证券日报网讯12月18日，青云科技在互动平台回答投资者提问时表示，青云科技在积极进行国际化布 局，产品与服务持续向海外市场推出。青云科技旗下AI算力云服务——基石智算国际版CoresHub.ai已 全面上线并开放使用，为全球开发者带来真正低成本、高效率、高可靠的模型服务新选择。 CoresHub.ai已同步上线多款大模型，为全球AI应用开发者、企业开发团队、AIGC创作者提供更灵活、 更高性能的模型调用服务。公司的容器软件KubeSphere是在Kubernetes之上构建的企业级容器平台，在 全球开源容器领域受欢迎程度位列第二，在全球范围内颇具技术影响力，已被海内外数万家用户使用。 ...

格隆汇12月12日｜有投资者在互动平台向青云科技提问：请问贵公司与阿里有合作吗？ 青云科技回复称，青云科技与阿里巴巴的合作主要聚焦于青云科技AI智算平台对阿里巴巴集团旗下平 头哥半导体推出的AI PPU 芯片的产品适配工作，使得算力硬件与智算平台的高效兼容。 ...

答:公司实际控制人中国有色矿业集团有限公司旗下中色经贸有限公司完成了巴西 Taboca（塔博卡矿业 公司）的约束性股权收购事项。塔博卡矿业公司拥有一座在产的锡钽铌多金属矿山、锡冶炼厂、钽铌铁 合金冶炼厂和一座为矿山供电的UHE水电站等资产；其中，锡钽铌多金属矿山和钽铌铁合金冶炼厂位 于巴西亚马逊州。2025年4月，公司已与塔博卡矿业公司公司签署了《铁钽铌合金采购合同》，拟采购 约3000吨铁铌钽合金原材料，采购金额预计为5.4 亿元人民币，为钽铌矿石原料供应链的稳定可控提供 有力保障，基本实现原材料供应自主可控。同时公司拥有矿石湿法冶炼到钽铌制品生产加工的全流程生 产线，形成从原材料到产品的全供应链保障，并不断向高端产品突破的全链条进行升级改造。 格隆汇12月11日丨青云科技(688316.SH)在投资者关系中表示，有被问到:公司的原材料供应链是否有保 障？ ...

格隆汇12月11日丨青云科技(688316.SH)在投资者关系中表示，有被问到:公司本次募集资金主要用于建 设哪些项目？ 一是钽铌湿法冶金数字化工厂建设项目。拟新建氟钽酸钾1100t/年、五氧化二铌1700t/年、高纯五氧化 二铌150t/年、高纯五氧化二钽50t/年和钽铌化合物209.5t/年和副产品锡精矿90t/年的生产线。项目总投资 6.77亿元。二是钽铌火法冶金熔炼产品生产线改造项目。预计建成达产后，新增年产熔炼铌860t/年、熔 炼钽80t/年、铌及铌合金条74t/年、钽及钽合金条(棒)240t/年。项目总投资2.88亿元。三是钽铌高端制品 生产线建设项目。预计建成达产后，钽铌板带制品产能将新增145t/年。项目总投资2.81亿元。 答:公司本次募集资金将用于投资于三个建设项目及补充流动资金，其中建设项目规划如下： ...

格隆汇12月11日丨青云科技(688316.SH)在投资者互动平台表示，截至目前，青云科技未单独研发、销 售智能体相关产品。 ...

证券代码：688316 证券简称：青云科技 公告编号：2025-060 北京青云科技集团股份有限公司 关于召开 2025 年第三季度业绩说明会的公告 本公司董事会及全体董事保证本公告内容不存在任何虚假记载、误导性陈述 或者重大遗漏，并对其内容的真实性、准确性和完整性承担法律责任。 重要内容提示： 会议召开时间：2025 年 12 月 10 日（星期三）下午 14:00-15:00 北京青云科技集团股份有限公司（以下简称"公司"）已于 2025 年 10 月 31 日发布公司 2025 年第三季度报告，为便于广大投资者更全面深入地了解公司 2025 年第三季度经营成果、财务状况，公司计划于 2025 年 12 月 10 日（星期三） 下午 14:00-15:00 举行 2025 年第三季度业绩说明会，就投资者关心的问题进行交 流。 一、说明会类型 本次投资者说明会以网络互动形式召开，公司将针对 2025 年第三季度的经 营成果及财务指标的具体情况与投资者进行互动交流和沟通，在信息披露允许的 范围内就投资者普遍关注的问题进行回答。 二、说明会召开的时间、地点 （一）会议召开时间：2025 年 12 月 10 日（ ...

