Core Viewpoint - Moer Technology plans to raise 8 billion yuan through its IPO on the Sci-Tech Innovation Board, focusing on self-developed GPUs for high-performance computing applications in AI, digital twins, and scientific calculations [2][6]. Company Overview - Founded in 2020, Moer Technology specializes in developing full-function GPUs and has launched four generations of GPU architectures, covering various applications such as AI computing, high-performance computing, graphics rendering, and smart media [2]. - The company has established R&D and technical support centers in major cities like Beijing, Shanghai, Chengdu, and Shenzhen to quickly respond to customer needs [4]. Technology and Product Development - Moer Technology's MUSA architecture allows a single chip to support AI computing acceleration, graphics rendering, physical simulation, and scientific computing, marking a significant technological breakthrough in the domestic GPU industry [2][3]. - Compared to other AI acceleration products, the MUSA architecture offers stronger computing versatility, better technological evolution capability, and broader market adaptability [3]. Market Applications - In the intelligent computing market, Moer Technology's products support various high-end applications, including large language models and medical imaging, with solutions like the MTT S4000 and S5000 series [5]. - The company's products are also widely used in high-performance graphics workstations for industrial design and simulation, contributing to the optimization of the domestic high-performance graphics market [5]. Financial Performance - Moer Technology's revenue from 2022 to 2024 is projected to grow from 46 million yuan to 438 million yuan, with a compound annual growth rate exceeding 200% [5]. - The company has maintained high R&D investment, with over 3.8 billion yuan allocated from 2022 to 2024, and employs a workforce where 78.69% are R&D personnel [6]. Future Plans - The funds raised from the IPO will be used for the development of new self-controlled AI training and inference chips, graphics chips, and AI SoC chips, as well as to supplement working capital [6].