- Cambricon plans to supply 500,000 AI accelerator chips subsequent 12 months
- The Siyuan 590 and 690 fashions account for 300,000 items
- Present yield charges stay extraordinarily low at solely 20%
Chinese language chipmaker Cambricon Applied sciences goals to triple AI chip manufacturing in 2026, in search of to fill the hole left by Nvidia’s retreat from the Chinese language market.
Bloomberg reports that the corporate intends to supply roughly 500,000 AI accelerator chips subsequent 12 months, with 300,000 items consisting of its major Siyuan 590 and 690 fashions.
This represents a sharp increase from the roughly 142,000 units expected in 2025, yet Cambricon still faces major fabrication challenges.
Fabrication challenges and yield limitations
The reported yield rate for its 590 and 690 chips stands at just 20%, meaning that only one in five chips produced is usable.
Even with access to capacity at Semiconductor Manufacturing International, the effective output could fall far below projections.
By comparison, TSMC’s 2nm technology, seven generations ahead of SMIC’s capabilities, reaches a 60% yield, showing the efficiency gap.
Shortages of memory, including HBM and LPDDR components, further threaten the ability to meet production goals, potentially slowing delivery to data center clients.
Cambricon’s move comes as Chinese companies like Alibaba and ByteDance increasingly favor local suppliers.
They are supported by the Chinese government’s incentives to boost China’s semiconductor independence.
Cambricon’s reported revenue for the last quarter surged fourteenfold, showing strong domestic demand and investor confidence.
However, this plan will put Cambricon in direct competition with tech giant Huawei, which is planning to double its chip output, increasing pressure on Cambricon.
Both companies compete for similar wafers and fabrication resources, creating bottlenecks that could limit the speed and scale of production.
Cambricon’s strategy relies heavily on the “N+2” 7nm process node at SMIC, but whether it can sustain large scale fabrication remains uncertain.
Trade restrictions and chip embargoes over the past year have restricted access to high end AI hardware, making domestic alternatives essential for national AI ambitions.
The gap between China’s current semiconductor technology and Western competitors like Nvidia, AMD, and Intel stays substantial.
Cambricon’s GPU chips nonetheless fall far behind in efficiency and effectivity in comparison with high tier world merchandise.
CPU workloads in Chinese language knowledge facilities could proceed to depend on current infrastructure whereas AI accelerators scale up.
Workstation integration of those new chips will doubtless be examined as firms regulate to native {hardware} limitations.
In a impartial evaluation, Cambricon’s enlargement exhibits the rising strategic significance of home AI chip manufacturing.
Sturdy authorities assist and rising home demand increase its momentum, however inefficiencies and useful resource competitors could restrict its full potential.
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