股价年内翻倍，复牌20CM跌停，宝莱特“芯片借壳”剧本落幕

marsbitPublished on 2026-08-10Last updated on 2026-08-10

Abstract

2026年8月10日，宝莱特因筹划近一周的控制权变更事项宣告终止，股价复牌后遭遇20CM一字跌停。公司核心的血透业务深陷集采价格战，监护仪增长乏力，已连续三年巨额亏损，2026年一季度仍未见好转。此外，公司还面临短期偿债压力，其发行的“宝莱转债”即将到期，存在兑付风险。此前，市场对公司控制权变更抱有“借壳”预期。2026年1月，主营存储芯片的威固信息通过衢威智合受让了宝莱特部分股份，成为重要股东。由于双方主业差异巨大，市场猜测威固信息可能借道上市，推动宝莱特股价在年内一度翻倍。但8月7日，该事项因“涉及事项较多”被终止筹划，预期落空成为股价暴跌的直接导火索。当前，宝莱特主业扭亏前景不明，债务压力迫近，控制权变更终止后，公司面临的经营与财务困境亟待解决。

2026年8月10日,在停牌近一周后,市场期盼的宝莱特(300246.SZ)控制权变更事项宣告终止,这一利空消息直接引发二级市场的大幅抛售,宝莱特股价直接被巨量卖单死死按在20CM一字跌停板上,截至收盘,股价定格于15.41元/股。

但对于宝莱特来说,这场由“易主”预期破灭引发的股价下挫,绝非一次简单的情绪宣泄。在业务层面上,公司核心血透业务深陷集采价格战泥潭,监护仪赛道增长见顶,连续三年的巨额亏损,截至目前看不到站上盈亏线的时间点。

今年1月份,浙江衢威智合控股合伙企业(以下简称“衢威智合”)的进入,让外界看到了公司的另一种可能性。而一周多前的控制权转让公告,更是让外界纷纷猜测,是不是衢威智合背后做固态存储和计算融合方案(存储芯片)的威固信息技术(衢州)股份有限公司(以下简称“威固信息”)要借道上市,但目前来看这种幻象已经破灭。

闪电终止控制权变更

将时间拨回至2026年7月31日晚间,宝莱特突然发布公告称,控股股东燕金元及一致行动人王石正在筹划可能导致公司控制权发生变动的重大事项。这一消息犹如一颗深水炸弹,瞬间点燃了市场的炒作热情。

其实,易主的苗头最早在今年1月初就已经开始萌芽。2026年1月12日,在公司业绩已经出现明显颓势的背景下,控股股东燕金元及一致行动人王石与衢威智合签署《股份转让协议》,以9.45元/股的价格协议转让了7%的公司股份,套现约1.75亿元。5月28日,该笔股份过户完成,衢威智合正式成为持股5%以上的重要股东。

2025年9月成立的衢威智合并没有什么相关实体业务,倒是其背后站着的国家级专精特新“小巨人”企业威固信息更值得关注。

图源:天眼查APP

笔者从公开信息中了解到,公司主打高可靠特种固态存储业务,自研闪存控制器与固件算法,产品覆盖芯片级、嵌入式、加固式存储解决方案,主要面向航空航天、军工装备、轨道交通、车规等高可靠性场景,同时布局信创、工业存储赛道,核心团队具备超算项目技术背景,手握全套军工资质。

因为其在存储业务上的发展,也吸引了产业与国资背景的投资方入局。2020年12月,公司完成2亿元C轮融资,航天科工系投资平台、中铝资本、山东高速等央企及地方国资,多家上市公司产业资本共同参与;2021年9月,公司再获数亿元C+轮融资,深创投、前海母基金、超越摩尔基金等头部机构相继入场。并在2024年8月,完成D+轮融资。

显然,威固信息和宝莱特有着巨大差异的主业,这也让市场和投资者都浮想联翩,正是基于这种“跨界重组”的强烈预期,宝莱特股价在2026年内一度走出翻倍行情。公司股价自1月5日收盘价8.61元持续拉升,5月20日盘中触及21.67元,区间最大涨幅达151.68%。截至7月31日停牌前,股价年内涨幅高达137.78%,停牌前一个交易日更是大涨10.37%。

图源:Choice

但这一切都被8月7日晚间披露的终止筹划控制权变更公告击碎。宝莱特方面表示,停牌期间控股股东与交易对方就相关重大事项进行了充分探讨,“由于涉及事项较多,相关交易方经慎重考虑,认真听取各方意见,决定终止筹划本次控制权变更事项”。

深陷亏损泥潭

如果说控制权变更的终止是压垮股价的直接导火索,那么宝莱特亏损的基本面,才是其20CM跌停的根本原因。

作为一家2011年登陆创业板的老牌医疗器械企业,宝莱特早年依靠监护仪业务站稳市场。时过境迁,血液透析业务已经成长为公司第一大收入支柱,企业重心向肾科医疗倾斜,但监护仪业务并未退场,依旧作为重要的高毛利业务板块与血透业务双轮并行。

