Nvidia’s $100 billion OpenAI investment raises eyebrows and a key question: How much of the AI boom is just Nvidia’s cash being recycled?

Nvidia's substantial investments in its customers, including a $100 billion commitment to OpenAI and stakes in companies like CoreWeave and Lambda, are intensifying investor concerns about a potential AI bubble. These 'circular' financing arrangements, where Nvidia funds entities that subsequently purchase its GPUs or services, are seen by analysts as potentially inflating perceived demand and revenue figures, drawing parallels to practices observed in past tech bubbles. While these deals enable customers to secure better debt rates, they raise questions about the true underlying demand for AI infrastructure and the quality of Nvidia's revenue, given its 'priced for perfection' valuation and the risk of bearing depreciation costs or inventory if demand for AI workloads does not meet expectations.

Analysis

Nvidia's recent $100 billion investment commitment to OpenAI is amplifying concerns among investors regarding 'circular financing' within the AI sector, a practice that potentially inflates the perception of organic demand. This follows a pattern where Nvidia invests in or finances its own customers, such as CoreWeave and Lambda, who then use the capital or improved borrowing capacity to purchase Nvidia's GPUs. For instance, CoreWeave, in which Nvidia holds a 7% stake valued at approximately $3 billion, has purchased about $7.5 billion worth of Nvidia GPUs. These arrangements, which recall the vendor financing seen before the dot-com bubble burst with companies like Cisco, create a tangled web that makes it difficult to ascertain true end-market demand. Analysts from Bernstein and Seaport Global have noted this 'bubble-like behavior,' highlighting that while the share of revenue from such deals may be small, Nvidia's 'priced for perfection' valuation makes it highly sensitive to any perceived weakness. Furthermore, by leasing GPUs to OpenAI, Nvidia is absorbing the depreciation costs and inventory risk, a liability that could become material if AI workload demand does not meet projections. The opacity of these deals, many of which are individually too small to be reported as material, adds a layer of uncertainty for investors trying to gauge the quality of Nvidia's record revenues.

Key Decisions for Investors

• Investors should intensely scrutinize Nvidia's revenue quality by monitoring financial filings for any disclosures on vendor financing, customer investments, and large-scale lease agreements to distinguish organic growth from capital-stimulated sales.
• Given the 'priced for perfection' valuation and the negative sentiment surrounding these circular deals, it is prudent to review position sizing in NVDA and consider hedging strategies to mitigate downside risk from a potential sentiment shift or demand reassessment.
• Monitor the financial health and capital expenditure plans of key private customers like CoreWeave and other 'neo-cloud' companies, as their ability to service debt and fund purchases is a critical dependency for Nvidia's growth trajectory.
• The historical parallels to the dot-com era suggest a need for caution across the AI ecosystem; therefore, evaluate exposure to companies heavily reliant on Nvidia's technology and investment, as they may face outsized risk in a market downturn.