China is moving quickly to boost its domestic artificial intelligence chip production, with plans to triple output by next year as competition with the United States intensifies.
A fabrication plant focused on producing Huawei’s AI processors is expected to begin operations by the end of this year, with two more facilities scheduled to launch in 2026, according to industry sources. While these plants are tailored for Huawei, the company itself has denied ownership, leaving questions about their structure.
At the same time, Chinese developers are working on the next generation of AI chips designed to align with a data format promoted by DeepSeek, a fast-growing local AI start-up. Huawei’s latest processors, along with Cambricon’s 690 model, are considered compatible with DeepSeek’s standard.
The combined capacity of these plants, once fully operational, could surpass the current production of SMIC (Semiconductor Manufacturing International Corporation), China’s largest contract chipmaker. SMIC itself plans to double its output of 7-nanometer processors, the most advanced chips mass-produced domestically, with Huawei as its biggest customer.
This expansion could also benefit smaller Chinese chip design firms such as Cambricon, MetaX, and Biren, giving them greater access to manufacturing capacity at a time when U.S. export bans have limited the availability of Nvidia’s processors in China.
Industry experts believe that next year’s growth in production will significantly reduce supply shortages. DeepSeek has already announced that its models are shifting to the FP8 data format — a move that boosts efficiency, though with some loss in precision — offering a potential path for Chinese AI companies to stay competitive despite lagging behind Nvidia in hardware power.
However, such progress will require close coordination among chipmakers, memory and connectivity hardware providers, and software developers over the coming years.
Beijing is throwing its weight behind these efforts. This week, China’s State Council emphasized the importance of AI adoption and called for stronger collaboration in research, engineering, and commercialization of AI-driven technologies.
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