自2023年起,宝莱特便陷入了持续亏损的泥沼。财务数据显示,2023年至2025年,公司净利润分别为-6518.51万元、-7144.13万元和-6942.78万元,三年累计亏损额超过2亿元。进入2026年,亏损的态势并未得到遏制,一季度财报显示,公司营收同比下滑1.91%至2.43亿元,净利润亏损731.89万元,扣非净利润亏损更是扩大至1462.75万元。

图源:Choice

究其原因,首当其冲的便是国家医保局主导的医疗耗材集中带量采购(集采)。随着国内血透耗材集采的全面落地,透析器、透析液等产品价格遭遇断崖式下跌,宝莱特的毛利率被严重挤压。

更紧迫的是,公司短期偿债压力巨大。截至2026年一季度末,公司流动负债规模达8.3亿元,账面货币资金仅4.57亿元,仅依靠现有货币资金难以覆盖全部短期负债,叠加即将到期的宝莱转债,短期资金周转压力凸显更致命的是,公司发行的可转换公司债券“宝莱转债”将于2026年9月3日到期,剩余票面总金额约2.18亿元。在目前股价(15.41元)远低于转股价(18.30元)的倒挂背景下,转债持有人几乎不可能选择转股,这意味着宝莱特面临不小的短期资金兑付压力。

图源:Choice

所以公司不得对此前募资的项目进行结项,并将剩余的6066.31万元募集资金将永久补充流动资金。

对于宝莱特而言,控制权变更的终止或许只是迟到的利空出尽,但如何填补主业盈利的窟窿、如何化解迫在眉睫的债务危机,才是摆在管理层面前亟待解决的问题。(文| 公司观察,作者| 曹晟源 ,编辑 | 邓皓天 )

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What is AGENT S

Agent S: The Future of Autonomous Interaction in Web3 Introduction In the ever-evolving landscape of Web3 and cryptocurrency, innovations are constantly redefining how individuals interact with digital platforms. One such pioneering project, Agent S, promises to revolutionise human-computer interaction through its open agentic framework. By paving the way for autonomous interactions, Agent S aims to simplify complex tasks, offering transformative applications in artificial intelligence (AI). This detailed exploration will delve into the project's intricacies, its unique features, and the implications for the cryptocurrency domain. What is Agent S? Agent S stands as a groundbreaking open agentic framework, specifically designed to tackle three fundamental challenges in the automation of computer tasks: Acquiring Domain-Specific Knowledge: The framework intelligently learns from various external knowledge sources and internal experiences. This dual approach empowers it to build a rich repository of domain-specific knowledge, enhancing its performance in task execution. Planning Over Long Task Horizons: Agent S employs experience-augmented hierarchical planning, a strategic approach that facilitates efficient breakdown and execution of intricate tasks. This feature significantly enhances its ability to manage multiple subtasks efficiently and effectively. Handling Dynamic, Non-Uniform Interfaces: The project introduces the Agent-Computer Interface (ACI), an innovative solution that enhances the interaction between agents and users. Utilizing Multimodal Large Language Models (MLLMs), Agent S can navigate and manipulate diverse graphical user interfaces seamlessly. Through these pioneering features, Agent S provides a robust framework that addresses the complexities involved in automating human interaction with machines, setting the stage for myriad applications in AI and beyond. Who is the Creator of Agent S? While the concept of Agent S is fundamentally innovative, specific information about its creator remains elusive. The creator is currently unknown, which highlights either the nascent stage of the project or the strategic choice to keep founding members under wraps. Regardless of anonymity, the focus remains on the framework's capabilities and potential. Who are the Investors of Agent S? As Agent S is relatively new in the cryptographic ecosystem, detailed information regarding its investors and financial backers is not explicitly documented. The lack of publicly available insights into the investment foundations or organisations supporting the project raises questions about its funding structure and development roadmap. Understanding the backing is crucial for gauging the project's sustainability and potential market impact. How Does Agent S Work? At the core of Agent S lies cutting-edge technology that enables it to function effectively in diverse settings. Its operational model is built around several key features: Human-like Computer Interaction: The framework offers advanced AI planning, striving to make interactions with computers more intuitive. By mimicking human behaviour in tasks execution, it promises to elevate user experiences. Narrative Memory: Employed to leverage high-level experiences, Agent S utilises narrative memory to keep track of task histories, thereby enhancing its decision-making processes. Episodic Memory: This feature provides users with step-by-step guidance, allowing the framework to offer contextual support as tasks unfold. Support for OpenACI: With the ability to run locally, Agent S allows users to maintain control over their interactions and workflows, aligning with the decentralised ethos of Web3. Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

1.1k Total ViewsPublished 2025.01.14Updated 2025.01.14

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