvidia's AI buildout. Nobody has yet said what the money buys, or who absorbs the loss if the demand never arrives. A group of financial firms is working with Nvidia on a $500bn funding package for AI infrastructure. The group covers Apollo Global Management, Blackstone, BlackRock's Global Infrastructure Partners, Brookfield Asset Management, Goldman Sachs and KKR. The Financial Times reported the talks first. Bloomberg confirmed them with people familiar with the matter. A deal could land as early as Monday. The market did not read it as good news. Nvidia shares fell as much as 3.2% on Monday. They traded at $219.01 in the early New York afternoon, down 2.2% on the day. The caveat is the story Almost nothing about the package is settled. Bloomberg's sources could not say which projects or companies the funding would back, or what form it would take. They also could not say whether the $500bn is new money at all. That last point matters more than the headline number. Nvidia has already announced hundreds of billions of dollars of commitments across the AI supply chain this year. A package that repackages existing pledges is a very different object from one that adds fresh capital. BlackRock and KKR declined to comment to Reuters. Nvidia and the other firms did not immediately respond. Nvidia has been carrying the buildout itself For most of this year the chipmaker has financed its own demand. It has been in talks over a $250bn backstop for OpenAI to lease compute at a 10-gigawatt Ohio campus. SoftBank subsidiary SB Energy is developing that site. Separately it has discussed financing around $350bn of OpenAI's chip purchases. It expanded its partnership with South Korea's SK Group to more than $500bn of mutual business. It also made a substantial investment in Ilya Sutskever's Safe Superintelligence. Add it up and the pattern is consistent. Nvidia guarantees the customer, the customer buys the chips, and the revenue lands back on Nvidia's income statement. Why a $500bn deal knocked the shares down That pattern has a name investors do not like. Circular financing describes an arrangement where a supplier funds the buyer that funds the supplier. Critics say it can inflate demand and valuations across a whole sector before anything breaks. Nvidia has heard the charge all year. When it announced $750bn of deals earlier in 2026, its own credit market flinched rather than cheered. Bringing in six outside balance sheets is one answer to that criticism. It spreads the capital load beyond the chipmakers. It also puts independent underwriters between Nvidia and the projects. That answer only works if the underwriting is real. Private credit and infrastructure funds now sit closer to the AI trade than at any point in this cycle. The BIS has already flagged the resemblance to pre-2008 credit structures. Wall Street was already inside the tent None of these firms are new to the sector. Apollo and Blackstone built a $35bn vehicle around Google TPUs. Morgan Stanley arranged a $917m loan secured against Lambda's Nvidia GPUs. BlackRock, Global Infrastructure Partners, Microsoft and MGX launched the AI Infrastructure Partnership in September 2024. It targets $30bn of equity and up to $100bn including debt. Nvidia and xAI joined in March 2025, with Nvidia serving as technical adviser rather than capital partner. Jensen Huang framed that arrangement in broad terms at the time. The global buildout of AI infrastructure, Nvidia's chief executive said, "will benefit every company and country that wants to achieve economic growth and unlock solutions to the world's greatest challenges." A $500bn package would be roughly five times the size of that earlier programme. It would also place Nvidia much closer to the money. The number to watch is not $500bn Big Tech is on track to spend more than $730bn on AI this year. Nvidia itself returned to the US bond market in June. That was its first debt sale since 2021. Against that backdrop, half a trillion dollars of arranged financing is large but not implausible. The open question is narrower and harder. If the data centres get built and the demand does not follow, somebody eats the loss. Nobody outside the room yet knows who. It could be Nvidia, a pension fund, or a private credit investor who was told this was infrastructure.

[34]

SiliconANGLE

Nvidia taps Wall Street for half a trillion dollars to fuel global AI infrastructure buildout

Some of Wall Street's biggest financial firms are partnering with Nvidia Corp. to pour half a trillion dollars of funding into the artificial intelligence industry's massive infrastructure buildout. Nvidia said today it has struck deals with Apollo Global Management Inc., BlackRock Inc., Blackstone Inc., Brookfield Corp., The Goldman Sachs The Goldman Sachs Group and KKR & Co. Inc. For the first time, those investors are treating AI hardware and infrastructure as an asset class like stocks, bonds and commodities, the chipmaker added. "In AI, compute is revenue," said Nvidia Chief Executive Jensen Huang. "We are bringing the world's leading long-term capital providers together to independently underwrite AI infrastructure." Nvidia said the funds from today's deals will go towards both its own projects and also those of its partners. Some of the projects backed by the fund will include the construction of new data centers needed to house, operate and maintain servers filled with hundreds of thousands of Nvidia's graphics processing units, which are widely used to process AI workloads. The money will also be used to back new manufacturing facilities to produce those chips in order to meet growing customer demand. Nvidia has become the single largest beneficiary of the AI boom. These days, basically every major AI firm and technology company uses its chips to power AI features, services and chatbots. It could even be argued that basically every large organization in the world has indirectly become a customer of Nvidia's, for few companies these days don't use some form of AI tools in their day-to-day business operations. Some of Nvidia's biggest direct customers include Google LLC, Microsoft Corp., Meta Platforms Inc., Amazon.com Inc., SpaceX Corp., OpenAI Group PBC and Anthropic PBC. Collectively, these companies have spent over a trillion dollars on AI projects and infrastructure in the last three years, and they're expected to invest even more in future. A huge chunk of that money has, and will continue to find its way into Nvidia's bank accounts, which is why the chipmaker's stock has increased fivefold over that three-year period. By using institutional credit, insurance funds and private capital to underwrite new AI infrastructure projects, Nvidia is helping its customers to secure the financing they need without drawing on their own balance sheets. "This is really the first time that technology chips have become an investable asset class," Huang told CNBC in an interview. "These are revenue-generating assets now. They're productive, long-lived, fungible and flexible." Traditionally, GPUs have always been seen as depreciating investments that quickly lose value upon delivery to customers. But Nvidia is challenging that assumption, arguing that compute capacity is a longer-term and bankable asset class that's widely adopted and transferable across customers. It means lenders can reliably underwrite compute as a revenue-generating asset, though skeptics may question if GPUs really retain their value when newer generations of the chips emerge. "What's different about this industry and this way of doing computing is that the computer is now part of the infrastructure, like electricity, like the internet, and so you have to think about it like it's infrastructure," Huang argued. KKR co-CEOs Joe Bae and Scott Nuttall have certainly bought into Huang's argument. They said in a joint statement that AI is already so pervasive and so important that compute has become a critical asset. "As we've scaled our approach to digital infrastructure, we've learned that delivery, not ambition, is the hard part," they added. However, not everyone agrees with Nvidia. Some investors have become wary of the chipmaker's alleged "circular dealmaking" involving eyewatering amounts of money, and today's announcement will likely stoke those fears. Last month, for instance, Nvidia announced a $500 billion deal with the South Korean semiconductor giant SK hynix Inc. to secure a supply of memory chips. Shortly after announcing that deal, reports emerged claiming that the company was discussing a $250 billion deal with OpenAI to help finance the AI giant's massive 10-gigawatt data center project in Ohio, which is expected to be one of the world's largest "AI factories" once it's completed in 2028. No agreement has been confirmed so far, but if it is, it would represent one of the company's biggest deals with a customer, Bloomberg reported. The $250 billion would only cover the data center lease and debt, and talks are ongoing regarding a separate, $350 billion deal to finance chip purchases, the report added. Critics say that Nvidia is weaving a dangerous, tangled web of deals with a handful of companies that have overlapping interests, many of which have struck multibillion-dollar deals with each other. The concern is that these financial dependencies mean that if one deal falls apart, it could lead to a domino effect that engulfs not only the AI industry, but the entire global economy, given how much money is at stake.

[35]

Entrepreneur

Nvidia Is Close to a $500 Billion Deal to Build AI Infrastructure. Why Aren't Some Investors Happy About It?

A group of Wall Street's biggest investment firms wants to hand Nvidia $500 billion for AI infrastructure, but not everyone is jumping for joy, according to Bloomberg. Apollo Global Management, Blackstone, BlackRock, Brookfield Asset Management, Goldman Sachs and KKR are among the firms in talks, with a deal possibly landing as soon as Monday. It's not yet clear which projects the money would back, or whether the commitments are brand new or stuff Nvidia already agreed to spend. Meanwhile, Nvidia's stock dropped 2.2% the same day the news broke. Some investors are concerned about Nvidia's dealmaking. The chip company has already signed hundreds of billions of dollars in agreements across the AI industry, including talks to guarantee up to $250 billion in financing so OpenAI can lease computing power from a massive Ohio data center. Investors worry these arrangements, where Nvidia funds the very companies buying its chips, are inflating demand and valuations across the industry rather than showing real growth. Nvidia keeps chugging along regardless, recently expanding a partnership with South Korea's SK Group worth more than $500 billion and making a "substantial" investment in Ilya Sutskever's Safe Superintelligence.

[36]

Nvidia is trying to quiet 'circular financing' accusations. Wall Street is unsure it will

Wall Street is on the fence about chipmaker Nvidia's latest financing initiative. Nvidia announced "memorandums of understanding" with six financial heavyweights on Monday, designed to provide half-a-trillion dollars of financing for Nvidia customers to purchase the company's products. CEO Jensen Huang immediately got out in front of the question of whether Monday's MOUs constitute more circular financing - agreements by which companies effectively pay themselves by investing in their own customers and one of the main criticisms of the AI buildout so far. "This initiative is designed to address that concern," Huang wrote Monday in a social media post , assuring investors that "the demand is real" and that "the capital is not Nvidia revenue." Some analysts on Wall Street agreed. "This appears to be a pivot away from vendor-financing ... that drew circularity fire," Vivek Arya at Bank of America wrote in a Monday note to clients. Arya said the burden of the capital commitment "sits with the consortium" of Apollo Global Management , BlackRock , Blackstone , Brookfield Asset Management , Goldman Sachs and KKR that Nvidia signed memos with, as opposed to "NVDA's balance sheet" itself. Analysts at Morgan Stanley also took heart in the announcement, saying that it should "alleviate circularity concerns." "For all of the handwringing over circularity, Nvidia's actual direct credit exposure thus far is mostly confined to credit backstops with a couple of smaller neoclouds," Joseph Moore at Morgan Stanley wrote on Tuesday. Markets reacted positively to the developments, sending Nvidia about 1% higher Tuesday. NVDA 1D mountain NVDA 1D Others on Wall Street were far more skeptical of the capital framework outlined in the MOUs. "In the end NVDA is still a part of the financing," traders at Wells Fargo wrote in Tuesday. "NVDA seems to at some point still be financially committed to helping financing the buildout itself." Wells Fargo traders said Nvidia's financial ambitions are giving "investors relative pause." Traders at Mizuho said in a Tuesday client note that they were "not sure this does much to quiet the growing concerns around circular financing." "While this partnership expands the pool of available capital and could accelerate deployments, it doesn't fundamentally answer the question of how much end-user demand and economic return sits underneath all of this spending," the Mizuho traders wrote. And even the Morgan Stanley analysts questioned the extent to which the AI buildout can absorb more investment that relies on debt, regardless of its source. "The view that the AI ecosystem will take on more leverage is in itself an investment debate, even if Nvidia does not provide the leverage," Joseph Moore at Morgan Stanley wrote. "The Nvidia view, and generally the view of the AI ecosystem, rightly or wrongly, is that this investment is not enough, given token growth of 10x or so." AI data centers can burn through high-performance graphics processing unit chips quickly, and multiple Wall Street firms complimented the Nvidia memoranda for the assurances they provided on depreciation costs. "NVDA guarantees asset quality, not the debt - turning bears' depreciation worry into the enabling feature," Vivek Arya, the Bank of America analyst, wrote. Wells Fargo traders on Tuesday called the agreements a form of "depreciation insurance."

