Key Takeaways
CoreWeave’s debt-fueled growth highlights a broader trend in the AI infrastructure boom, where heavy leverage, hardware-collateralized lending, and risky financing structures create systemic vulnerabilities
Smaller developers are particularly exposed, in our view, as long-term projects often rely on contingent funding and tenant agreements, leaving them at risk of financial collapse if delays or shortfalls occur
Across the AI ecosystem, the rapid expansion of data centers and hardware investment is testing the limits of traditional financing strategies, raising concerns about financial sustainability
The explosive growth of AI infrastructure and the US data center buildout—driven by massive debt issuance from both tech giants and startups—signals a glaring risk of financial instability reminiscent of past speculative bubbles, in our opinion. At the core of this debt-fueled expansion lies a critical question: Can the AI boom sustain itself without triggering a financial reckoning?
THE DEBT ICEBERG
Debt issuance for data centers surged to $183B in 2025, up from $92B the previous year, according to S&P Global.1 Hyperscalers and massive cloud service providers, such as Oracle and Microsoft, drove a lot of this borrowing, aggressively loading up the ecosystem with debt. While much of the debt has been issued in the corporate bond market, off-balance sheet transactions have also surfaced, which have historically been late-cycle signals. Alternative managers such as Blue Owl Capital Inc., and Blackstone Inc., have established multi-billion-dollar funds dedicated to investing in data centers, supplemented by billions more flowing through major banks. Morgan Stanley projects a $1.5T financing gap for global data center construction and AI infrastructure through 2028, which is expected to be funded by various credit markets, with private credit expected to cover over half of this staggering amount.2
Data Center Debt Issuance
Early signs of stress in the debt-fueled AI data center buildout are already emerging wherever public disclosure is available, in our view. Credit default swap (CDS) spreads, which measure the cost of insuring against credit risk, have generally risen for all hyperscalers. Spreads for Oracle, for instance, tripled over their five-year average, as the company’s total outstanding debt surged 40% year-over-year to $124B. Yet these measures, in our view, only scratch the surface of the risks involved. Meta, for example, financed a $27B data center in Louisiana through a special purpose vehicle (SPV) with notably higher interest rates, effectively masking the consequences of increased leverage from its own balance sheet.3
As we progress through 2026, big tech companies continue to face little difficulty in raising billions to fund their ambitious AI expansion plans. Just last month, Alphabet Inc., Google’s parent company, successfully secured over $30B in under 24 hours across multiple currencies—marking one of the largest and fastest corporate bond sales in history.
However, signs of strain are beginning to emerge in other areas. Blue Owl Capital, a key financier of data centers and currently managing over $305B in assets, is reportedly grappling with liquidity challenges. As some of its non-traded, retail-facing vehicles have faced redemption amidst tech sector selloffs, concerns have begun to spread in the private credit market about the ability of private lenders to keep funding AI infrastructure. These challenges have contributed to a wave of data center cancellations and refinancing struggles, further exacerbating the already tight financing conditions.
NEOCLOUDS, A FRAGILE UNDERBELLY
Despite the significant debt burden carried by major players like Alphabet and Oracle, this is far from where we think the true risks lie. More recently, big tech companies have increasingly shifted risks onto so-called neoclouds by signing short-term leases on data centers, leaving neoclouds to bear the burden of long-term debt and infrastructure development. According to S&P Global 451 Research, non-hyperscaler firms are responsible for 64% of the 647 data centers slated for completion by the end of 2027. As a result, neoclouds’ business models hinge on explosive growth in demand for AI compute from only a handful of clients such as Anthropic, Meta, or OpenAI, in our view. If AI progress stalls, neoclouds could face significant default risks, potentially triggering ripple effects throughout the financial system.
