Asia’s AI hardware bet has a financing problem

The US cannot sustain its own AI boom. Access to power, not capital, is now the biggest bottleneck for new capacity in the country, with new facilities in places like Virginia waiting as long as seven years for adequate supply.

China, meanwhile, cannot buy Nvidia graphics processing units (GPUs). Washington has restricted AI chip exports since October 2022 and banned every workaround chip that Nvidia designed for the Chinese market. The most recent ban on the Nvidia H20 in April 2025 triggered an announced US$5.5 billion charge for the chipmaker in a single quarter.

Southeast Asia’s advantages are clear: open land, available power, and fast permits.

Malaysia’s Johor state, which had about 10 megawatts of data center capacity in 2021, is a leading example. Now it has a development pipeline approaching 6 gigawatts by 2029, a 600x expansion in power.

The region can build AI data centers, but the tougher question is how to pay for the GPUs inside them. As chips become the dominant cost in AI infrastructure, a new financing market has emerged around the hardware itself – one with its own lenders, risks, and rules.

As someone who works on GPU financing transactions, I’ve seen firsthand how lenders evaluate these deals and where they see the biggest risks. Let’s take a closer look.

What is GPU financing?

For traditional data centers, IT equipment takes up less than 30% of total capital expenditure. But for AI data centers, GPU servers and related IT equipment account for up to 70% of the total capex.

That shift has turned GPUs into a separate asset class from the data center facilities that house them. Lenders now finance GPUs separately from the buildings, with different terms and repayment structures.

This new asset class is led by neoclouds, or cloud providers that primarily offer GPU as a service. The neocloud buys GPUs and rents them out by the hour or by the year, copying Amazon Web Services’ playbook without the AWS balance sheet.

See also: Cerebras builds gigantic AI chips. Can SEA get its hands on them?

To fund the hardware, the neocloud signs an offtake agreement – a multiyear contract in which a customer commits to buy compute capacity in advance. Lenders finance the hardware against that contract, typically placing it in a special purpose vehicle (SPV), a ring-fenced legal entity that holds the assets so the lender can seize them cleanly if payments stop.

CoreWeave first proved the model at scale by raising US$7.5 billion in debt from Blackstone and Magnetar in 2024. That deal showed that compute could be project-financed like power, aircraft, or construction – not because GPUs are safe assets, but because contracted cash flows could make risky assets financeable.

A good deal

For anyone lending to or borrowing against AI hardware in Southeast Asia, three questions determine whether a deal holds together: Will the hardware arrive on time? What will it be worth at the end of the term? Who is actually paying?

Customer concerns

Where the demand actually comes from