[37]

Nvidia's $500 billion plan envelops Wall Street in its AI frenzy

Nvidia has unveiled a major financing initiative aimed at supporting artificial intelligence chip acquisitions. By collaborating with prominent financial institutions, the plan seeks to provide substantial debt solutions tailored for AI startups. This multifaceted financing strategy is designed to address the skyrocketing demand for computing power, ultimately fostering the essential digital and AI infrastructure development needed in the tech industry. Goldman Sachs Group Inc., Blackstone Inc. and Apollo Global Management Inc. had been working tirelessly for months to draw up debt deals that would help developers of artificial intelligence systems pay for chips from Nvidia Corp. With slow progress on the complex deals, Nvidia's chief executive officer, Jensen Huang, decided to change tack: He went public this week with the effort, saying the group is aiming to collectively finance AI computing deals totaling $500 billion -- a round figure with no obvious provenance. US MarketsPowered By As on 14 Aug 2026, 11:23 PM IST S&P 500 Top Gainers Copart31.53(7.28%) Seagate Technology Hldgs972.06(5.50%) Halliburton34.33(4.54%) Advanced Micro Devices504.66(4.48%) Gainers" S&P 500 Top Losers Coterra Energy32.56(-8.62%) Broadcom391.46(-6.31%) Applied Materials504.16(-5.68%) GoDaddy96.40(-4.08%) Losers" In doing so, he was seeking to assure Nvidia's investors that there are plenty of deep-pocketed firms ready to finance his clients, particularly AI startups such as Anthropic PBC and OpenAI that are key to Nvidia's future demand. While he's bullish on AI spending overall, his company has been seeking to broaden its customer base beyond hyperscalers including Microsoft Corp. and Amazon.com Inc., many of which are trying to create their own components. Huang wanted something else, too. After months of working with the trio of financiers, his $5.5 trillion firm called the original group up just days before the announcement to say that three other lenders -- KKR & Co., BlackRock Inc. and Brookfield -- were joining the pack and committing to financing a chunk of the debt. With the partnership out in the open, some of the largest firms on Wall Street are standing by to arrange hundreds of billions of dollars in financing for chip deals, while Nvidia itself will backstop a portion of those deals with guarantees. No deals were signed by the time of the announcement, which was left deliberately vague, according to people familiar with the matter who asked not to be identified discussing private talks. Investors have been concerned that Santa Clara, California-based Nvidia, whose chips are crucial in many of the data centers powering the global AI surge, and other companies have been stoking a bubble in the industry through circular financing. That's been fueled by deals where Nvidia has invested in some of its clients such as CoreWeave Inc. Initially, the financing venture's framing unnerved debt investors, concerned about how exposed it left the chipmaker to more leverage. But that eased as Huang clarified that Nvidia's support would be for as much as 25% of an opportunity and the firm would assess each project on a case-by-case basis. "The announcement reflects the financing need as we look to build out digital and AI related infrastructure in the coming years," Alan Synnott, global head of real assets at advisory firm Mercer, said in an interview. "With these partnerships, you'll actually see a range of strategies developing likely across infrastructure, real estate credit, and maybe even private equity that will offer investors a lot more access paths." Representatives for Goldman, Apollo, Blackstone, KKR and BlackRock declined to comment. A Nvidia spokesperson had no immediate response, while a representative for Brookfield didn't respond to a request for comment. Earlier this week, when Huang appeared with executives from the six firms on CNBC to talk up the deal, the segment lasted more than 30 minutes and included few additional details. Goldman CEO David Solomon, Blackstone President Jon Gray, Apollo President Jim Zelter and Brookfield CEO Bruce Flatt appeared in studio with Huang, while KKR's Waldemar Szlezak, who leads its digital infrastructure business globally, also joined. BlackRock CEO Larry Fink was on video while traveling. Now, those executives are turning to their clients, including sovereign wealth funds, pension funds and insurance firms, to gauge their appetite for buying up the debt. Executives in the television discussion indicated that some of the money could come from retail investors. The $500 billion commitment has no set time frame and is a combination of deals that have been discussed, as well as forecasts of demand in the near future, according to people familiar with the matter. Each lender will be able to vet individual customers for creditworthiness before committing. While much of the total amount will be raised through private credit markets, the scale is so large that public markets will need to be tapped. That's expected to come in the form of bonds -- many set to be tens of billions of dollars each -- issued by special vehicles that would lease chips to Nvidia clients. One person involved in the announcement described Huang's intention as setting up a debt shopfront as an advertisement to customers and concerned investors. If the deals don't happen as announced or go awry, that could pose a risk to the reputation of the financing partners and Nvidia, the person said. For some of the financing partners, the venture promises that the companies will be in line to collect fees from the deals. While Goldman is the only firm with a dedicated banking arm, Apollo could also unlock more fees as it expands its trading operation, selling larger chunks of the loans it originates to other investors and making markets for clients. For Goldman, it's the culmination of years of building up close ties to the chipmaker. Jung Min, who was named Goldman's co-head of its technology, media and telecom practice last year after two decades at the firm, has covered Nvidia for years from his San Francisco base. Toshiya Hari, the former Goldman analyst who covered Nvidia, joined Nvidia last year to work in investor relations. The splashy affair contrasts with a similar announcement from Broadcom Inc. just weeks earlier. The chipmaker tapped Apollo and Blackstone as anchor investors for plans to finance more than 20 gigawatts of compute capacity for frontier AI labs including Anthropic and OpenAI through 2028 -- potentially requiring hundreds of billions of dollars. Broadcom, however, already had $35 billion of financing in hand through a deal with Apollo and Blackstone when it unveiled the partnership. Broadcom backstopped most of the debt on that first deal to help attract investors, while Apollo structured the deal to keep the borrowing off Broadcom's balance sheet. Blackstone has already sounded out investors for another transaction of more than $30 billion, Bloomberg reported. The Nvidia debt deals will vary according to the type of customer and the owner of the data centers that will house the chips. The collateral that backs the loans is expected to be some combination of the underlying chips and the offtake agreements, said some of the people. If a deal goes awry and Nvidia clients can't afford the chips, the chips can be rented by others, helping to reduce the risk of individual Nvidia customers defaulting on the debt, according to some of the people. Skeptics say that valuations of the underlying chips is currently inflated by record demand, driven by the hype around AI. One of the worries is that the intense buildup of AI infrastructure might fuel an oversupply of computing power years in the future. For all the questions, there's no doubt other banks and investment firms still want in. JPMorgan Chase & Co.'s asset management arm, for one, is discussing how it can be involved as well, according to a person familiar with the matter. A spokesperson for the bank declined to comment. And just minutes after Monday's announcement, Morgan Stanley, long a significant lender to AI infrastructure, put out a release saying it was launching a framework to facilitate $1.5 trillion of funds in US innovation and national security. Top of its list: AI and advanced computing.

[38]

Finextra Research

Nvidia partners with Wall Street mobilise funds for AI infrastructure, Goldman Sachs leads financing

This content has been selected, created and edited by the Finextra editorial team based upon its relevance and interest to our community. On Monday the AI chipmaker announced partnerships with Wall Street firms including Apollo, Blackstone, Blackrock, Brookfield, Goldman Sachs, and KKR to raise at least £500 billion in long-term capital to finance AI infrastructure. Nvidia CEO Jensen Huang told CNBC that "computing capacity is becoming an asset class of its own," and that AI will soon be part of national infrastructures like electricity and the internet. The move marks the growing prioritisation from governments and industry leaders in investing in AI and building AI datacentres to meet demand. Huang wrote in a company blog post: "We have moved from an era in which companies bought chips and built data centers project by project to one in which AI factories can be financed as productive infrastructure -- with repeatable platforms, long-term institutional capital and a diverse customer base that uses compute to create revenue." The investor base for the financing is expected to consist of money managers and insurers, while asset managers will gain a share of the financing, sources reported to Reuters. Nvidia may back just a quarter of the financing, Huang said in the blog post. Goldman Sachs is in discussions with investors on financing the deal with junior capital and private credit, and will be a central lender, the sources said. Goldman Sachs, Apollo, and Blackstone also joined Anthropic's AI $1.5 billion joint venture in May 2026. In February 2026, Nvidia was considering a $30 million investment in OpenAI.

