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hot_img Citrini Analyst: The progress of China's DUV is not surprising, the sell-off of semiconductor equipment stocks like ASML is excessive

Citrini analyst Jukan posted on social media that the news of China's progress in DUV lithography technology is not particularly surprising, as the market had already formed certain expectations. He pointed out that The Information's related report only cited a professor from a transportation university in China speaking at an internal meeting in June and did not disclose more substantial information. Jukan believes that the sell-off reaction seen in semiconductor equipment stocks like ASML is an overreaction to this news.According to previous reports, The Information cited sources saying that a state-owned enterprise supported by Chinese state capital has begun mass production of domestically developed DUV (Deep Ultraviolet) lithography manufacturing equipment, marking a key progress in the localization of China's semiconductor industry.Insiders stated that the enterprise plans to produce about 5 domestically made DUV lithography machines by 2026 and expand to about 20 machines by 2027. Although there is still a gap compared to the 131 immersion DUV lithography systems delivered by Dutch lithography giant ASML last year, the entry of domestic equipment into mass production is seen by the market as an important breakthrough in the localization of China's chip supply chain.

Goldman Sachs released a report on China's AI computing power, predicting that by 2026, the market share of domestic chips will exceed 50%

According to the Goldman Sachs report on "China's AI Computing Power" disclosed by P Equity Research, China is accelerating the construction of a national computing power network, with related infrastructure projects expected to attract 7 trillion yuan in investment by 2026. In the next five years, investment in data centers is projected to reach about 2 trillion yuan. Currently, funds and technology are being massively transferred to western computing power hubs, while data centers in first-tier cities are transforming to focus on ultra-low latency computing, edge nodes, and AI inference. Although GW-level clusters with over 100,000 chips remain scarce domestically, in typical GW-level computing power parks, workloads are primarily composed of inference, which accounts for more than half, as well as training and full-stack R&D.The report predicts that by 2026, the market share of domestically produced AI acceleration chips is expected to exceed 50%. Among them, Huawei and Alibaba's Pingtouge lead the domestic camp with shares of 20% and 7%, respectively, but Nvidia currently maintains overall market dominance with a 55% share. In terms of cost and performance, domestic chips have capital expenditures on IT power consumption that are 40% to 50% lower than imported chips, but due to performance gaps, their capital expenditures per unit of computing power are 2 to 4 times that of imported chips, and the computing power generated per unit of power consumption is only 10% to 30% of that of imported chips. Additionally, the daily average token output of Huawei's 910B/910C servers is about one-sixth to one-third of that of Nvidia's H800, resulting in significantly lower API profit margins based on that hardware compared to peers using Nvidia hardware.
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