Why Jensen Huang’s $500 Billion AI Financing Plan Faces a Big Risk from China

Jensen Huang’s plan to transform Nvidia’s graphics processing units (GPUs) into investment-grade assets has raised eyebrows in financial circles. The company’s founder envisions a $500 billion market for financing data centers and GPU clusters, with his chips serving as collateral for investors. However, this ambitious bet relies on the assumption that Nvidia’s GPUs will retain their value over time.

This notion is not entirely far-fetched, given that specialized computer chips can generate revenue and last for decades, like commercial real estate or toll roads. But there are reasons to doubt whether Nvidia’s AI factory platform behaves in the same way as traditional infrastructure assets. For one, the productive lifespan of cutting-edge GPUs is far from settled.

New chips power frontier model training, but they eventually become relegated to lower-margin inference work, which directly impacts their resale and collateral value. As Ben Emons, founder of FedWatch Advisors, pointed out, depreciation is the key risk here. The single biggest threat to Nvidia’s financing model comes from China, which is rapidly ramping up domestic compute capacity.

Chinese production could push hardware prices into a freefall, eroding the collateral backing hundreds of billions in private loans faster than the terms of the debt itself. This would leave investors exposed to losses if they treat GPUs as high-depreciation equipment rather than real estate, demanding high-yield returns in the 11% to 17% range.

The economics are still moving in Nvidia’s favor for now, driven by scarcity as hyperscalers race to build out capacity. Rental rates for Nvidia’s H100 chips have risen significantly this year. However, if Chinese production increases and drives down prices, this trend may not be sustainable.

The China Factor: A Wild Card in the AI Chip Market

U.S.-China trade tensions have disrupted the supply chain for AI chips. Huawei, the dominant provider of Chinese AI chips, has been on the U.S. Commerce Department’s Entity List since 2019. In May, the U.S. government said Huawei’s Ascend AI chips violate U.S. export controls.

Even if China were to restrict its AI chip exports, it’s unlikely that Nvidia would be able to maintain its market share indefinitely. The Chinese government has been actively promoting domestic compute capacity development, and local companies are already gaining traction in the market.

The CUDA Effect: A Potential Mitigator of Risk

Nvidia argues that its CUDA software layer continuously improves hardware performance after deployment, allowing older chips to stay productive longer than traditional accounting models predict. This could mitigate some of the risks associated with depreciation.

However, it’s unclear how this factor will impact the resale value of Nvidia’s GPUs. The company’s assertion is based on the assumption that continuous improvements in software will offset declining hardware value over time. But if prices plummet due to increased Chinese production, investors may still be left holding the bag.

The High-Stakes Gamble: What’s at Stake for Investors

The $500 billion market for financing AI chip infrastructure is a high-stakes gamble for investors. If Nvidia’s assumption about the long-term value of its chips turns out to be correct, it could be a lucrative opportunity for those who get in early. However, if prices plummet and investors are left holding collateral with eroded value, they will suffer significant losses.

The outcome will have far-reaching implications for the entire industry, making Nvidia’s AI financing plan a critical test of its business model and the resilience of the AI chip market.