[39]

What Makes the AI Music Stop: a $1.5 Trillion Mountain of Hidden Leverage - Meta Platforms (NASDAQ:META),

The artificial-intelligence infrastructure race might be entering an opaque phase. What began as a cash-flow-funded spending spree by the world's richest technology companies is increasingly becoming a debt-driven capital-expenditure cycle. A vast amount of capital is routed through leases, joint ventures, purchase commitments and private-market financing. The tension is that the hyperscalers still look extraordinarily healthy. Companies such as Alphabet Inc., Meta Platforms Inc., Microsoft Corporation and Amazon.com Inc. generate vast cash flows, hold large cash balances and carry relatively modest reported leverage. But, according to Robin Wigglesworth, author and editor of the FT Alphaville - official balance sheets are no longer telling the full story. "It's one of the biggest capital markets events of our lifetimes," Wigglesworth said in a recent interview. For years, the hyperscalers could fund data centers from their core businesses because "Google search, Amazon, Facebook itself just prints money." Now, he said, "the scale is just becoming so massive that they've increasingly turned to the debt markets." The Hidden AI Balance Sheet The clearest example is Meta's Hyperion data center in Louisiana. Rather than simply issue debt itself, Meta formed a joint venture with Blue Owl called Beignet, took a 20% stake and guaranteed that it would lease the facility for at least 20 years. That structure allowed Beignet to issue $27 billion of bonds while keeping the debt off Meta's balance sheet. Latest Private Market Opportunities Join 400,000+ Investors "It doesn't come up as a bond or a debt or a loan for Meta," Wigglesworth said. "But, of course, it's on the hook for paying this lease for 20 years." Goldman Sachs has estimated that hyperscalers carry about $1.5 trillion in lease commitments. Roughly $1 trillion relates to leases that have not yet commenced and therefore are not recognized as conventional liabilities under U.S. accounting rules. They reside largely in disclosure footnotes until the lease begins. The companies are also accumulating contractual commitments for chips, computing capacity, cooling systems and energy. Those purchase obligations have reached nearly $1.5 trillion, led by Alphabet, which disclosed more than $800 billion in future commitments. "These are financial liabilities that are in many cases extremely hard to squirrel out of," Wigglesworth said. "They kind of walk, talk and quack a bit like debt, but they don't actually appear as debt." Compute Becomes Collateral The next stage is the financialization of compute itself. NVIDIA Corporation and alternative-asset managers including Blackstone Inc. , BlackRock Inc. and KKR & Co. Inc. are pursuing structures designed to treat chip capacity and computing contracts as investable assets. The comparison to commercial real estate or energy infrastructure is tempting. But compute has a shorter and less certain useful life than a pipeline, power plant or office building. Chips depreciate, fail, require replacement and can be superseded by new generations of hardware. "Just because you say something is an asset class doesn't make it so," he said. Chips degrade, require maintenance and can become obsolete quickly. Those risks can be priced, he added, but the sheer volume of money and the prevailing fear of missing out make the cycle more fragile. William Lee of Global Economic Advisors is more direct. "I want to be the person that raises that awful word leverage," he said on CNBC. The parallels, he argued, are with captive finance models such as GMAC in autos -- except now the financing is tied to compute. "We're seeing NVIDIA providing financing for compute," Lee said. Private credit funds are taking on more exposure, while banks are indirectly connected through credit lines that provide liquidity to the system. If rates rise or liquidity dries up, he warned, "we start to have a crunch." The risk is more concentrated among companies without the core cash-generating businesses of the biggest hyperscalers. Oracle Corporation is more indebted relative to revenue than its larger peers, while CoreWeave Inc. represents the more leveraged neocloud model: massive borrowings underwriting an AI buildout without the same cushion from legacy businesses. "I'm not worried about Facebook and Alphabet or Amazon going bust," Wigglesworth said. "There will be, of course, in any cycle a few extreme outliers that just borrowed way too much money." Why the Boom May Last Marko Papic of BCA Research expects AI infrastructure to eventually face overbuilding, as has happened with previous investment booms in areas such as canals and fiber-optic networks. However, Papic does not see a bust as necessarily imminent. Falling token costs and the rise of open-source models are making AI cheaper to deploy. That could broaden adoption, increase demand for computing capacity and support further data-center investment. Papic argues that lower AI costs are helping extend the capital spending cycle because data centers can still generate attractive returns and support viable business cases. The key warning sign would emerge when the pace of AI capital spending growth begins to slow and earnings stop delivering positive surprises. Image via Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

[40]

Wccftech

US Tech Advisor David Sacks Calls The Biggest Risk To NVIDIA's $500 Billion AI Financing Plan A 'Dark GPU' Glut

After NVIDIA and CEO Jensen Huang announced their latest initiative last week, which now turns the firm's GPU into an asset class similar to financial securities, Trump advisor David Sacks discussed the biggest risk to the plan and the ongoing AI buildout. NVIDIA's latest announcement will also see the firm backstop the GPUs by providing residual support, Huang outlined. In his appearance on the All In Podcast, Sacks outlined that an oversupply of compute remained the biggest risk to the AI buildout. Sacks Says Opposition To AI Data Centers Might Work In Favor Of The Ongoing Buildout With big tech's spending on the data center infrastructure buildout continuing to scale to new highs, David Sacks, who serves on the President's science and technology advisory council, discussed the biggest risk to NVIDIA's partnership with the investment community to establish independent financing platforms to make GPUs a financeable and income-producing asset. Sacks remarked that the biggest risk to the initiative was not on the demand side. Instead, he outlined: "The biggest risk, to me, is not on the demand side, the biggest risk is that you get a glut of compute and you get an overbuild. And, in the same way we had dark fiber after the dotcom crash, if you have dark GPUs that would be a disaster for everyone, especially if you built out your compute infrastructure expecting a spot price of $30-$50/watt, as, you know, Elon said they were expecting, right." NVIDIA's $500 Billion Initiative Aims To Address Buildout Financing Constraints, Says Sacks Sacks' comments referred to remarks made by Elon Musk to SpaceX employees in a company call where he outlined that the value of AI compute was roughly $30 to $50 per watt. The executive added that the value could enable him to earn between $300 billion and $500 billion in revenue by the end of 2027 through providing a gigawatt of compute. Yet, soon, compute infrastructure provider Nebius outlined that its multi-year cloud agreements were worth between $20 million and $25 million per megawatt for annual contract value. Nebius' statement implied that Musk intended to. charge significantly more for short-term agreements. Sacks continued and shared that oversupply risks in the compute market, coupled with expectations of the price per watt, could create a situation similar to the Dotcom crash, where fiber prices collapsed in the aftermath to create 'dark fiber:' "So, if all of a sudden, there are too many people racing to supply this compute and now there's an oversupply, and the market crashes, that's be the risk factor. In a weird way, all of the political headwinds ensure against that outcome. Because it is so hard to build data centers for all the reasons we said. There is a whole moral panic slash hysteria slash hoax going on, that actually, it's those political headwinds I think will almost guarantee that there is not an oversupply relative to the exponentially growing demand. So in a weird way, you're protected against that." As for the reasons behind NVIDIA's latest initiative, Sacks believes that the primary objective is to alleviate financing constraints currently being faced to meet the total addressable market (TAM) estimates for the AI infrastructure buildout: "So, just to take one example. Elon plans to add somewhere around six to eight gigawatts next year. We know that that would cost three to four hundred billion dollars of Capex. The company just raised a hundred billion in its equity and debt offerings. So obviously, they would have to go out and finance that somehow. And as we talked about on our previous episode, the simplest way to finance it would be to get seller financing from NVIDIA. . .so now, Jensen is creating, you could say, the line of credit using these big banks, using these big private equity shops. And he's making that available and that's going to now benefit all these downstream purchasers." Follow Wccftech on Google to get more of our news coverage in your feeds.

[41]

Japan Times

Nvidia's show of financial force soothes credit markets

Six of the biggest names in finance are helping Nvidia ease some of the investor anxiety that's been building for weeks over its swelling commitments to backstop the artificial intelligence boom. The early signs came after Nvidia CEO Jensen Huang announced Monday that the coalition of major investment firms including BlackRock and Goldman Sachs Group were lining up more than $500 billion to help fund the AI build-out. The group will independently judge individual deals and their own participation level, while Nvidia's contribution will be relatively limited, and only factor into some deals. The idea is that outside money, sophisticated eyes on deals and Wall Street's stamp of approval should help alleviate worries that Nvidia was inflating an AI asset bubble with circular financing. In less than three weeks, a gauge of the chipmaker's credit risk had nearly doubled on concern that while loans to customers would bring more sales, they risked causing pain later if those customers fail.

[42]

GameReactor

Nvidia teams up with Wall Street banks for huge AI investment

The chip manufacturer has raised $500 billion for AI infrastructure. Nvidia has struck deals with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR, some of the biggest banks on Wall Street, in order to invest $500 billion into artificial intelligence. According to Nvidia, this is the first time AI hardware and infrastructure has been treated as an asset class. The huge sum of money is set to go towards Nvidia's own projects, as well as helping those built by its partners. It's believed new data centres are likely to be made off the back of the investment, and new factories to manufacture the AI chips needed, and increase their availability to buyers. "Compute has become a critical infrastructure asset. As we've scaled our approach to digital infrastructure, we've learned that delivery, not ambition, is the hard part," said Joe Bae and Scott Nuttal, co-CEOs at KKR (via BBC News). Big tech has collectively spent over a trillion dollars USD in three years on AI infrastructure, with more spending expected as it continues its bet on the technology.

[43]

Wall Street just endorsed Jensen Huang's 'big concept' for AI. What now?

