| 序 | 发行对象名称 | 获配股数 | 获配金额 | 限售期 | | --- | --- | --- | --- | --- | | 름 | | (股) | (元) | (月) | | 1 | 广发基金管理有限公司 | 1.010.861 | 1,207.999.112.22 | 6 | | 2 | UBS AG | 364,010 | 434,999,230.20 | 6 | | 3 | 新华资产管理股份有限公司 | 351,458 | 419,999,339.16 | 6 | | 4 | 汇添富基金管理股份有限公司 | 296,647 | 354,499,097.94 | 6 | | 5 | 诺德基金管理有限公司 | 233,217 | 278,698,979.34 | 6 | | 6 | 国泰海通证券股份有限公司 | 221,753 | 264,999,270.06 | 6 | | 7 | 国信证券(香港)资产管理有限公司 | 184,097 | 219,999,596.94 | 6 | | 8 | 博时基金管理有限公司 | 132,215 | 157,999,569.30 | 6 | | 9 | ...

寒武纪公告称，公司向特定对象发行A股股票333.49万股，每股发行价格为人民币1195.02元，募集资金总额为39.85亿元，扣除各项发行费用人民币3217.13万元（不含税），公司实际募集资金净额为人民币39.53亿元。募集资金将用于面向大模型的芯片平台项目、面向大模型的软件平台项目及补充流动资金。 ...

（一）本次《募集资金专户存储三方监管协议》的签订情况 公司于 2025 年 9 月 12 日召开第二届董事会第三十六次会议，审议通过了《关于公 司设立 2025 年度向特定对象发行 A 股股票募集资金专用账户的议案》。为规范公司募集 资金存放、使用与管理，提高资金使用效率，切实保护投资者权益，根据《上市公司募 集资金监管规则》《上海证券交易所科创板上市公司自律监管指引第 1 号——规范运作》 等法律、法规及规范性文件和公司《募集资金管理制度》的相关规定，2025 年 9 月 30 日，公司与保荐机构中信证券股份有限公司（以下简称"中信证券"）、募集资金专户存 储的商业银行中国建设银行股份有限公司北京中关村分行、北京银行股份有限公司九龙 山支行、中信银行股份有限公司北京分行（以下简称"签约银行"）分别签订了《募集 资金专户存储三方监管协议》（以下简称"三方监管协议"或"本协议"），本协议内容 与上海证券交易所制订的《募集资金专户存储三方监管协议（范本）》不存在重大差异。 证券代码：688256 证券简称：寒武纪 公告编号：2025-058 中科寒武纪科技股份有限公司 关于设立募集资金专项账户 并签订募集资金专户 ...

中信证券股份有限公司 关于 中科寒武纪科技股份有限公司 2025 年度向特定对象发行 A 股股票 发行过程和认购对象合规性的报告 保荐人（主承销商） 二零二五年九月 经中国证券监督管理委员会（以下简称"中国证监会"）《关于同意中科寒 武纪科技股份有限公司向特定对象发行股票注册的批复》（证监许可[2025]1969 号）批复，同意中科寒武纪科技股份有限公司（简称"寒武纪"、"发行人"或 "公司"）向特定对象发行股票的注册申请。 广东省深圳市福田区中心三路8号卓越时代广场（二期）北座 中信证券股份有限公司（以下简称"中信证券"、"保荐人"、"主承销商" 或"保荐人（主承销商）"）作为寒武纪本次向特定对象发行股票（以下简称"本 次发行"）的保荐人和主承销商，对发行人本次发行过程及认购对象的合规性进 行了核查，认为寒武纪的本次发行过程及认购对象符合《中华人民共和国公司法》 （以下简称"《公司法》"）、《中华人民共和国证券法》（以下简称"《证券法》"）、 《证券发行与承销管理办法》《上市公司证券发行注册管理办法》（以下简称"《注 册管理办法》"）、《上海证券交易所上市公司证券发行与承销业务实施细则》 （以下简称"《实施 ...

