Nvidia’s AI Chip Financing Plan Faces Wall Street Scrutiny

Nvidia’s ambitious effort to use its artificial intelligence chips as collateral for financing the global AI boom is facing growing scrutiny from Wall Street lenders, who remain cautious about how long the chips can retain their value and generate revenue.

The company announced a financing initiative in August involving financial firms including Blackstone, Apollo and KKR, with plans to help mobilize as much as $500 billion for AI infrastructure. Nvidia has argued that its advanced GPUs can remain productive for up to a decade, making them suitable for long-term financing.

But banks and credit investors are taking a more conservative approach. Several financial industry sources told Reuters that lenders may seek stronger guarantees or require loans to be supported by revenue from highly rated technology companies. Banks typically assess GPUs over a three- to four-year depreciation period, reflecting uncertainty over their long-term residual value.

The concerns come as investors pour hundreds of billions of dollars into AI data centers, computing infrastructure and power capacity. Some analysts have also raised questions about private-credit and vendor-financing structures used to fund the rapid expansion of the sector.

Nvidia says its AI computing assets are “productive, durable and fungible” and can support long-term financing. The company has also pointed to studies showing that some major cloud providers are extending the depreciation periods of their servers to five or six years.

Recent transactions illustrate the cautious approach among lenders. CoreWeave secured an $8.5 billion GPU-backed financing facility that received an investment-grade rating, with lenders relying heavily on contractual payments from Meta. Broadcom, meanwhile, has backed more than 80% of a $35 billion financing structure supporting AI computing capacity for Anthropic.

For Nvidia, the challenge is to convince investors that its GPUs can function not only as essential AI infrastructure but also as reliable long-term financial assets. How lenders value the chips could influence the cost and structure of financing for the wider AI industry as companies race to expand computing capacity.