"You can think about it as a revenue stream, and you can securitize it or effectively divide that risk and sell it," said Waldemar Szlezak, KKR's head of digital infrastructure. The first three-plus years of the artificial intelligence buildout has been paid for through record amounts of equity and debt issued by the world's leading tech companies, some of whom are spending so much of their existing capital that they've turned cash-flow negative. Nvidia CEO Jensen Huang just revealed what he expects to be the next phase of financing, backed not by corporate balance sheets, but by Wall Street's top power brokers. In an interview with CNBC on Monday, Huang called his plan a "big concept," unveiling it on camera alongside leaders from Goldman Sachs, BlackRock, Blackstone, KKR, Apollo and Brookfield. Together, those firms say they're willing to loan $500 billion, and potentially more, for the construction and buildout of new AI factories, as chipmakers and hyperscalers race to meet seemingly endless demand. Huang and his big-money partners, one by one, described what they view as a fundamental shift in the tech industry: AI infrastructure has become a new asset class. "These systems are not like our PCs, not like our phones," Huang told CNBC's Becky Quick. "These are revenue-generating assets now. They're productive, they're long lived, they're fungible, they're flexible." The discussion was thin on specifics as far as the types of borrowers that will emerge, what interest rates will look like, where the facilities will be constructed and when it will all kick off. Their joint press release said the companies had signed memos of understanding, with no reference to any contracts. The details matter. Almost 11 months ago, Nvidia announced a partnership to invest up to $100 billion in OpenAI as part of a plan to build out data centers requiring a combined 10 gigawatts of power. That investment never materialized, but Nvidia contributed $30 billion to the record-breaking funding round that OpenAI closed earlier this year. Monday's announcement struck a different tone, with the companies collectively pushing the message that money won't be the problem as the AI buildout hits what McKinsey expects will be $7 trillion in global outlays by the end of the decade. So far this year, Alphabet, Amazon, Meta, Microsoft and Oracle have raised well over $150 billion combined by selling debt and equity to build data centers and fund the development of new AI models and support the explosion of AI agents. Intel just announced a $15 billion stock offering, then upsized it to $20 billion. Financial firms are now gearing up to jump into the market in a different way, as executives like Goldman Sachs CEO David Solomon and KKR's Waldemar Szlezak see AI equipment attaining familiar money-making characteristics. "You're starting to see, in a sense, you know, asset-based financing against this infrastructure buildout," Solomon said on the CNBC panel. "That's not surprising because these are real assets. They have real value." Instead of seeing supercomputers as devices that customers buy and use -- the argument goes -- these systems, filled with Nvidia's graphics processing units that can cost $3 million per rack, look like profitable investments. Huang says the systems can be improved through his company's CUDA software, and their lifespans extended, leading to better economics. "You can think about it as a revenue stream, and you can securitize it or effectively divide that risk and sell it to investors who want to participate anywhere in that stack," said Szlezak, KKR's head of digital infrastructure. When Wall Street starts getting noticeably excited about securitizing physical assets, a natural question emerges: What could go wrong? One of the hallmarks of the financial crisis of 2007 to 2009 was the packaging of subprime mortgages into bundled securities that were then sold to investors as another way to make money from the housing boom. When mortgage defaults started going up, the whole system began to unwind. Famed short-seller Michael Burry, who made a fortune betting against subprime mortgages, suggested late last year that companies including Meta, Oracle, Microsoft, Google and Amazon were overstating the useful life of their AI chips and understating depreciation. The subprime meltdown wasn't part of the conversation on Monday, but several of the financiers acknowledged a certain amount of risk in the AI trade. "There will be excesses, there will be pullbacks," said Jim Zelter, president of Apollo Global Management, adding that the number of participants in the project alleviates concentration concerns. "There'll be big companies that win," Solomon said. "There'll be big companies that turn out to be not what people expected." In discussing BlackRock's role in Monday's agreement, CEO Larry Fink made a direct comparison to the mortgage market, though he referenced a period decades before the housing boom and bust. "This is the very beginning, like what it was when I started in the mortgage-backed securities market in the 1970s," Fink said. "I look upon this as as a next future for financial engineering." All six of the financiers will make their own lending decisions, Huang said in the interview, noting that Nvidia will connect customers with financing partners. Nvidia said it will have the option of backstopping 25% of every loan, a structure that should result in more favorable interest rates for companies that have previously had to rely on their own credit rating. Borrowers will have to use system architectures specified by Nvidia that would allow another company to take it over and operate it "if something were to happen," Huang said. Nvidia still has plenty to iron out with its financing partners, but Monday's gathering marked a major step in showing the kind of money available to others in the ecosystem. Brookfield CEO Bruce Flatt said Huang created the necessary format for investors. "Jensen's leading this to create structures," Flatt said. "Because there's hundreds of trillions of dollars of money in the world." Choose CNBC as your preferred source on Google and never miss a moment from the most trusted name in business news.

[44]

Goldman in talks with investors on Nvidia financing deal after landing prized role

Nvidia announced on August 10 it has partnered with six major financial institutions including Goldman to launch compute platforms aimed at raising over $500 billion in third-party capital for AI infrastructure. The move ⁠highlights how ⁠surging demand for AI computing capacity is drawing institutional investors, as governments, companies and startups race to build out data centers to support AI workloads. Goldman Sachs is in talks with potential investors about participating in Nvidia's $500 billion AI financing initiative, after leveraging its long-standing relationship with the chipmaker to secure a coveted role in the deal, people familiar with the matter said. US insurers, money managers and banks are expected to form the core investor base for the financing, one of the people said, while asset managers plan to retain a sizable share of the financing, a second source said. Nvidia announced on August 10 it has partnered with six major financial institutions including Goldman to launch compute platforms aimed at raising over $500 billion in third-party capital for AI infrastructure. The move ⁠highlights how ⁠surging demand for AI computing capacity is drawing institutional investors, as governments, companies and startups race to build out data centers to support AI workloads. Goldman can provide junior capital and private credit financing through its asset management arm, while its investment bank can also help place the debt into private credit funds and eventually public debt markets, the second source said. The first source said the firm had held discussions with a wide range of investors about such structures, including banks, asset managers, insurers and private credit firms. The Wall Street bank's central role as the sole lender on the deal, alongside alternative asset management giants such as Blackstone and Apollo, marks the culmination of years of ties with Nvidia. Goldman Sachs has advised Nvidia on several transactions ⁠and on numerous technology financing deals in which the chipmaker was an investor, according to Dealogic. The bank was also among the lead underwriters on the chipmaker's $25 billion bond sale in June and served as an exclusive financial adviser on Nvidia's $6.9 billion acquisition of ⁠Mellanox Technologies in 2019. The bank's technology teams also maintain close ties with Nvidia, while the relationship extends to the highest levels of both companies, the second source and a third source familiar with the matter said. Less than two years ago, Goldman Sachs CEO David Solomon interviewed Nvidia CEO Jensen Huang at a technology conference hosted by the Wall Street firm. "Jensen came, approached us with the idea, and we said we'd love to talk to you about it," Solomon told CNBC in a joint interview with Huang and executives of other partner firms after the Nvidia financing plan was unveiled on Monday. Nvidia declined comment and instead pointed Reuters to Huang's blog post which details that the financing is to support the buildout of AI infrastructure over time. Nvidia, which went public in 1999 in an initial public offering led by Morgan Stanley, is now worth about $5.2 trillion, making it the most valuable publicly listed company in the United States. Unusual structure Goldman Sachs Research analysts recently noted the financing needs for artificial intelligence are enormous with the top four hyperscalers planning to spend more than $5 trillion by ⁠2030 on technology and data centers. That scale of investment is likely to make private capital an increasingly important funding source. The demand has encouraged firms to explore new ways of financing deals. The structure of the Nvidia financing differs from earlier AI infrastructure deals that depended heavily on vendor guarantees such as Broadcom's residual-value guarantee on roughly $30 billion of senior debt backing Anthropic's AI chip financing. Nvidia CEO Huang said on X that the company has the option to backstop up to $125 billion, or 25% of the potential deals. The goal is to create an asset-backed market for AI compute, allowing debt to trade more like traditional securities, which could lower funding costs and draw a broader pool of investors, the second source said. "This appears to be a pivot away from vendor-financing," said Bank of America analyst Vivek Arya in a note. "The burden sits with the consortium, not (Nvidia's) balance sheet."

[45]

PYMNTS

Nvidia Uses $500 Billion Financing Initiative to Dispel AI Bubble Fears | PYMNTS.com

The initiative is also meant to expand Nvidia's customer base beyond hyperscalers, some of which are developing their own components; to show that some of the largest Wall Street firms are set to arrange financing for chip deals; and to ease investors' concerns that circular financing, including Nvidia's investments in some of its clients, could stoke a bubble in the AI industry, according to the report. One person involved in the announcement of the initiative described the project as an advertisement to customers and investors, per the report. As PYMNTS reported Monday, Nvidia's partners in the AI financing initiative include Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR. The partnerships remain subject to the execution of final agreements. Nvidia and the six financial institutions will establish independent compute platforms designed to mobilize over $500 billion of third-party capital for the buildout of AI infrastructure. The compute financing platforms will be established at global scale, and the partnerships will see Nvidia work with the firms to create dedicated pools of capital at scale at attractive rates for Nvidia customers. When announcing the initiative, Nvidia CEO Jensen Huang said in a press release: "In AI, compute is revenue. Nvidia compute is uniquely suited for this role. It is broadly adopted, flexible across models and workloads, fungible and transferable across customers and operators, and continuously improved through CUDA software -- extending its useful life and improving its economics over time. It is supported by a deep global ecosystem of developers, customers and offtakers." It was reported Friday that Goldman Sachs is talking with potential investors about participating in the initiative and that the firm has talked with banks, asset managers, insurers and private credit firms. Goldman Sachs' investment bank can help place the debt into private credit funds and public debt markets, while its asset management arm can provide junior capital and private credit financing, the report said. For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

[46]

Goldman Sachs Eyes Role in Nvidia's $500B AI Financing Initiative - Goldman Sachs Group (NYSE:GS)

Goldman Sachs Courts Investors to Join Nvidia's $500 Billion AI Financing Initiative: Report Goldman can supply junior capital and private credit, and help place debt into private and public markets, Reuters reported, citing sources. Asset managers plan to retain a sizable share of the financing. Goldman Sachs did not immediately respond to Benzinga's request for comment. A Relationship Years in the Making This relationship extends to the top of both firms. Less than two years ago, Goldman CEO David Solomon interviewed Nvidia CEO Jensen Huang at a technology conference hosted by the bank. In a CNBC interview on Monday, Solomon said Huang approached Goldman with the idea for the financing structure, and the bank welcomed the opportunity to discuss it. Skepticism Hedge fund manager Michael Burry earlier this week called the initiative a "Wall Street stunt," warning the private-credit structure recalls past cycles, "Meet the new Boss. Same as the old Boss." FedWatch Advisors founder Ben Emons also flagged China's cheaper chips as a risk to GPU collateral values underpinning the debt. Stock Comparison According to Benzinga Pro data, GS closed at 1,042.63, up 0.52%, on Thursday, while NVDA closed at 225.30, up 0.54%. Benzinga's Edge Stock Rankings indicate that GS is experiencing short-term consolidation along with medium and long-term upward movement. Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Photo Courtesy: bluestork on Shutterstock.com Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

[47]

