Revolving Financing Behind the GPU Boom: Truth and Crisis

** How the capital chain makes the price of graphics cards inflated, but hides the real cost **

Revolving financing has made the GPU industry prosperous on the surface, but in fact it has buried costs in the black hole of financing. In 2023, Nvidia delivered US$26 billion in revenue, but revealed in its supply chain report in December of the same year that the actual production cost of a single RTX4090 was still around US$1,200; at the same time, CoreWeave completed US$150 million in Series B‑ financing, and Nebius completed Series C‑ with a valuation of US$400 million. It seems that capital is "fueling the flames", but every new money further smoothes the true face of costs. ** Let me make a bet: without this financing cycle, GPU prices will immediately fall by more than 30%. **

Financing Chain Self-reinforcement

In the past two years, the explosive growth in demand for AI computing power has left several computing power providers almost relying on "financing to buy GPUs." CoreWeave started from 5,000 GPUs at the end of 2022 and has rented 30,000 A100 units at the end of 2023;Nebius's 2023 Q3 financial report shows that the GPU asset-liability ratio has exceeded 70%. Behind these numbers is a closed loop: VC investment → prepayment leasing → billing services → refinancing. ** The blood of capital is injected again and again, forming a self-sustaining bubble. ** The following histogram visually compares the financing amounts of the three major computing power manufacturers from 2022 to 2024.

The "prepaid lease" model of financing passes on the depreciation costs of graphics cards to end users. A common cost model is:

def gpu_monthly_cost(price, lease_rate=0.03, months=36):
    return price * lease_rate / (1 - (1 + lease_rate)**-months)

Assuming a $2,000 GPU with an annual rent rate of 3%, the monthly cost is approximately $81 after 30 months of amortization. Compared with the average charge per GPU‑hour of cloud computing power services of US$0.12 (approximately US$6/day), it seems cost-effective, but the capital cost is forcibly embedded in the service fee. ** Real hardware expenditures are swallowed up by financial expenses, and users cannot even feel the existence of this layer of expenses. **

QKPFX0 Mirror effect of QK capital

I know Xiao Liu, an operation and maintenance engineer at a computing company. During a routine inspection last year, he found that the monthly fee for the lease contract increased by 40% compared with the same period last year. He traced back to the supply chain and found that the inventory of the GPU supplier had been locked in advance. The inventory cost shown on the book was only US$1,100, but the leasing company included the "financial premium" of the graphics card into the monthly fee. Xiao Liu sent a message in the Slack group: "What we bought was not a graphics card, but a bond." This sentence quickly spread in the industry and became the first slogan to reveal the financing cycle. ** Don't be deceived by the "high price of graphics cards", the truth is that capital is adding interest to graphics cards. **

Anti-Steel Man

Some people will say that the GPU industry itself is capital-intensive and has a long R & D cycle, and relying on financing is the only way to survive. Opponents even quoted the 2023 IDC report: "AI computing power demand will double in 2025, and capital inflows are necessary expansion levers." But they ignored two key points: first, financing did not simultaneously bring about cost reductions; second, the entry of capital led to irrational price increases. Take Nvidia as an example. Although its profit margin will remain at around 40% in 2023, the retail price of its graphics cards has increased by more than 55% since 2021. If you exclude the cost of capital, the profit margin will fall below 20%. ** Capital is not a panacea, it is more like a tool to package graphics cards into financial derivatives. **

Cross-Border Analogy: Mortgage Securities for Real Estate

Comparing GPU revolving financing to the 2008 subprime crisis is not an empty analogy. The core of that crisis was the packaging of non-performing mortgages into securities, followed by layers of leverage in the capital market, which ultimately led to overvaluation of asset values. Today's computing companies regard the leased GPUs as "collateral" and continue to "package" them with financing rounds. In real estate, house prices are ultimately pushed up by investors 'speculative demand; in computing power, GPU prices are raised by the "rental demand" of capital. What the two have in common is: ** The true use value is concealed by the financial structure, and systemic risks are growing. **

Conclusion

Looking back, revolving financing has pushed the GPU market into a self-reinforcing bubble: each round of financing uses a higher rental rate to lay the foundation for the next round of financing, and the true nature of costs is buried in layers of financial packaging. ** The faster the blood of capital flows, the more outrageous the real price of graphics cards will be. ** Without external financing shocks, graphics card prices are likely to fall by 20%‑30% in the next quarter. I bet that the breaking point in this financing cycle is not a technical bottleneck, but an unsustainable financing cost. ** Readers, what unexposed financial traps do you think are hidden behind capital-driven graphics card prices? **