Kerman Kohli: The Bottleneck in Computing Financing Lies in Credit

Kerman Kohli pointed out in "Compute Financing" on October 19, 2026, that the main bottleneck in financing computing infrastructure is capital, particularly credit. He mentioned that early financing primarily relied on balance sheet cash, then shifted to equity financing, citing Alphabet's $85 billion financing and Meta's fundraising through shareholder dilution, with the next step being the credit market. Kohli summarized three beliefs of credit providers: AI may be a bubble; the counterparty risk of purchase contracts is the greatest risk; and underlying GPUs depreciate like ordinary hardware and are worthless. He believes that the demand for agentic AI is growing by about 2.5 to 5 times each year, with supply potentially doubling by the end of 2030, memory will be sold out by 2027, and the total computing power commitment will reach trillions of dollars, mentioning Jane Street's multi-billion dollar commitment, as well as the demands from pharmaceutical companies, research, military, and cybersecurity. Regarding efficiency, he pointed out that as intelligent costs decrease by 90%, the increase in usage is even greater, with a baseline exceeding 10 times, citing Jevons' Paradox. Kohli believes that computing power is more substitutable than real estate, and when demand is strong, if someone withdraws their commitment, others will take over. He noted that many credit providers require contracts of 2 to 3 years and a down payment of 20% to 30%, locking in long-term discount contracts effectively shorting computing power for lenders. The price of computing power leasing has risen by about 50% in the past 6 months and about 100% in the past year, with B300 supplies being tight. Regarding collateral, he believes that the A100 from 2020 is still being rented out in 2029, indicating at least about 9 years of usable value, and the current price of B200 is about 50% higher than two years ago. Kohli believes that computing power will surpass real estate to become the largest asset class, and the scale of credit-supported computing power is currently just beginning.

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