CXOToday

Nvidia Has a $500 Bn Plan To Create a Secondary Market for Ageing GPUs

More compute creates better AI; better AI creates more usage; more usage creates more revenue; and more revenue drives more compute. GPU-maker Nvidia had announced earlier this week that a bunch of investors led by the likes of BlackRock, Brookfield, Goldman Sachs, and KKR would commit up to $500 billion for AI datacentre buildouts. However, what skipped notice is that the company is also making efforts to create a secondary market for aging GPUs. "This is a major milestone for NVIDIA and the AI industry. We have moved from an era in which companies bought chips and built datacentres project by project to one in which AI factories can be financed as productive infrastructure -- with repeatable platforms, long-term institutional capital and a diverse customer base that uses compute to create revenue," the company had said in a blog. What Nvidia has done to convince the big ticket financiers is that it would guarantee that its chips used as collaterals in these deals will retain their value. And the chipmaker would use its own money to make this guarantee. At first glance the move appears to be rather unusual though some say it is a killer idea. In fact, the bond markets did not know how to respond to this plan, that was also described by some as rather dangerous. Essentially, the idea is to fund AI datacentres but Nvidia is looking to ensure that there is an ecosystem of used AI hardware in the process. Nvidia CEO Jensen Huang said on his X handle that "AI has reached an inflection point. It is moving from research into production. AI is creating real value, and the infrastructure behind it is becoming one of the world's most productive assets. In AI, compute is revenue." Nvidia compute is not just a chip. It is a complete AI factory platform including accelerated computing, networking, systems software, AI frameworks and a global developer ecosystem. The DSX AI factories can run the world's broadest range of AI models, modalities and algorithms -- language, vision, speech, biology, physical AI and robotics. One NVIDIA AI factory can serve many customers and many workloads. That makes it flexible and fungible, he says. Stating that the demand for AI infrastructure was extraordinary and access to capital uneven, he noted that several AI companies, enterprises and AI clouds have demand for compute but do not yet have access to financing at the scale or cost required to build quickly. "That is why we are partnering with the world's leading long-term capital providers," said. Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR are also among the world's leading infrastructure investors, with deep expertise in underwriting long-lived, productive assets. Together, we are creating repeatable financing platforms to help the AI ecosystem build the factories it needs, the Nvidia CEO noted. He underscored the fact that the platforms are designed to help qualified AI labs, enterprises and AI clouds access AI-factory infrastructure at scale. The more than $500 billion figure represents aggregate third-party capital that these platforms are designed to mobilize over time -- the capital is not Nvidia revenue, a single fund or a commitment to a single customer, he added. Huang said the financial institutions will independently assess each opportunity -- the customer, demand, utilization, cash flow and residual value. Nvidia provides the AI factory platform. The financial institutions provide long-term capital and financing expertise. "This initiative is designed to address that concern. We are bringing independent, long-term institutional capital into the AI infrastructure market." He underscored that this wasn't circular financing as he demand was real and came from frontier AI labs, AI-native startups, enterprises, cloud providers and countries building AI services. "The capital providers independently underwrite each project -- including the customer, demand, utilization, cash flow and residual value. NVIDIA provides the platform; the investors make independent financing decisions. This is the beginning of an open capital market for AI infrastructure," he said. He further clarified that Nvidia may provide a residual-value support mechanism for up to 25% of an opportunity, assessed carefully on a project-by-project basis. That support is limited, residual-value based and designed to complement -- not replace -- independent underwriting. This is substantially lower than other compute-financing arrangements. Nvidia can provide support because Nvidia compute is unique: it is fungible, universally adopted, software-upgradable and re-deployable across a large ecosystem of customers. "Our role is to help unlock a very large pool of independent capital while maintaining disciplined risk exposure," he added. The Nvidia boss said the question is not whether they are building datacentres but these would be productive AI factories. An AI factory turns energy and data into valuable intelligence. Its customers are broad: frontier AI labs, AI clouds, enterprises and nations. They are building AI because it has become useful -- doing valuable work across every industry, he noted. "There is discipline in the model. Each financing partner will independently evaluate demand, utilization, cash flow and residual value. Capacity will be built around real customer economics," he said, noting that the return is in the usefulness of AI. Huang said every industrial revolution has been built on infrastructure: electricity, transportation, communications and computing, with every buildout enabled by external financing and AI factories are the infrastructure of the intelligence era. With these partnerships, Nvidia and the world's leading financial institutions are creating a new way to finance the infrastructure that will power this industrial revolution. We will make AI factories more accessible to the companies, industries and nations building the future. The age of AI is here. Together, we will build the infrastructure to power it, he added. Companies are using AI to write software, discover drugs, design products, serve customers, automate operations and build new services. AI factories make this possible. More compute creates better AI; better AI creates more usage; more usage creates more revenue; and more revenue drives more compute.

[48]

PYMNTS

Goldman Sachs Mobilizes Investors for Nvidia's $500 Billion AI Infrastructure Push | PYMNTS.com

Goldman Sachs has talked with banks, asset managers, insurers and private credit firms, according to the report. The firm's investment bank can help place the debt into private credit funds and public debt markets, while its asset management arm can provide junior capital and private credit financing, the report said. Nvidia announced Monday that Goldman Sachs is one of the six financial institutions it partnered with to establish independent compute platforms designed to mobilize over $500 billion of third-party capital for the buildout of AI infrastructure. The other five institutions are Apollo, BlackRock, Blackstone, Brookfield and KKR. The partnerships remain subject to the execution of final agreements. Nvidia Founder and CEO Jensen Huang said in the announcement that AI factories are "a new class of productive, investable architecture," that in AI, "compute is revenue" and that Nvidia compute is suited for this role because it is broadly adopted, flexible, fungible and transferable. In Nvidia's Monday press release announcing the partnerships, Goldman Sachs Chairman and CEO David Solomon said: "We're in a pivotal moment of a historic AI investment cycle. Nvidia's full-stack platform is in high demand and uniquely positioned at the center of that global buildout. Our investment and distribution roles reflect our confidence in Nvidia's leadership, and we're excited for the new opportunity to create a market for credit backed by Nvidia compute." PYMNTS reported July 14 that Goldman Sachs had an unusually profitable trading period during the second quarter and that the AI investment boom was beginning to function as a full-firm revenue engine. Goldman Sachs executives spent much of the firm's July 14 earnings call positioning the AI investment cycle as a multiyear generator of advisory, underwriting, financing, trading and wealth management revenue. The expansion of the AI capital cycle into the physical buildout plays directly into Goldman Sachs' effort to connect its historically volatile investment-banking and trading businesses with a more durable financing and asset management revenue, PYMNTS reported at the time.

[49]

Goldman Sachs taps investors for Nvidia's $500 billion AI financing push

Goldman Sachs is negotiating with investors for Nvidia's massive AI financing initiative. U.S. insurers and money managers will likely form the core investor base. This plan aims to raise over $500 billion for AI infrastructure development. Nvidia's CEO approached Goldman Sachs with this innovative financing idea. The structure aims to create an asset-backed market for AI compute. New York: Goldman Sachs is in talks with potential investors about participating in Nvidia's $500 billion AI financing initiative, after leveraging its long-standing relationship with the chipmaker to secure a coveted role in the deal, people familiar with the matter said. U.S. insurers, money managers and banks are expected to form the core investor base for the financing, one of the people said, while asset managers plan to retain a sizable share of the financing, a second source said. Also Read: Goldman Sachs cuts India's 2026 CAD forecast to 1.3% of GDP Nvidia announced ⁠on August ⁠10 it has partnered with six major financial institutions including Goldman to launch compute platforms aimed at raising over $500 billion in third-party capital for AI infrastructure. The move highlights how surging demand for AI computing capacity is drawing institutional investors, as governments, companies and startups race to build out data centers to support AI workloads. Goldman can provide junior capital and private credit financing through its asset management arm, while its investment bank can also help place the debt into private credit funds and eventually public debt markets, the second source said. The first source said the firm had held discussions with a wide range of investors about such structures, including banks, asset managers, insurers and private credit firms. The Wall Street bank's central role as the sole lender on the deal, alongside alternative asset management ⁠giants such as Blackstone and Apollo, marks the culmination of years of ties with Nvidia. Goldman Sachs has advised Nvidia on several transactions and on numerous technology financing deals in which the chipmaker was an investor, according to Dealogic. The bank was also among the lead underwriters on the ⁠chipmaker's $25 billion bond sale in June and served as an exclusive financial adviser on Nvidia's $6.9 billion acquisition of Mellanox Technologies in 2019. Also Read: Goldman Sachs raises India FY27 growth forecast to 6.5% The bank's technology teams also maintain close ties with Nvidia, while the relationship extends to the highest levels of both companies, the second source and a third source familiar with the matter said. Less than two years ago, Goldman Sachs CEO David Solomon interviewed Nvidia CEO Jensen Huang at a technology conference hosted by the Wall Street firm. "Jensen came, approached us with the idea, and we said we'd love to talk to you about it," Solomon told CNBC in a joint interview with Huang and executives of other partner firms after the Nvidia financing plan was unveiled on Monday. Nvidia declined comment and instead pointed Reuters to Huang's blog post which details that the financing is to support the buildout of AI infrastructure over time. Nvidia, which went public in 1999 in an initial public offering led by Morgan Stanley, is now worth about $5.2 trillion, making it the most valuable publicly listed company in the United States. UNUSUAL STRUCTURE Goldman Sachs Research analysts recently noted the financing needs for artificial intelligence are enormous with the ⁠top four hyperscalers planning to spend more than $5 trillion by 2030 on technology and data centers. That scale of investment is likely to make private capital an increasingly important funding source. The demand has encouraged firms to explore new ways of financing deals. The structure of the Nvidia financing differs from earlier AI infrastructure deals that depended heavily on vendor guarantees such as Broadcom's residual-value guarantee on roughly $30 billion of senior debt backing Anthropic's AI chip financing. Nvidia CEO Huang said on X that the company has the option to backstop up to $125 billion, or 25% of the potential deals. The goal is to create an asset-backed market for AI compute, allowing debt to trade more like traditional securities, which could lower funding costs and draw a broader pool of investors, the second source said. "This appears to be a pivot away from vendor-financing," said Bank of America analyst Vivek Arya in a note. "The burden sits with the consortium, not (Nvidia's) balance sheet."

[50]

CCTV Script 11/08/26

- This is the script of CNBC's financial news report for China's CCTV on AUG 11, 2026. NVIDIA said Monday it has signed memorandums of understanding with six Wall Street giants, including Apollo Global Management, Blackstone, BlackRock, Brookfield, Goldman Sachs and KKR, to advance a $500 billion financing plan for its customers. Analysts say the move shows Nvidia is seeking to turn AI chips into a new asset class for Wall Street. The plan could reshape financing for AI infrastructure. Institutional credit, insurance capital and private capital would support hyperscalers, frontier AI labs and companies building data centers and purchasing Nvidia chips. That could allow Nvidia customers to tap external funding instead of relying entirely on their own capital, easing pressure on their balance sheets. Nvidia CEO Jensen Huang and several financial executives spoke with CNBC overnight. Huang said computing is undergoing its first fundamental technology-platform transition in roughly 60 years, shifting from a traditional model to one centered on artificial intelligence. Jensen Huang Nvidia CEO "Fundamentally, what's different about this industry and this way of doing computing is that the computer is now part of the infrastructure, like electricity, like the internet, and so you have to think about it like its infrastructure and build it out accordingly. Every company will be powered by it. Every country will build it, and so we're talking about a extraordinarily significant infrastructure build." Several financial executives also expressed confidence in demand and agreed that AI computing capacity could become a new asset class. Jon Gray Blackstone President "At our companies, we've seen a sevenfold increase in demand for LLMs in the last six months, and yet the amount of compute is not keeping up. The data centers, the power, the chips, and so what you're going to see here is people are going to begin to recognize that this is a financeable asset class." Larry Fink BlackRock CEO "I look at the financing of data centers. This is the very beginning, like what it was when I started in the mortgage-backed securities market in the 1970s, and I look upon this as the next future for financial engineering." Analysts say the core of the arrangement is that the value of computing assets does not depend on the success or failure of a single AI company. Even if one company fails, the equipment could be taken over by others. Because these chips have longer useful lives and retain their value, financial institutions could securitize them into financeable, tradable assets. But some market participants remain concerned about the risk of "circular deals" in AI. Nvidia has often provided funding to its AI partners or helped them raise debt, which has also supported Nvidia's own revenue. That creates a cycle in which Nvidia funds customers, and customers then buy Nvidia products. If AI demand, financing conditions or partners' debt-servicing capacity fall short of expectations, risks could spread among chip suppliers, customers and capital providers.

