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Chinese AI labs pursue custom chips to lower costs but heavy upfront investment a risk

Custom silicon allows for hardware optimisation tailored to specific architectures, such as the DeepSeek-R1 model

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Custom AI chips offer better performance per dollar and per watt when designed around a hyperscaler’s own software stack and data-centre architecture. Photo: Shutterstock Images
Wency Chenin ShanghaiandAnn Caoin Shanghai

Chinese AI labs are increasingly pursuing proprietary chips, mirroring a global trend towards software-hardware integration, but industry insiders and analysts warn that the strategy carries risk due to the massive upfront investments required.

“The core motivation for choosing in-house chips lies in pursuing [greater] hardware-software synergy and lowering long-term operating costs,” said Arisa Liu, chief director and research fellow at Taiwan Industry Economics Services.

Paul Triolo, a partner and technology policy lead at DGA-Albright Stonebridge Group, said in his personal newsletter AIStackDecrypted that the proprietary efforts underscored how China’s leading model developers increasingly viewed silicon as a strategic extension of the model stack rather than simply another infrastructure input.

DeepSeek has been quietly hiring chip-design talent without posting public job openings, according to two people familiar with the situation, who declined to be named as the matter was private.

The Hangzhou-based start-up’s plans for a customised AI inference chip began roughly a year ago and remained at an early stage, according to a Reuters report on Tuesday.

Meanwhile, Zhipu AI, the Beijing-based developer of the high-performance GLM-5.2 model, was in early talks with domestic chip-design companies about tailored AI processors amid a sharp increase in its daily token usage, The Information reported on Tuesday.
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