中科寒武纪科技股份有限公司发布2025年度向特定对象发行股票发行情况提示性公告。公司本次向特定 对象发行A股股票的发行承销总结相关文件已获上海证券交易所备案通过，将尽快办理新增股份登记托 管手续。本次发行具体情况可查看公司同日在上海证券交易所网站披露的《中科寒武纪科技股份有限公 司2025年度向特定对象发行A股股票发行情况报告书》等相关文件。 ...

Core Viewpoint - The company, Zhongke Hanwuji Technology Co., Ltd., has announced a private placement of 3,334,946 shares at a price of 1,195.02 yuan per share, raising a total of approximately 3.99 billion yuan, with a net amount of about 3.95 billion yuan [1] Fundraising Details - The funds raised will be allocated to specific projects, including the "Chip Platform Project for Large Models" [1] - A tripartite supervision agreement for the special account for raised funds has been signed with the sponsor, CITIC Securities, and the contracted bank, effective until the funds are fully utilized and the supervision period ends [1] - Detailed regulations regarding the rights and obligations of all parties, fund usage, and supervision have been established in the agreement [1]

Core Insights - The release of the new generation large model GLM-4.6 by the domestic unicorn company Zhipu marks a significant advancement in programming capabilities, surpassing the latest model DeepSeek-V3.2-Exp and aligning with global leader Claude Sonnet 4 in various benchmarks [2][3][5] Model Performance - GLM-4.6 has achieved substantial improvements in core capabilities such as Agentic Coding, long context processing, reasoning ability, information retrieval, text generation, and intelligent agent applications [3][4] - The context window has been increased from 128K to 200K, allowing for better handling of longer code and agent tasks [3] - The model's reasoning ability has been enhanced, supporting tool invocation during reasoning processes [3] - In practical programming tasks, GLM-4.6 outperformed Claude Sonnet 4 in 74 real-world scenarios [3] Token Efficiency and User Experience - GLM-4.6 has improved token efficiency, consuming over 30% fewer tokens compared to GLM-4.5 for similar tasks [4] - The model enhances the usability of presentations and the aesthetic quality of front-end code, improving layout design [4] Open Source and Ecosystem Development - GLM-4.6 is set to be open-sourced on platforms like Hugging Face and ModelScope under a permissive MIT license, positioning it as one of the strongest general-purpose models in the global open-source ecosystem [5] - The model has been adapted for use on domestic AI chips from companies like Cambrian and Moore Threads, facilitating a collaborative ecosystem between domestic large models and chips [5][6] Industry Collaboration and Future Prospects - The rapid adaptation of GLM-4.6 by domestic chip manufacturers indicates a deepening collaboration within China's AI industry, moving towards a unified ecosystem of software and hardware [6] - Zhipu has initiated A-share listing guidance, aiming to become the first publicly listed company focused on domestic AI large models, signaling a shift from technological competition to commercialization and capital operation [6]

Core Insights - The release of the new generation large model GLM-4.6 by the domestic unicorn company Zhipu marks a significant advancement in programming capabilities, surpassing the latest model DeepSeek-V3.2-Exp and aligning with global leader Claude Sonnet 4 in various assessments [1][2][5] Model Performance - GLM-4.6 has shown substantial improvements in core capabilities such as Agentic Coding, long context processing, reasoning ability, information retrieval, and text generation, making it the strongest coding model in China [2][5] - The context window has been increased from 128K to 200K, allowing for better handling of longer code and agent tasks [5] - The model has improved reasoning capabilities and supports tool invocation during reasoning processes, enhancing its overall performance [5] Token Efficiency - GLM-4.6 has achieved over 30% savings in token consumption compared to its predecessor GLM-4.5, indicating improved efficiency in processing tasks [5] Open Source and Global Positioning - GLM-4.6 is set to be open-sourced on platforms like Hugging Face and ModelScope under a permissive MIT license, positioning it as one of the strongest general-purpose models in the global open-source ecosystem [6] Chip Adaptation and Ecosystem Development - The model has been adapted for use on domestic AI chips from companies like Cambricon and Moore Threads, marking a significant step in the collaboration between domestic large models and chips [7][8] - The successful adaptation of GLM-4.6 on these chips demonstrates the capability of domestic GPUs to collaborate with cutting-edge large models, accelerating the development of a self-controlled AI technology ecosystem [7][8] Industry Collaboration - The rapid adaptation of GLM-4.6 following the release of DeepSeek-V3.2-Exp indicates deep collaboration among leading companies in the Chinese AI industry, suggesting a shift towards a unified ecosystem of software and hardware [8] - Zhipu has initiated A-share listing guidance, aiming to become the first publicly listed company focused on domestic AI large models, signaling a transition from technological competition to commercialization and capital operation [8]