[51]

Jensen Huang's $500 Billion Nvidia AI Financing Bet Faces a China Problem -- Could Cheaper Chinese Chips Sin

China Could Threaten Nvidia's $500B AI Financing Bet That creates a major risk for Nvidia's new financing strategy. The initiative aims to help companies, including startups and cloud providers, finance the cost of expensive data centers and GPU clusters. Huang's argues that Nvidia's AI infrastructure is an "investable asset" because it generates revenue and can support workloads across cloud providers and AI models. But Emons believes depreciation could undermine that thesis. Nvidia GPUs Face Depreciation Risk Unlike buildings or other traditional infrastructure, cutting-edge GPUs can lose value quickly as newer chips arrive. Older processors may eventually shift from frontier AI training to lower-margin inference workloads, reducing their resale value. That becomes especially dangerous if Chinese chipmakers offer cheaper alternatives. If GPU values plunge while borrowers still owe billions of dollars in financing, Wall Street lenders could be left with collateral worth significantly less than the outstanding debt. Emons estimates investors could therefore demand high-yield returns of roughly 11% to 17% to compensate for the risk. Nvidia Still Has a Major Advantage For now, Nvidia remains the dominant U.S. AI chip supplier, while demand for its processors remains strong. Huang has also argued that Nvidia's CUDA software ecosystem can keep older GPUs productive for longer. The company has another advantage. U.S. restrictions have limited access to leading Chinese AI chips, including Huawei Technologies' Ascend processors. BofA Sees Nvidia Earnings Beat and 56% Upside Nvidia is scheduled to release its second-quarter results on Aug. 26. In a note published Monday, Bank of America analyst Vivek Arya maintained Nvidia as a "top pick" and reiterated a $350 price target, representing a 56.3% upside from the stock's $223.96 price at the time. BofA forecasts Nvidia's quarterly revenue at $94 billion to $95 billion, about $3 billion to $4 billion above the company's $91 billion guidance. The bank also expects third-quarter revenue guidance of $107 billion to $108 billion, ahead of the roughly $104 billion consensus estimate. Price Action: Nvidia closed at $217.50 on Tuesday, down 0.02%, while the stock rose 0.67% to $218.96 in Wednesday's premarket trading, according to Benzinga Pro. According to Benzinga Edge Rankings, Nvidia ranks in the 99th percentile for growth and maintains positive short-, medium-, and long-term price trend ratings. Benzinga's screener lets investors compare Nvidia's performance against its industry peers. Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Photo courtesy: jamesonwu1972 / Shutterstock.com Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

[52]

New York Post

Nvidia partners with major Wall Street players to raise $500B for AI infrastructure

Nvidia said on Monday it has partnered with six major financial institutions to launch compute financing platforms aimed at raising over $500 billion in third-party capital for AI infrastructure. Nvidia CEO Jensen Huang said on X that the company has the option to backstop up to $125 billion, or 25% of the potential deals. The move highlights how surging demand for AI computing capacity is drawing institutional investors, as governments, companies and startups race to build out data centers to support AI workloads. Big Tech companies have signaled that spending on AI would not slow down, with combined outlays set to surpass $730 billion this year. Nvidia signed memorandums of understanding with Apollo APO.N, BlackRock BLK.N, Blackstone BX.N, Brookfield BAM.N, Goldman Sachs GS.N and KKR KKR.N for the financing platforms. The initiative is intended to broaden access to Nvidia-based infrastructure among frontier AI developers, enterprises, governments and cloud providers, while creating longer-duration, usage-linked investment opportunities for large asset managers and private capital firms. "These financing platforms will help customers access scarce compute at scale and build the AI factories that will power every industry and country in the age of AI," Huang said. Nvidia said the arrangements would "create dedicated pools of capital at significant scale at attractive rates" for its customers. The company did not disclose the financial terms, investment commitments by individual firms or a timetable for deploying the planned $500 billion. The Financial Times had reported the development first on Monday, later confirmed by Reuters.

[53]

BNN

Nvidia, Wall Street firms partner on US$500 billion AI financing venture, source says

A group of financial firms, including Apollo Global and Blackstone, is working with Nvidia to put together a US$500 billion funding package for AI infrastructure development, a person familiar with the matter told Reuters on Monday. Nvidia's shares fell over 3 per cent in afternoon trading. The tie-up highlights Nvidia's efforts to raise capital for the chips, power generation and data centers underpinning the AI boom. Big Tech companies have signaled that spending on AI would not slow down, with combined outlays set to surpass US$730 billion this year. The group, which also includes BlackRock's Global Infrastructure Partners, Brookfield Asset Management BAM.N, Goldman Sachs and KKR, is in talks to partner with Nvidia on the AI build-out, according to the Financial Times, which reported the development first. BlackRock and KKR declined to comment when contacted by Reuters, while Nvidia and the other companies did not immediately respond to requests. Nvidia said in June it would raise US$25 billion through a U.S. bond issuance, as it taps the debt market to increase liquidity for the first time since 2021. (Reporting by Isla Binnie in New York and Juby Babu in Mexico City; Editing by Jonathan Ananda and Shinjini Ganguli)

[54]

Morgan Stanley sees AI financing as defining summer 2026 By Investing.com

Investing.com -- Morgan Stanley analysts said summer 2026 may be remembered for major developments in AI financing rather than new technology releases, as capital markets rapidly adapted to fund the AI infrastructure buildout. The four largest hyperscalers, Microsoft (NASDAQ:MSFT), Alphabet (NASDAQ:GOOGL), Amazon (NASDAQ:AMZN), and Meta (NASDAQ:META), are expected to increase total capital expenditures by 57% in 2027 compared to 2026, according to Morgan Stanley equity research estimates. The spending plans reflect growing belief that these investments can generate returns on invested capital of at least 25%. The gap between capital deployment and revenue generation continues to pressure near-term cash generation. Morgan Stanley analysts' 2027 free cash flow estimates for the four hyperscalers have moved lower, creating a widening financing gap that suggests AI-related credit issuance will need to increase before cash flows catch up. Credit spreads for hyperscalers widened notably during the summer, reaching roughly 35 basis points wider for higher-quality issuers and about 50 basis points wider for lower-rated names at one point, before rallying sharply in the last two weeks. Spread widening was most pronounced in higher-quality unsecured bonds, where issuance volumes increased sharply. Data center asset-backed securities and commercial mortgage-backed securities saw more modest spread widening, backed by operating assets with established contractual cash flows. The major hyperscalers, with average ratings of roughly AA, have substantial financing needs combined with significant ratings flexibility. Morgan Stanley analysts said these issuers, including semiconductor companies such as Nvidia (NASDAQ:NVDA) and Broadcom (NASDAQ:AVGO), are relatively insensitive to modest changes in borrowing costs given their return expectations. Lower-rated issuers such as Oracle (NYSE:ORCL), rated mid to low BBB across agencies, and data center developers have less balance-sheet flexibility and lower tolerance for higher funding costs. The next phase of AI financing is expected to shift toward compute equipment, particularly servers and chips, as well as energy assets. Recent developments include Nvidia's announced compute infrastructure financing platform and a $35 billion chip financing transaction backed by Broadcom. Morgan Stanley expects high-quality issuers to increasingly provide backstops, credit support arrangements, and residual value guarantees to help private capital finance larger pools of AI infrastructure assets. This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.

[55]

PYMNTS

Nvidia Forms Financial Partnerships to Fuel AI Factory Boom | PYMNTS.com

The firms with which the AI chip manufacturer has announced these strategic partnerships are Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR. The partnerships remain subject to the execution of final agreements, according to the release. The compute financing platforms will be established at global scale, and the partnerships will see Nvidia work with the firms to create dedicated pools of capital at scale at attractive rates for Nvidia customers, the release said. Nvidia Founder and CEO Jensen Huang said in the release that AI factories are "a new class of productive, investable architecture," that in AI, "compute is revenue" and that Nvidia compute is suited for this role because it is broadly adopted, flexible, fungible and transferable. "That is why we are bringing the world's leading long-term capital providers together to independently underwrite AI infrastructure," Huang said. "These financing platforms will help customers access scare compute at scale and build the DSX AI factories that will power every industry and country in the age of AI." Huang said during a May earnings call that AI infrastructure spending could reach $3 trillion to $4 trillionannually by the end of the decade. Hyperscaler capital expenditure on AI alone is forecast to exceed $1 trillionin 2027. "Compute is revenues. Compute is profit," Huang said during the call. Nvidia said in its State of AI reports released in March that AI is delivering measurable financial gains for businesses. The reports found that 88% of organizations said AI has increased their annual revenue, while 87% reported cost reductions. It was reported in July that the five companies spending the most on AI data centers in the United States doubled their debt load over the past five years to finance their efforts. In total, Alphabet, Amazon, Meta, Microsoft and Oracle added about $350 billion to their debt obligations. It was reported Wednesday (Aug. 5) that Apollo named a new leader to head AI-related deals as part of a larger strategy to capture more digital infrastructure deals.

