Nvidia’s Pivot: Can New AI Chips Survive U.S. Trade Crackdown?

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As the U.S. considers implementing stricter trade restrictions to prevent advanced chip technology from reaching China, Nvidia, a leading semiconductor manufacturer based in the U.S., is reportedly developing a modified version of its AI chips to comply with these regulations.

According to a report by Reuters, Nvidia is creating a variant of its new Blackwell AI chips for the Chinese market and will partner with local distributor Inspur to introduce and market the chip, which is provisionally named the “B20.” Sources indicate that the B20 is expected to begin shipping in the second quarter of 2025.

Nvidia has designed three chips, including the H20, specifically to meet U.S. export control requirements. In response to sluggish sales against competition from domestic rival Huawei, Nvidia lowered prices for the H20 chip. However, reports suggest that sales for the H20 are now on the rise, with projections indicating that the company may sell over one million units in China this year, generating approximately $12 billion in revenue, despite the existing trade restrictions. This anticipated figure is nearly double the expected sales for Huawei’s Ascend 910B chip, according to data from SemiAnalysis.

Nonetheless, Jefferies analysts warn that Nvidia’s H20 chips may face additional risks under forthcoming U.S. trade regulations. They expect that during the annual review of semiconductor export controls in October, it is “highly likely” that the H20 will be prohibited for sale to China. This potential ban could be enacted through several mechanisms, including a product-specific prohibition, a reduction in the computing power threshold, or limitations on memory capacity.

Furthermore, there is speculation that the U.S. may broaden export controls on semiconductor sales not only to China but also to other countries in the region, such as Malaysia, Indonesia, and Thailand. Extending these controls to overseas Chinese companies could also be a consideration, although this would present more significant implementation challenges.

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