红星资本局12月7日消息，沐曦股份今日公告，回拨机制启动后，网下最终发行数量为2282.9081万股，占扣除最终战略配售部分后本次发行数量的 70.26%，网上最终发行数量为966.55万股，占扣除最终战略配售部分后本次发行数量的29.74%。回拨机制启动后，网上发行最终中签率为0.03348913%。 值得注意的是，成功上市后，沐曦股份将成为继摩尔线程（688795.SH）之后第二家登陆A股市场的国产GPU公司。 12月3日晚间，沐曦股份发布公告显示，公司本次新股发行价为104.66元/股。 公告称，发行人与保荐人（主承销商）根据网下发行询价报价情况，协商确定公司发行价格为104.66元/股，发行价格确定后上市时市值约为418.74亿元， 对应的发行人2024年摊薄后静态市销率为56.35倍，低于同行业可比公司2024年静态市销率平均水平。 | 图片来源：公司公告 | | --- | 沐曦股份本次发行数量为4010万股，占发行后公司总股本比例为10.02%。若本次发行成功，预计募集资金总额41.97亿元，将用于投资"新型高性能通用 GPU研发及产业化项目""新一代人工智能推理GPU研发及产业化项目"和"面向 ...

Core Insights - The 2025 World Artificial Intelligence Conference (WAIC) highlighted the significance of "super nodes" in AI computing infrastructure, with Huawei showcasing its Ascend 384 super node, which boasts a computing power of 300 PFLOPs, nearly double that of NVIDIA's GB200 NVL72 system [1][3] - Domestic AI chip manufacturers are increasingly embracing the super node trend, moving beyond mere parameter comparisons to collaborative efforts, as seen in a rare joint appearance of executives from four domestic AI chip companies [2][11] - The demand for AI computing power is rapidly increasing, leading to the emergence of the "super node" concept as a recognized solution to meet the needs of large-scale AI models [3][4] Super Node Development - The super node concept, proposed by NVIDIA, involves connecting multiple high-performance AI servers to form a larger, more powerful computing node, specifically designed for complex AI model calculations [3][4] - Current super node implementations are characterized by high-performance GPUs interconnected within a single node, with a focus on maintaining consistent bandwidth and latency [4][5] - The future of domestic super node solutions will involve maximizing computing power within individual cabinets and connecting multiple cabinets through optical interconnects [6] Industry Collaboration and Innovation - The WAIC showcased various super node products from multiple vendors, including high-density liquid cooling systems and innovative interconnect technologies, indicating a competitive landscape among domestic manufacturers [7][8] - The emergence of the "AI factory" concept by domestic GPU manufacturers aims to address the efficiency bottlenecks in training large models, emphasizing the need for a comprehensive AI training infrastructure [9][10] - The establishment of the "Model-Chip Ecological Innovation Alliance" signifies a deeper integration between domestic AI models and chips, promoting collaboration among various stakeholders in the industry [11][12]

Core Insights - The 2025 World Artificial Intelligence Conference (WAIC 2025) was held in Shanghai, showcasing innovations in AI chips, servers, and intelligent computing centers, emphasizing domestic R&D and solutions for various application scenarios [1][2]. AI Chip Innovations - Companies like Muxi and Houmo Intelligent presented their self-developed AI chips, with Muxi showcasing the Xiyun C600 general-purpose GPU, designed for cloud AI training and inference [3][4]. - Houmo Intelligent introduced the M50 chip, claiming a 5-10 times efficiency improvement over traditional architectures, with a processing power of 160 TOPS at only 10W, supporting large models locally [5]. Market Trends - The demand for computing power is growing exponentially alongside model iterations, with a shift towards edge AI chips as models migrate from cloud to edge applications [3][5][6]. - The industry is witnessing a trend towards high-efficiency inference becoming mainstream, with inference computing power expected to be 100 to 1000 times that of training power [6]. Supernode Developments - Major Chinese companies like Huawei and Xinhua San showcased their supernode solutions, with Huawei's Ascend 384 supernode being the largest in the industry, achieving 300 PFLOPs of computing power [7][8]. - The LightSphere X supernode, developed by a consortium including Shanghai Yidian and ZTE, utilizes innovative optical interconnect technology for high bandwidth and low latency [9][10]. Industry Collaboration - The development of supernodes requires cross-industry collaboration, as no single chip company can achieve the necessary technological advancements alone [8][10]. - The industry is encouraged to adopt open-source development to accelerate product development and market entry, with a focus on collaborative efforts in computing infrastructure and services [10][12].