This Chinese chip giant is boosting production to try and take on Nvidia - but how will Huawei feel?

• Cambricon plans to produce 500,000 AI accelerator chips next year
• The Siyuan 590 and 690 models account for 300,000 units
• Current yield rates remain extremely low at only 20%

Chinese chipmaker Cambricon Technologies aims to triple AI chip production in 2026, seeking to fill the gap left by Nvidia’s retreat from the Chinese market.

Bloomberg reports that the company intends to produce approximately 500,000 AI accelerator chips next year, with 300,000 units consisting of its main Siyuan 590 and 690 models.

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 remains substantial.

Cambricon’s GPU chips still fall far behind in performance and efficiency compared to top tier global products.

CPU workloads in Chinese data centers may continue to rely on existing infrastructure while AI accelerators scale up.

Workstation integration of these new chips will likely be tested as companies adjust to local hardware limitations.

In a neutral assessment, Cambricon’s expansion shows the growing strategic importance of domestic AI chip production.

Strong government support and rising domestic demand boost its momentum, but inefficiencies and resource competition may limit its full potential.

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