A closer look at neoclouds’ debt levels reveals a darker reality, potentially exposing a fragile underbelly of the AI ecosystem. In just a few years, six key players—mostly new companies with little credit history—have amassed over $32B in debt, ramping up leverage at a time when venture capital fundraising remains near decade lows.4 For example, Amsterdam-based Nebius Group’s debt more than tripled over the past two years, reaching $4.6B. Similarly, Dallas-based AI data center builder Applied Digital Corporation also saw its debt skyrocket from $36M to $700M during the same period. While these numbers may seem small in isolation, we believe they represent only the tip of the iceberg.
Estimated Financing Breakdown for Total CapEx (USD), 2025-2028
Data centers require significant upfront cash outlays for electrical equipment, land acquisitions, and power-related commitments. Meanwhile, revenue is backloaded and dependent on factors like delivery schedules, tenant ramp-up, and pricing which can weaken if capacity floods the market all at once. In practice, this “bridge” can collapse before revenue flows in, whether due to project delays or the failure of customer funding to materialize as expected. And even the financing that is supposed to bridge that ramp can prove optional: Fermi, a smaller data center developer, disclosed in December that a prospective anchor tenant (later reported to be Amazon) terminated an agreement that would have advanced up to $150M for its West Texas AI campus, leading the stock to drop by more than a third on the news.5 That gap between front-loaded commitments and conditional tenant funding with backloaded revenue is where we see how “growth CapEx” can quietly mutate into a potential solvency problem. A single delay cycle, rate reset, or demand wobble can trigger covenant pressure, expensive amendments, or project cancellations altogether. A class action lawsuit was recently filed against Fermi by investors accusing Fermi of misleading the market about tenant demand.
Most importantly, examples like Fermi underscore that the boom’s most fragile leverage is concentrated in the least resilient part of the ecosystem: smaller builders with limited liquidity buffers and highly binary project outcomes. If this cycle turns, we believe the first visible fractures are unlikely to surface in the hyperscalers’ financial statements; they are more likely to show up in developers whose capital structures are predicated on everything proceeding perfectly—on time, on budget, and at scale.
COREWEAVE: “THE WORST BALANCE SHEET”
Perhaps the most striking example of this debt-fueled growth is CoreWeave Inc., an eight-year-old neocloud provider whose rapid rise has been built almost entirely on aggressive debt financing. Among its peers, CoreWeave stands out for having the highest debt level and the lowest coverage ratio, raising serious questions about its long-term viability, in our opinion. CoreWeave’s story is a useful lens on the broader AI infrastructure sector, where promises of innovation increasingly risk being overshadowed by the mounting burden of unsustainable debt.
With over 300,000 advanced Nvidia GPUs across 43 data centers, CoreWeave has rapidly scaled to become a critical enabler of AI startups and enterprises, supporting their training and inferencing workloads.6 Yet this growth model raises concerns about durability: interest rate shifts, potential slower adoption of AI applications, or broader economic downturns that could make debt servicing untenable, leaving companies like CoreWeave teetering on the brink of financial distress.
CoreWeave’s balance sheet appears to reflect these vulnerabilities. By end-2025, the company was burdened by $21.4B in debt with interest rates exceeding 10%, funneling nearly all its revenue toward debt servicing. For the first half of 2025, CoreWeave spent $2B on debt payments while generating $2.2B in revenue during the period. This troubling pattern persisted into the second half, with the company reporting $5.1B in total revenue for 2025, nearly all consumed by debt obligations totaling $3.4B in principal payments and $1.2B in interest payments.7 CoreWeave reported a net loss of $452M for the fourth quarter of 2025 due to a surge in its interest payments to $388M.