Core Viewpoint - Qingyun Technology continues its strategic partnership with Moore Threads, focusing on product adaptation and certification, as well as deep integration in AI computing management platforms [1] Company Collaboration - Qingyun Technology has engaged in product adaptation and mutual product certification with Moore Threads [1] - The collaboration includes deep integration and cooperation in AI computing management platforms, leveraging Qingyun's expertise in KubeSphere and intelligent computing operations [1] - As of November 24, 2025, the strategic partnership between Qingyun Technology and Moore Threads remains active [1]

Core Viewpoint - Qingyun Technology has established a strategic partnership with Moore Threads, focusing on product adaptation and certification, particularly in the AI computing management platform area [2] Group 1 - Qingyun Technology has engaged in product adaptation and mutual product certification with Moore Threads [2] - The collaboration leverages Qingyun Technology's deep expertise in KubeSphere and intelligent computing operations [2] - The strategic partnership between Qingyun Technology and Moore Threads remains active as of now [2]

Market Overview - The Sci-Tech Innovation Board (科创板) index fell by 3.19%, closing at 1285.83 points, with a total trading volume of 4.022 billion shares and a turnover of 172.61 billion yuan, resulting in an average turnover rate of 2.09% [1] - Among the tradable stocks on the Sci-Tech Innovation Board, 33 stocks closed higher, with 3 stocks rising over 10%, while 559 stocks closed lower, with 12 stocks declining over 10% [1] Stock Performance - The stock with the highest turnover rate was C Hengkun, a new stock listed for 5 days, which saw a decline of 11.47% and a turnover rate of 46.22%, with a trading volume of 1.25 billion yuan and a net outflow of 13.49 million yuan [1] - Other notable stocks with high turnover rates included Yingfang Software, Qingyun Technology, and Tengjing Technology, with turnover rates of 15.29%, 14.95%, and 14.62% respectively [1] High Turnover Stocks - Among stocks with a turnover rate exceeding 5%, C Hengkun was noted as a new listing, while the top gainers included He Xin Instrument, Aike Saibo, and Dekeli, with increases of 20.00%, 13.31%, and 5.06% respectively [2] - The electronic industry had the highest representation among high turnover stocks, with 22 stocks, followed by the power equipment and computer sectors with 12 and 8 stocks respectively [2] Fund Flow Analysis - In terms of fund flow, 16 stocks experienced net inflows, with Dekeli, Woerde, and Yuanjie Technology receiving the most significant inflows of 110 million yuan, 95.93 million yuan, and 78.53 million yuan respectively [2] - Conversely, stocks with the largest net outflows included Rongbai Technology, Guo Dun Quantum, and Dongxin Co., with outflows of 383 million yuan, 350 million yuan, and 320 million yuan respectively [2] Leverage Fund Movements - Recent data indicated that 32 stocks received net purchases from leveraged funds, with Dongxin Co., Huafeng Technology, and Huasheng Lithium receiving the largest increases in financing balances of 332 million yuan, 260 million yuan, and 206 million yuan respectively [3] - Stocks that saw significant reductions in financing balances included Aters, Tengjing Technology, and Woerde, with decreases of 176 million yuan, 126 million yuan, and 122 million yuan respectively [3] Key Stocks on November 21 - A table of key stocks on the Sci-Tech Innovation Board highlighted C Hengkun with a closing price of 51.54 yuan and a daily decline of 11.47%, alongside other stocks like Yingfang Software and Qingyun Technology, which had notable turnover rates and net fund flows [4][5]

Core Insights - The competitive landscape for enterprises is being reshaped by artificial intelligence (AI), which is now a baseline strategy for survival and growth rather than a mere possibility [2] - The core challenge of AI adoption in enterprises lies not in the lack of models or computing power, but in seamlessly integrating disruptive AI capabilities into gradually evolving organizations [3] - Enterprises face a triad of challenges during digital transformation: respecting historical investments while embracing AI innovation, simplifying management while meeting diverse needs, and ensuring business stability while allowing for continuous technological upgrades [3][4] Group 1 - Many enterprises encounter three major barriers: data fragmentation leading to inaccurate decision-making, insufficient insights resulting in reliance on experience, and rigid systems limiting adaptability to different business models [4] - The anxiety surrounding AI adoption is exacerbated by a lack of understanding and recognition of the uncertainties associated with new technologies, leading to feelings of helplessness in the face of change [4][5] - A significant portion of enterprises focus solely on improving operational efficiency during digital transformation, with few prioritizing product service innovation and the cultivation of intelligent business models [5] Group 2 - To address the current challenges in AI transformation, enterprises need to build a bridge connecting their historical systems with future strategies, providing four forms of reassurance: investment security, transformation ease, operational simplicity, and innovation support [6] - The historical burden of multiple IT architectures complicates the transition to AI, necessitating a new generation of intelligent computing infrastructure to facilitate smooth collaboration between technological iteration and gradual business development [6][7] - The key to successful AI transformation lies in enabling gradual innovation that maximizes compatibility with existing digital transformation efforts, rather than pursuing disruptive changes [7] Group 3 - The AI Infra 3.0 framework proposed by Qingyun Technology aims to create a unified architecture that supports various capabilities, ensuring compliance and performance while optimizing resource allocation [8] - This architecture adheres to three principles: compatibility with existing assets to avoid resource waste, phased upgrades to mitigate transformation risks, and assurance of business continuity and data security [8] - The concept of "reconstruction and unification" represents a significant shift in architectural philosophy, allowing enterprises to integrate flexible technological capabilities into their existing IT systems [8]