Nvidia's market capitalization shrank by roughly $365 billion last week, as escalating borrowing costs fueled doubts about the durability of Wall Street's artificial intelligence spending spree. The chipmaker's shares declined 6.6% over the five trading sessions ending October 16, closing at $214.13. The broader Philadelphia Semiconductor Index fell 11.4%, reflecting deepening unease across the sector.
Demand for Nvidia's processors remains robust. The central concern is whether companies constructing the data centers that house these chips can continue to finance their ambitious projects. The AI boom has been underpinned by massive capital expenditures, and the recent spike in interest rates is testing the financial resilience of key players.
CoreWeave's Debt Woes Highlight Financing Risk
CoreWeave, a cloud provider backed by Nvidia, saw its market value plunge nearly a quarter last week as its borrowing costs soared. Yields on one of its bonds climbed above 15%, up from around 9.6%, while investors demanded significantly higher premiums against default risk.
Paul Chew, head of research at Phillip Securities, estimates that CoreWeave carries roughly $30 billion in net debt and an additional $36 billion in lease commitments, supported by a $104 billion revenue backlog. Chew warned in a research note that a four-percentage-point increase in financing costs could add almost $500 million to annual interest expenses. He emphasized, "Nvidia cannot afford CoreWeave to fail."
Nvidia owns approximately 11% of CoreWeave, which purchases its processors and helps diversify chip demand beyond the major technology giants. However, the risks remain prospective, as CoreWeave's contracted backlog provides some buffer, and Nvidia CEO Jensen Huang has defended the company's financial strength.
AI Demand Persists, but Funding Becomes More Difficult
Building data centers requires enormous upfront expenditure on processors, energy, and cooling systems. Revenue often materializes years later, leaving operators vulnerable when borrowing becomes more expensive. My Bui, an economist at AMP, told Reuters that rising government bond yields and wider corporate credit spreads are increasing financing costs, complicating borrowing and refinancing. She also questioned whether future AI revenues would recover construction costs before equipment depreciates.
The strain extends beyond individual borrowers. The Financial Times reported that at least 47 major U.S. data-center projects have been stalled or canceled this year, reflecting financing, power, and planning constraints. Yet the pressure is uneven, concentrated among heavily leveraged operators. Microsoft, Alphabet, and Meta possess far stronger financial resources than smaller providers dependent on debt markets.
That distinction matters for Nvidia, as its customers may still want more computing capacity, even if some lack affordable capital to build it immediately. The AI boom's sustainability hinges on the ability of these companies to secure funding at reasonable costs.
Meta's Earnings to Provide Next Test
Investors will look to Meta's earnings on Wednesday for reassurance that spending by major customers remains intact. Meta expects capital expenditure of $130 billion to $145 billion this year. Goldman Sachs estimates that five major AI hyperscalers could spend approximately $1.2 trillion combined in 2027.
These commitments support Nvidia's growth outlook, but greater spending is not automatically good news if profits and cash generation deteriorate. Technology investor Michael Parekh wrote in his AI: Reset to Zero newsletter that "this is a financing cycle more than a demand cycle." He expects financing strains to delay construction and drive consolidation rather than eliminate demand for computing power.
This article is for informational purposes only and does not constitute financial advice.