Essentially, CoreWeave is handing over nearly all its revenues to creditors such as major Wall Street banks, hedge funds, and vendors, leaving its $1.3B in operating costs uncovered.8 In the technology sector, such high leverage is considered reckless, even in favorable economic conditions. “CoreWeave has one of the worst balance sheets I have ever seen—and I mean it,” said Gil Luria, head of technology research at D.A. Davidson, in an interview.9
Distribution of Total Debt/Equity Among Large-Cap US Tech
A FLURRY OF GPU-COLLATERALIZED LOANS
CoreWeave’s scale-up illustrates a familiar pattern across the entire AI data center ecosystem: With contracts in place to deliver high-performance computing, CoreWeave secures commitments from data center builders. Simultaneously, the company obtains funding from lenders to purchase the necessary hardware based on these commitments, often at double-digit interest rates and under stringent covenants. The company has signed multibillion-dollar agreements with OpenAI, Meta, and Microsoft, expanding its backlog to over $67B as of end of 2025.6 While this secures future revenue streams, it also demands exponential infrastructure expansion—dozens of additional data centers, hundreds of thousands of GPUs, and billions in upfront capital expenditures.
To fund its growth, CoreWeave primarily uses Delayed Draw Term Loan (DDTL) facilities, an asset-backed structure collateralized by GPUs, which Blackstone and Magnetar began utilizing specifically for lending to CoreWeave in 2023.10 These facilities allow gradual capital drawdowns while requiring repayment over subsequent years, and are secured by GPUs—assets that CoreWeave depreciates over six years, a timeline that does not align with our proprietary research and mentioned in our previous Dotcom on Steroids III. Lenders mitigate risks by adding restricted cash requirements and enforcing strict covenants.
Taking a closer look, we see that these loan facilities have imposed significant financial strain on CoreWeave. For example, CoreWeave’s $2.3B DDTL 1.0 facility from Blackstone and Magnetar, now fully utilized, carries a steep 15% interest rate and is expected to cost the company around $250M per quarter to service the loan until 2028.11 In July 2025, CoreWeave added a DDTL 3.0 facility, a 9% loan allowing up to $2.6B in borrowing, led by Morgan Stanley, MUFG, and Goldman Sachs, along with other major banks.11 Despite the smaller size, creditors mandated $100M in restricted cash for this tranche, double the $50M required for the preceding DDTL 2.0 facility, highlighting increased caution.11
Since 2023, CoreWeave has obtained a total of $15.5B via four DDTL facilities, with about 60% already being tapped.11 By contrast, the company’s GPU assets, classified as “technology equipment” on its balance sheet, were valued at $14.6B as of September 2025, the latest data available. We believe this mismatch underscores the central fragility in hardware-collateralized lending. If utilization or GPU pricing falls, or refresh cycles accelerate, collateral coverage and cash flow can erode quickly, potentially triggering expensive refinancing or abrupt cuts in capital expenditures. This is not a theoretical risk. As we have recently written, third-party trackers such as Silicon Data have documented meaningful declines in the rental prices for Nvidia’s advanced B200 GPUs.4
WALKING THE FINANCIAL TIGHTROPE
CoreWeave has pursued multiple funding channels, but each appears to introduce new constraints that mirror broader data center finance dynamics. After a lackluster IPO that raised $1.5B versus a $2.7B target, the company continued leaning on vendor and structured financing rather than meaningfully de-levering.12 Beyond the IPO proceeds, CoreWeave has relied heavily on leasing agreements with original equipment manufacturers (OEMs) like Dell to acquire GPU servers essential for its operations; these leases, typically lasting two to three years with interest rates of 8% to 10%, amounted to $2.7B as of October 2025.11
Nvidia also plays a direct financial role. In a notable turn of events, Nvidia stepped in as an anchor investor just before the IPO, committing $250M for a 6% equity stake in CoreWeave, and has pledged $6.3B in financing through a strategic partnership agreement. This arrangement allows CoreWeave to sell any unsold capacity through 2032 back to Nvidia, which we believe further increases its dependency on Nvidia’s ongoing support and on sustained demand for Nvidia-based compute.
