China’s AI compute surge heavily reliant on US chips, offshore cloud access: report

China’s access to artificial intelligence computing power will double next year, but US-designed chips will account for about 65 per cent of that capacity, an indication of its continued reliance on foreign hardware, according to new research.

Total compute available to Chinese entities was expected to expand in 2027 from about 4.6 million to 8.8 million “H100-equivalents” – a metric benchmarked against Nvidia’s data-centre graphics processing units, according to a report by the Washington-based Institute for Progress (IFP).

To project these figures, IFP said it tallied domestic chips, legal imports, smuggled processors and compute accessed remotely via overseas cloud networks. Remote access alone was expected to swell to 2.8 million H100-equivalents by the end of 2027, up from roughly 1 million this year, according to the report published this week.

While the US maintains a roughly 16-fold advantage in AI training compute over China, leading Chinese models lag their American rivals by only 6.5 months, the report said.

IFP pointed to distillation – where developers train systems on the outputs of superior AI models – as a key factor helping China close the gap. China has previously rejected US allegations of “aggressive, malicious” AI distillation by domestic developers as groundless.

In light of the findings, the institute urged US policymakers to impose stricter controls on overseas cloud access, chip smuggling and legal exports.

A separate report published on Tuesday by the Institute for AI Policy and Strategy stated that US-designed compute power remained legally available for rent to foreign entities otherwise barred from buying the hardware.

The Washington-based policy group called on the US Bureau of Industry and Security to restrict Chinese access to cloud capacity large enough for training frontier AI models or running them at scale, while advocating for stronger checks on customer identity and ownership.

While chip exports are subject to licensing restrictions, Washington moved in January to allow case-by-case export reviews for Nvidia’s H200, Advanced Micro Devices’ MI325X and comparable processors under security conditions.

American exporters must show that sales would not divert supply from US customers, while Chinese buyers must adopt formal export compliance procedures and submit chips for independent testing within the US.

Meanwhile, Chinese tech giants are scrambling to bolster domestic alternatives. Huawei Technologies last month said its Ascend 960DT chip, designed for AI model training, would become available in the first quarter of 2027 – three quarters ahead of its original schedule.

The Shenzhen-based firm revealed that more than 1,000 of its Atlas 900 A3 SuperPoDs had already been deployed, while its Atlas 950 system had entered large-scale commercial use. These cluster architectures link thousands of individual processors to handle demanding AI workloads.

However, scaling domestic hardware production remains a challenge.

In an updated report last month, San Francisco-based research group Epoch AI identified high-bandwidth memory – a crucial component for feeding data to AI chips – as the main constraint on Huawei’s output.

Epoch AI estimated that Huawei’s chip output this year would deliver less than 4 per cent of the computing power of Nvidia’s global shipments.