Core Insights - The average stock price on the STAR Market is 43.07 yuan, with 80 stocks priced over 100 yuan, and the highest priced stock is Cambrian-U at 1325.00 yuan [1][2] - A total of 426 stocks increased in price today, while 155 stocks decreased, with the average increase for stocks over 100 yuan being 2.72% [1] - The premium of the latest closing prices of stocks over 100 yuan relative to their issue prices averages 472.26%, with the highest premiums seen in companies like Shunwei New Materials and Cambrian-U [2] Stock Performance - Cambrian-U closed at 1325.00 yuan, up 0.11%, followed by Maolai Optics and Yuanjie Technology at 439.00 yuan and 429.00 yuan respectively [1] - New stocks crossing the 100 yuan mark today include Pinming Technology at 100.60 yuan, which rose 18.60%, and Huahong Company at 114.56 yuan, which increased by 15.72% [1] - The top gainers among stocks over 100 yuan include Pinming Technology, Huahong Company, and Canxin Technology, while the biggest losers include Jingyi Equipment and Dongxin Technology [1] Industry Analysis - The majority of stocks priced over 100 yuan are concentrated in the electronics, pharmaceutical, and computer industries, with 41, 13, and 10 stocks respectively [2] - The net capital outflow for stocks over 100 yuan today totaled 7.69 billion yuan, with significant inflows into companies like Dekeli and SMIC [2][3] - The total margin financing balance for stocks over 100 yuan is 967.13 billion yuan, with SMIC and Cambrian-U having the highest balances [3]

Core Viewpoint - The release of the new generation model GLM-4.6 by Zhiyu marks a significant advancement in programming capabilities, positioning it as the leading domestic coding model and enhancing the collaboration between domestic AI models and chips [1][2][14]. Group 1: Model Performance - GLM-4.6 has achieved substantial improvements in various capabilities, including real programming, long context processing, reasoning ability, information retrieval, and writing skills, surpassing the performance of the latest DeepSeek model [1][12]. - In tests conducted in the Claude Code environment, GLM-4.6 outperformed Claude Sonnet 4 in 74 real-world programming tasks, establishing itself as the strongest coding model in China [12][14]. - The model has improved token efficiency, saving over 30% in token consumption compared to GLM-4.5, while enhancing the usability and aesthetics of front-end code [12][14]. Group 2: Chip Adaptation - GLM-4.6 has been adapted for use with domestic AI chips from Cambrian and Moore Threads, marking a significant step in the integration of domestic models and chips [13][14]. - The model utilizes a mixed quantization inference deployment (FP8+Int4) on Cambrian chips, significantly reducing inference costs while maintaining model accuracy [14]. - The adaptation of GLM-4.6 to Moore Threads' GPU demonstrates the compatibility and rapid adaptation capabilities of domestic chips with advanced models [14][15]. Group 3: Industry Implications - The simultaneous release and adaptation of models by leading domestic companies indicate a deep collaboration within the Chinese AI industry, accelerating the development of a unified ecosystem [15]. - Zhiyu has initiated A-share listing guidance, aiming to become the first publicly listed company focused on domestic AI models, signaling a shift towards commercialization and capital operation in the AI sector [15].