CoreWeave is just one example of Nvidia’s outsized influence in the data center buildout. Data from S&P Global 451 Research showed that Nvidia was involved in dozens of data center financing deals worth tens of billions of dollars during the past three years. S&P’s tally showed that 458 data center deals were conducted from 2022 to 2025, bringing the total deal value to $191B. Importantly, we believe Nvidia does not have to contribute large amounts of capital in some deals; with its endorsement alone, other backers are more than willing to step in and finance the buildout. For instance, Voltage Park, a neocloud launched in late 2023 and an official Nvidia Cloud Partner, was funded by the Navigation Fund, a nonprofit backed by crypto billionaire Jed McCaleb.13 Similarly, Vultr, which became an Nvidia Elite Partner in 2023, later raised hundreds of millions of dollars from major banks including J.P. Morgan and Bank of America.14
In response to rising financing pressure, CoreWeave has recently amended the terms of its newly-established DDTL 3.0 facility, including easing liquidity requirements, postponing financial tests, and increasing flexibility in managing covenant breaches—a highly unusual move in the credit market. In January 2026, Nvidia stepped in again with a $2B investment, with CoreWeave pledging to acquire more GPUs from it. As a result, CoreWeave investors experienced dilution due to the issuance of new shares, which increased Nvidia’s stake in the company to 11%. More recently, CoreWeave is reported to be negotiating with a group of banks to borrow $8.5B in new debt financing, which will be backed by long-term contracts signed with Meta.15 With these adjustments in place, CoreWeave is giving itself more breathing room to delay the risk of triggering a default in the near term.16
Execution risk compounds the balance sheet risk
Construction delays have already impacted CoreWeave’s 2025 performance, leading to a downward revision in projected revenue in October by up to $200M.17 Yet the company plans to roll out 3.1 gigawatts of contracted capacity over the coming years, requiring tens of billions in additional spending, according to the company’s latest financial results, an expansion plan that depends on continued access to large-scale, affordable capital.6 However, a significant setback came in October with the collapse of CoreWeave’s proposed $9B all-stock acquisition of Core Scientific. Rejected by Core Scientific’s shareholders, the deal would have provided CoreWeave with vital strategic and financial benefits, including the elimination of $10B in lease liabilities, improved credit metrics, and access to critical power infrastructure for its AI cloud platform.18
Without this acquisition, CoreWeave’s ability to secure reliable resources and sustain its ambitious growth trajectory remains uncertain, in our view. Tellingly, CoreWeave insiders and early investors have sold more than $5B in stock since its March IPO, according to regulatory filings, marking one of the fastest exits in recent corporate history.
CoreWeave Insider Trades
Cumulative net open market transactions
CoreWeave’s story is not just its own. We think it epitomizes the debt frenzy fueling this AI boom—heavy leverage, hardware-collateralized lending, vendor financing, and SPVs that redistribute and obfuscate risk rather than eliminate it. In our view, the risks are more concentrated one layer down in the buildout ecosystem, where smaller developers are underwriting long-duration projects with funding and tenant agreements that often remain contingent well into the construction phase. As the recent Fermi episode showed, even “bridge” capital tied to an anchor tenant can evaporate quickly, forcing developers to scramble to fill a sudden and substantial funding gap.
Critically, that funding gap is being widened in real time by soaring input costs that were not fully baked into earlier projections, cost escalations that stand to meaningfully magnify the strain on an already fragile financing structure. Memory—a core input for every AI accelerator and server in these facilities—is seeing broad-based price escalation across HBM, DRAM, and NAND. The three dominant players, Micron, SK Hynix, and Samsung Electronics, are on pace to collectively generate over $500B in memory revenues in 2026 alone, a nearly 200% increase from 2025.19,20 Paired with Nvidia’s projected ~$330B in data center revenues, pricing power seems concentrated entirely upstream—while financial strain is borne, in our view, by the leveraged operators at the bottom.21 While the real-world impact of AI innovations remains to be seen, they are driving a race to secure resources and infrastructure on a scale that tests traditional financing strategies, leaving many firms highly leveraged, particularly those outside the hyperscalers. The question is no longer just whether lenders can fund the buildout, it is whether the cost structure of the buildout itself has become self-defeating.