[56]

Forget gold and stocks: Nvidia CEO Jensen Huang aims to make chips an investable asset, lines up $500 bn in financing

Nvidia CEO Jensen Huang said AI compute is emerging as a new investable asset class as the chipmaker partners with six major financial firms to establish financing platforms. The initiative aims to mobilise over $500 billion in third-party capital for AI infrastructure, as Nvidia seeks to position compute capacity as productive, long-term infrastructure. While gold, real estate and stocks are common investment choices, Nvidia CEO Jensen Huang wants investors to ride on the AI bandwagon and turn chips into Wall Street's newest asset class, partnering with six large asset managers on a $500 billion financing push. Nvidia on Monday announced that it had signed memorandums of understanding with Blackstone, BlackRock, Goldman Sachs and others to build financing platforms for the company's customers. US MarketsPowered By As on 11 Aug 2026, 01:30 AM IST S&P 500 Top Gainers Datadog260.78(11.48%) APA41.02(9.01%) Marathon Petroleum320.32(7.42%) Akamai Technologies117.65(6.43%) Gainers" S&P 500 Top Losers Coterra Energy32.56(-8.62%) Verisk Analytics181.18(-5.55%) Corning157.76(-4.78%) Southwest Airlines44.90(-4.57%) Losers" "This is really the first time that technology chips have become an investable asset class...These are revenue-generating assets now. They're productive, they are long-lived, they are fungible, they are flexible," Nvidia founder and CEO Jensen Huang told CNBC. The company aims to mobilise more than $500 billion of third-party capital for the buildout of AI infrastructure over time. "We began by building chips; today, we are helping create a new class of productive, investable infrastructure: AI factories," Huang said in a press release. He noted that compute is revenue in the case of artificial intelligence, and Nvidia is uniquely suited for this. "That is why we are bringing the world's leading long-term capital providers together to independently underwrite AI infrastructure. These financing platforms will help customers access scarce compute at scale and build the DSX AI factories that will power every industry and country in the age of AI," he further said. Also read | Elon Musk vs Michael Burry: World's richest man says AI internet traffic will outpace humans, market expert asks who is paying GPUs historically have been seen as rapidly depreciating hardware. Nvidia's latest efforts challenge that assumption, transforming AI compute capacity into long-term, bankable infrastructure. "Fundamentally, what's different about this industry and this way of doing computing is that the computer is now part of the infrastructure, like electricity, like the internet, and so you have to think about it like it's infrastructure," Huang said during his interview with CNBC. The AI buildout will require unprecedented investment and a skilled workforce to turn that investment into the infrastructure that will help power future growth, said Larry Fink, Chairman and CEO of BlackRock. KKR Co-CEOs Joe Bae and Scott Nuttall meanwhile said that compute has become a critical infrastructure asset. "As we have scaled our approach to digital infrastructure, we have learned that delivery, not ambition, is the hard part," they added. Nvidia's push to make chips an investable asset comes amid the topsy-turvy AI trade seen this year so far. While hyperscalers pour in billions of dollars into AI infrastructure, analysts question if such massive investments will actually bear fruit in future. Also read | AI frenzy spooks investors, but JPMorgan CEO Jamie Dimon says spending boom likely to pay off. Here's why (With inputs from agencies) (Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of The Economic Times)

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Why Is NVIDIA Stock Gaining Tuesday? - NVIDIA (NASDAQ:NVDA)

NVIDIA's Jensen Huang Says AI Isn't Just Tech Anymore -- It's Infrastructure, and Wall Street Is Financing It The world's most valuable chipmaker is seeking to turn AI infrastructure into a major financing opportunity as CEO Jensen Huang increasingly frames NVIDIA chips as long-lived, revenue-producing assets. NVIDIA Taps Wall Street For AI Financing The effort aims to unlock more than $500 billion for AI infrastructure and help hyperscalers, AI labs and enterprises fund data centers and NVIDIA hardware through institutional credit, insurance capital and private investment. Huang Sees AI Chips As Infrastructure Huang told CNBC that technology chips have become an investable asset class because they now generate revenue and can serve multiple customers and workloads. He said AI computing has become part of core infrastructure, comparable to electricity or the internet, which means investors should view the industry through an infrastructure lens. Goldman Sachs Backs NVIDIA Financing Push Goldman Sachs CEO David Solomon said the bank has strong confidence in the long-term opportunity surrounding NVIDIA and the massive capital requirements needed to support the buildout of artificial intelligence infrastructure. "We have a deep belief in the opportunity set that's ahead," Solomon told CNBC on Monday. He said Goldman Sachs can bring both capital and its distribution network to help connect investors with companies funding AI infrastructure. Solomon said Huang approached Goldman Sachs with the financing concept. He added that the bank sees significant opportunities over the next three, five, seven and 10 years as companies invest heavily in computing infrastructure. "It's a big infrastructure build," Solomon said, adding that capital markets are signaling ample investor appetite to finance the expansion. NVIDIA Looks To Third-Party Capital Huang said the initiative would rely on third-party, independent, long-term capital rather than NVIDIA's own money. "This is all third-party, independent, long-term capital that all of my partners present will help us bring together," Huang said. Huang described the financing need as part of a broader shift in computing, with AI increasingly viewed as essential infrastructure rather than simply a technology investment. "It used to be, you know, tech, and now it's infrastructure," Huang said. Price Action NVDA Stock Price Activity: NVIDIA shares were up 1.10% at $219.95 during premarket trading on Tuesday, according to Benzinga Pro data. Image via Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

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New AI financing backstops allows compute buyers more control over business models By Investing.com

Investing.com -- Artificial intelligence infrastructure financing backstops announced by Nvidia and Broadcom recently have allowed major buyers of AI compute to take more control of their business models, according to Barclays. Nvidia this week unveiled a mega $500 billion in third-party capital for AI infrastructure, teaming up with some of the biggest players in global finance: Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR. Meanwhile, Broadcom in June established a $35 billion compute financing platform with Apollo and Blackstone. Barclays analysts Ross Sandler and Tom O'Malley earlier this week noted that so far, AI capital expenditures had largely been borne by the so-called hyperscalers, to the tune of $1.5 trillion since 2023. "The hyperscaler industry has natural limits around debt levels and power agreements, and we seem to be approaching those limits in 2027. This has opened the door to new structures whereby the largest buyers of compute can build infrastructure outside of the hyperscaler's walls, in small chunks, via the new financing structures backstopped by NVDA/AVGO," the analysts said. "We estimate that the new 'backstopped' capex could reach 20%+ of industry capex next year and up to half of industry capex in 2028," they added. The brokerage believes this new structure could address many current issues across the AI space, including limits around how much capex hyperscalers can post and deeper levels of control over compute for AI labs that if not possible within cloud service agreements. "The basic structure of this new approach separates the datacenter (long dated assets, often 25-30 year useful life) from the compute (shorter dated assets) with two financing vehicles," Barclays said. "Datacenters have been around for decades and have a fairly standardized approach to financing construction and operations. Compute is the more expensive and potentially riskier portion of the AI buildout, and is what these new special-purpose-vehicle (SPV) structures are intended to solve," the analysts said. "Compute assets depreciate more quickly, have higher obsolescence risk, and are the largest percentage of the AI datacenter's capex," they added.

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Nvidia teams up with Wall Street asset managers on $500 billion AI infrastructure push

Nvidia is working with some of Wall Street's largest asset management firms on a $500 billion effort to finance artificial intelligence infrastructure, a person familiar with the matter told CNBC Monday. The chipmaker has enlisted Apollo Global Management, Blackstone, BlackRock's Global Infrastructure Partners unit, Brookfield Asset Management, Goldman Sachs and KKR to assemble the capital package, according to the person, who spoke on the condition of anonymity because they were not authorized to speak publicly. An announcement could be made as soon as Monday, the person said. The Financial Times first reported the deal. The move highlights the growing role of private capital in financing the costs of the artificial intelligence boom. For Nvidia, the effort could help its biggest customers secure the financing needed to buy its high-end GPUs, build power-hungry data centers and lock in long-term electricity capacity. Alternative asset managers have been eager to deploy capital into digital infrastructure, tapping institutional and insurance capital to finance projects. Apollo and Blackstone, among others, have already structured debt and equity financing for companies including Anthropic as AI companies deal with large capital expenditure requirements. Representatives for Nvidia, Apollo, Blackstone, Brookfield, BlackRock, Goldman Sachs and KKR did not immediately respond to requests for comment. This story is developing. Please check back for updates.

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Nvidia partners with Wall Street giants to raise $500 billion for AI buildout

In an ambitious collaboration, Nvidia is joining forces with six prominent financial institutions to establish compute financing platforms with the goal of unlocking upwards of $500 billion in third-party investment for AI infrastructure. Nvidia said on Monday it has partnered with six major financial institutions to launch compute financing platforms aimed at raising over $500 billion in third-party capital for AI infrastructure. Nvidia CEO Jensen Huang said on X that the company has the option to ⁠backstop up ⁠to $125 billion, or 25% of the poential deals. US MarketsPowered By As on 11 Aug 2026, 01:30 AM IST S&P 500 Top Gainers Datadog260.78(11.48%) APA41.02(9.01%) Marathon Petroleum320.32(7.42%) Akamai Technologies117.65(6.43%) Gainers" S&P 500 Top Losers Coterra Energy32.56(-8.62%) Verisk Analytics181.18(-5.55%) Corning157.76(-4.78%) Southwest Airlines44.90(-4.57%) Losers" The move highlights how surging demand for AI computing capacity is drawing institutional investors, as governments, companies and startups race to build out data centers to support AI workloads. Big Tech companies have signaled that spending on AI would not slow down, with combined ⁠outlays set to surpass $730 billion this year. Nvidia signed memorandums of understanding with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and ⁠KKR for the financing platforms. The initiative is intended to broaden access to Nvidia-based infrastructure among frontier AI developers, enterprises, governments and cloud providers, while creating longer-duration, usage-linked investment opportunities for large asset managers and private capital firms. "These financing platforms will help customers access scarce compute at scale and build the AI factories that will power every industry and country in the age of AI," Huang said. Nvidia said the arrangements would "create dedicated pools of capital at significant ⁠scale at attractive rates" for its customers. The company did not disclose the financial terms, investment commitments by individual firms or a timetable for deploying the planned $500 billion. The Financial Times had reported the development first on Monday, later confirmed by Reuters.

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Market Screener

Why Nvidia and Wall Street are lining up half a trillion dollars

STORY: :: What's behind Nvidia's $500 billion for AI infrastructure push? :: San Francisco, California / August 11, 2026 :: Max Cherney, Reuters Tech Correspondent "So $500 billion is an enormous amount of money for the company." // "Nvidia signed a deal for a $500 billion financing project with six financial institutions -- aimed at letting its customers access scarce capital at scale and build the AI data centers that power models like Anthropic and OpenAI's ChatGPT." // "For Nvidia, $500 billion is a large amount of money, but to put it in a little bit of context, the company is expected to generate roughly $320 billion in its data center segment for all of its fiscal 2027. "Nvidia's agreement to have the option to backstop up to $125 billion of the $500 billion or roughly 25% of each deal. In plain language, Nvidia is helping finance the purchase of its own products. "There are concerns about circular financing // that Nvidia is financially aiding its customers to buy its own products. "Jensen Huang, Nvidia's CEO, addressed this question directly on X yesterday. He said that specifically, this $500 billion initiative is designed to address the concern. And he said that they're bringing independent long-term institutional capital to the infrastructure market. // Huang also said the demand is real, it comes from AI labs like Anthropic and OpenAI, AI startups, big companies, cloud computing companies, and countries that are all building AI services. The capital providers, he says, independently underwrite each project // and Nvidia essentially provides the platform. :: Nvidia Handout "So this $500 billion is a memorandum of understanding, meaning it's an agreement to potentially do some work in the future. So when Nvidia or its customers announce deals [...] investors and others will want to pay attention closely to what those deals are, how much money they're for, what the terms are, and so on."' Nvidia CEO Jensen Huang said on X that the company has the option to backstop up to $125 billion, or 25% of the poential deals. The move highlights how surging demand for AI computing capacity is drawing institutional investors, as governments, companies and startups race to build out data centers to support AI workloads. Big Tech companies have signaled that spending on AI would not slow down, with combined outlays set to surpass $730 billion this year. Nvidia signed memorandums of understanding with Apollo APO.N, BlackRock BLK.N, Blackstone BX.N, Brookfield BAM.N, Goldman Sachs GS.N and KKR KKR.N for the financing platforms. The initiative is intended to broaden access to Nvidia-based infrastructure among frontier AI developers, enterprises, governments and cloud providers, while creating longer-duration, usage-linked investment opportunities for large asset managers and private capital firms.

