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Alibaba and Baidu Turn to In-House Chips for AI Training Amid U.S. Restrictions

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Alibaba and Baidu have begun using their own internally designed chips to train AI models, partly replacing Nvidia’s processors, according to a report from The Information. The move signals a major shift in China’s AI development strategy, as U.S. export controls continue to restrict access to advanced American-made semiconductors.

Key Developments

  • Alibaba has used its homegrown chips since early 2025 to train smaller AI models.

  • Baidu is testing its Kunlun P800 chip to train new versions of its Ernie AI model.

  • Both companies still rely on Nvidia for their most advanced models but are working to reduce dependence.

Impact on Nvidia

Nvidia remains dominant in AI training hardware, but China accounts for a large share of its business. The firm’s most powerful U.S.-approved chip for China, the H20, lags behind the H100 and Blackwell series — but still outperforms most Chinese alternatives.

However, employees cited by The Information said Alibaba’s latest AI chip matches the performance of Nvidia’s H20, narrowing the gap between U.S. and Chinese hardware.

An Nvidia spokesperson responded: “The competition has undeniably arrived … We’ll continue to work to earn the trust and support of mainstream developers everywhere.”

Geopolitical Pressure

  • U.S. export restrictions have pushed Chinese companies to accelerate domestic chip design.

  • Beijing has urged firms to rely on home-grown semiconductor technology as part of its strategic autonomy push.

  • Nvidia CEO Jensen Huang recently said talks with the White House over permission to sell a less advanced next-gen chip to China will take time.

According to the report, Nvidia has agreed to give the Trump administration 15% of China sales of its H20 chips in exchange for continued export licenses.

The Bigger Picture

China’s pivot toward domestic AI chips marks both a risk to Nvidia’s China revenues and a milestone for Chinese chipmakers, who are beginning to close the performance gap under intense geopolitical and economic pressure.