Amidst the general fog of data center financing, there are multiple reports of projects that may not get sufficient attention because the numbers involved are simply too large to be digested, in our opinion. For example, New Era Energy & Digital, with a market cap of just $120M, had begun development of a 7-gigawatt AI data center in New Mexico which we believe could cost more than $100B.22 The debt involved would propel the tiny, profitless New Era into the same league as the largest corporate borrowers in the world. New Era’s CEO is currently under investigation for fraud by the New Mexico Attorney General.23
As we have highlighted over the past few months, we believe the parallels to past speculative bubbles are difficult to ignore with aggressive expansion driven by cheap capital, inflated valuations based on future promises, and a lack of focus on sustainable profitability. Burdened by heavy debt, tight liquidity, and little margin for error, highly levered AI data center builders and operators now face a critical decision: maintain a rapid pace of expansion or recalibrate in favor of financial sustainability. The choices made by data center builders, hyperscalers, neoclouds, and lenders in managing this delicate balance may shape not only their individual futures but also influence the direction and potential fragility of the broader AI ecosystem.
END NOTES
1Roach, April. “Data center deals hit record $61 billion in 2025 amid construction frenzy.” CNBC. 19 December 2025.
2How Credit Markets Could Finance AI’s Trillion Dollar Gap.” Morgan Stanley Research. 6 August 2025.
3Weil, Jonathan. “AI Meets Aggressive Accounting at Meta’s Gigantic New Data Center.” The Wall Street Journal. 24 November 2025.
4”Dotcom on Steroids: Part III.” GQG Partners. 18 December 2025.
5Nishant, Niket. ”Data center REIT Fermi drops 34% after potential customer backs out of funding deal”. Reuters. 12 December 2025.
6CoreWeave, Inc. 4Q2025 Earnings Presentation. 26 February 2026.
7CoreWeave, Inc. Form 8-K. 26 February 2026.
8”CoreWeave Reports Strong Third Quarter 2025 Results.” CoreWeave, Inc. 10 November 2025.
9Luria, Gil. ”CoreWeave Exposed: What Are You Actually Buying?” YouTube. 6 June 2025.
10CoreWeave, Inc. Form S-1 Registration Statement. 3 March 2025.
11CoreWeave, Inc. Form 10-Q. 30 September 2025.
12Coben, Craig. “CoreWeave’s IPO tested the waters — and missed the mark. Wishful thinking results in a faceplant.” The Financial Times. 30 March 2025.
13Wiggers, Kyle. “New nonprofit backed by crypto billionaire scores AI chips worth $500M.” Tech Crunch. 31 October 2023.
14Elshahawy, Eman. ”Big banks provide $329 million loan to South Florida tech company.” South Florida Business Journal. 24 June 2025.
15Lipschultz, Bailey and Seligson, Paula. “CoreWeave Seeks $8.5 Billion Loan From Banks Backed by Meta Deal.” Bloomberg. 24 February 2026.
16CoreWeave, Inc. Form 8-K. 31 December 2025.
17Whelan, Robbie. “CoreWeave’s Staggering Fall From Market Grace Highlights AI Bubble Fears.” The Wall Street Journal. 15 December 2025.
18”Investor Presentation: A Flawed Process, A Deficient Structure and an Inadequate Price.” Two Seas Capital. October 2025.
19Kim, Shawn. “South Korea Technology: Memory – Double Up.” Morgan Stanley Research. 30 January 2026.
20Moore, Joseph. “Micron Technology Inc.: Raising estimates amid continued supply shortages.” Morgan Stanley Research. 11 February 2026.
21Bloomberg consensus estimates. 28 February 2026.
22Skidmore, Zachary. ”New Era plans 7GW AI data center in Lea County, New Mexico, powered by gas and nuclear.” Data Center Dynamics. 7 November 2025.
23”Securities Fraud Investigation Into New Era Energy & Digital, Inc. (NUAI) Announced – Shareholders Who Lost Money Urged To Contact Glancy Prongay & Murray LLP, a Leading Securities Fraud Law Firm.” Business Wire. 30 December 2025.
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