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Nvidia's neocloud funding could drive significant revenue stream - Morgan Stanley By Investing.com

Investing.com -- Nvidia this week grabbed the spotlight in the artificial intelligence space after unveiling a mega $500 billion in third-party capital for AI infrastructure, teaming up with some of the biggest players in global finance: Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR. The financing announcement drew varied reactions on Wall Street, from Michael Burry calling it a "stunt" to some analysts expressing concerns over the circular nature of AI deals. Nvidia itself said the move would allow compute to be treated as an investable asset. "Nvidia backstopping neo-cloud investment in exchange for revenue sharing is likely to further polarize the stock. We are definitively on the optimistic side, seeing a large annuity potential with limited downside," Morgan Stanley said on Friday. Analysts led by Joseph Moore said Nvidia remained their top pick in semiconductors and that they were enthusiastic about the new initiative. "We believe that the compute demand is there to support this - and that the demand would be underserved if not for this initiative," they said. "Adding annuity revenue streams through minority stakes in a wide variety of cloud service providers should add to the predictability of the longer term earnings power, in a way that limits downside," the analysts noted. "Broadening out of spending should keep NVIDIA as the defacto standard, especially heading into a major Vera Rubin product cycle," they added. The brokerage's tech teams estimated that the four biggest so-called U.S. hyperscalers will bring on about 25 gigawatts of compute in 2027 excluding Tensor Processing Unit. A neocloud ecosystem of a similar size monetizing at $20 million per megawatt would generate $500 billion of annual revenue, they estimated. "If Nvidia captured 1/4th of that as 100% margin revenue, it would drive 60% upside to our FY28 EBIT estimates, or 25% upside to FY29 without any change to Nvidia's initial sales. But at smaller scale (2-5GW) we could start to see ~10% or so uplift to EPS," the analysts said.

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Market Screener

Nvidia and Wall Street prepare $500bn financing plan for AI

The initiative is meant to marshal the capital needed to finance chips, data centers and power-generation capacity that are essential to AI's expansion. It comes as technology giants continue to accelerate investment in the field, with combined spending expected to top $730bn this year. The project remains at the discussion stage, and its precise terms have not been disclosed. Nvidia had already stepped up its funding strategy by announcing in June a $25bn bond sale in the United States, marking its return to the debt market to boost liquidity for the first time since 2021.

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Nvidia Just Turned Its Chips Into a Mortgage Market

Nvidia (NASDAQ:NVDA), the world's most valuable company, has done something genuinely new. It has partnered with a group of major financial institutions to mobilise more than $500 billion in third-party capital for AI infrastructure, treating computing power the way lenders have traditionally treated commercial real estate or toll roads. Nvidia CEO Jensen Huang has called this the first time technology chips have become an investable asset class. What Nvidia has done here is elegant, and that is exactly what worries me. Chips have never been treated as a bankable, long-duration asset before, because chips depreciate fast and lose value the moment a newer generation arrives. Turning that into something institutions can lend against, the way they lend against a building or a highway, only works if the underlying asset actually holds its value over time. This is no longer simply Nvidia selling chips. It is Nvidia helping its own customers borrow enormous sums to buy those chips, then helping structure the financing that makes the borrowing possible in the first place. When the seller starts underwriting the buyer's debt, at this scale, it is worth watching closely. Hyperscalers have already borrowed roughly $250 billion this year alone, several times their normal annual borrowing. Layering another $500 billion in financing on top of that is a genuinely large amount of leverage building on leverage, all resting on the assumption that AI infrastructure keeps generating returns fast enough to justify the debt. I keep thinking about the years leading into the 2008 financial crisis. Loans were packaged, leveraged, and sold on the assumption that the underlying asset would hold or increase in value. When that assumption failed, the leverage amplified the losses rather than the gains. This is a different asset and a different market, but the underlying structure, borrowing heavily against something whose future value is genuinely uncertain, deserves the same scrutiny. None of this means it fails. If AI adoption keeps accelerating and these data centres keep generating the revenue Nvidia expects, this financing structure could work exactly as intended, and some companies stand to make very large profits from it. Huang's argument that compute is now infrastructure, similar to electricity or the internet, is not unreasonable on its face. The risk sits entirely on the uncertainty. GPUs have historically been viewed as rapidly depreciating hardware, and newer chip generations arrive on a fast cycle. Borrowing long-term against an asset with a genuinely uncertain shelf life is a real gamble, even when the borrowing is dressed up in the language of infrastructure investment. This is why investors need to be genuinely careful right now about where their money sits within the AI trade. There is a real difference between owning the infrastructure and technology generating durable returns, and owning exposure to the debt piled on top of assets that may or may not hold their value as long as everyone is currently assuming. Talk to a financial advisor, understand exactly what you are exposed to, and do not assume every part of this trade carries the same risk simply because the numbers involved are enormous.

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Nvidia's $500 Billion AI Push Is Starting to Show Up in Credit

The chipmaker is working with some of Wall Street's largest financial groups on a framework that could mobilize more than $500 billion for AI infrastructure. Apollo, Blackstone, BlackRock, Brookfield, Goldman Sachs and KKR are all involved, with dedicated pools of capital expected to support data centres, power generation, AI clouds and the wider Nvidia ecosystem. Takeaways * Nvidia is working with major Wall Street firms on a financing framework that could mobilise more than $500 billion for AI infrastructure. * The AI buildout is increasingly being funded through debt, private credit, project finance and structured capital alongside traditional equity funding. * Bloomberg Markets Live notes Nvidia five year CDS widened toward 77.5 bp even as broader investment grade spreads remain relatively contained. * The move is not a distress signal, but it suggests credit markets are beginning to price the sheer scale of AI financing. * AI remains a powerful growth story, but funding costs are becoming a more important part of the trade. Nvidia's $500 Billion Credit Market Effect The AI buildout has always required enormous amounts of capital, but Nvidia's (NASDAQ:NVDA) latest move gives the scale of that financing challenge a much sharper outline. The chipmaker is working with some of Wall Street's largest financial groups on a framework that could mobilize more than $500 billion for AI infrastructure. Apollo, Blackstone, BlackRock, Brookfield, Goldman Sachs and KKR are all involved, with dedicated pools of capital expected to support data centres, power generation, AI clouds and the wider Nvidia ecosystem. That is a very large number even by AI standards. For the past few years, the market has mostly treated the AI boom as an earnings and capex story. Demand for GPUs surged, hyperscalers kept lifting spending plans and Nvidia sat at the centre of the whole cycle. Now the financing side is becoming harder to ignore. The sheer cost of building out AI infrastructure means technology companies are increasingly tapping every available source of capital. Public equity, investment-grade bonds, high-yield debt, private credit, securitized structures and project finance are all becoming part of the mix. Nvidia itself is taking a larger role in helping customers secure the capital needed to build infrastructure around its chips. That keeps the ecosystem moving, but it also introduces a new market question. How expensive does the AI buildout become as more leverage and structured financing enters the system? The circularity argument has already been around for some time. Nvidia helps support financing across the ecosystem, customers raise capital to buy infrastructure and chips, and that spending feeds directly back into Nvidia's own revenue stream. As long as capital remains readily available, that is a powerful growth engine. But credit markets are starting to register the scale. Bloomberg Markets Live strategist Brendan Fagan highlighted that Nvidia's $500 billion financing push is increasingly turning the AI buildout into a credit story, with spreads beginning to widen even while broader investment-grade credit remains relatively calm. Nvidia CDS widened to roughly 77.5 basis points on Monday. Chart 1 -- Nvidia Five-Year CDS That is not a distress signal. But it is a useful marker. Credit investors are beginning to demand more compensation as the AI ecosystem layers on more debt, structured financing and increasingly large capital commitments. Oracle remains the more obvious example of how aggressive AI investment can pressure credit, but Nvidia spreads moving wider suggest the market is at least beginning to ask similar questions around the broader financing model. Chart 2 -- AI Credit Spreads This does not mean the AI boom is running out of road. It means the market now has another variable to watch. The equity side of the story still depends on earnings, demand and hyperscaler spending. But as the size of the infrastructure buildout moves deeper into the hundreds of billions and eventually trillions, the cost of funding that expansion becomes increasingly important. For Asia, that leaves semiconductor-heavy markets with another angle to digest. The AI boom is still creating enormous demand for chips and infrastructure. But increasingly, investors also need to ask what price the capital comes at. The Financing Package Itself Is Substantial. Nvidia has signed memorandums of understanding with Apollo, Blackstone, BlackRock, Brookfield Asset Management, Goldman Sachs and KKR aimed at mobilizing more than $500 billion of third-party capital for AI infrastructure over time. The capital is expected to support projects across Nvidia's ecosystem, including data centres, power generation, AI clouds, frontier AI labs and enterprise infrastructure. The broader significance is that the AI buildout is now reaching a scale where even the largest technology companies cannot rely on conventional corporate funding alone. The sector is increasingly drawing on investment-grade bonds, high-yield debt, securitized financing, private credit and project finance to keep spending moving. Nvidia has also become more active in helping customers and partners secure financing for infrastructure that ultimately supports demand for its own chips. That includes backing projects, helping structure capital and building deeper relationships with private capital firms that are preparing to deploy very large sums into AI infrastructure. The scale is already enormous. Morgan Stanley estimates the major hyperscalers could spend around $3.5 trillion between 2026 and 2028, while Apollo has suggested total AI infrastructure investment could eventually exceed $8 trillion. That explains why Wall Street's largest alternative asset managers are moving so aggressively into the space. For Nvidia, the financing partnership effectively expands the pool of capital available to customers that want to build AI infrastructure but may not want the entire cost sitting directly on their own balance sheets. It also shows how the AI boom is evolving. The first phase was dominated by chip demand and hyperscaler capex. The next phase increasingly depends on whether global capital markets can finance the physical infrastructure required to keep that expansion going.

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