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芯海科技(688595.SH):BMS产品在笔记本电脑、无人机等领域的头部客户已实现大批量出货
Ge Long Hui· 2026-02-26 12:13
格隆汇2月26日丨芯海科技(688595.SH)在投资者互动平台表示,公司始终坚持以"模拟+MCU"双平台技 术为核心,持续推动各产品线的商业化落地。目前EC芯片已进入全球主流笔电供应链并实现大规模出 货,super IO芯片作为台式计算机的核心配套芯片,已在客户端顺利量产。针对边缘计算及服务器市场 的轻量级edge BMC管理芯片,目前已实现量产销售,正伴随边缘计算与服务器需求增长而稳步导入更 多客户。压力触控芯片、PD及BMS芯片作为公司成熟产品线,持续贡献营收,其中BMS产品在笔记本 电脑、无人机等领域的头部客户已实现大批量出货。今年核心增长点将主要来自通信与计算机相关芯片 及BMS等核心产品的持续放量。我们将继续聚焦"芯片+算法+场景+AI"的战略,稳步推进各业务线发 展。 ...
芯海科技2025年业绩预亏收窄,车规MCU等新品量产
Jing Ji Guan Cha Wang· 2026-02-14 03:57
Core Viewpoint - The company expects revenue growth in 2025 but anticipates a net loss, while also disclosing advancements in automotive-grade MCU and EC chips [1][2]. Group 1: Financial Performance - The company forecasts a total revenue of approximately 848 million yuan for 2025, representing a year-on-year growth of about 21% [2]. - The net loss attributable to the parent company is expected to be around 106 million yuan, which is a reduction in loss of approximately 67 million yuan compared to the previous year [2]. Group 2: Business Developments - The lightweight edge BMC management chip is steadily being introduced to customers due to the growing demand in the edge computing and server markets [3]. - The EC chip has entered the global mainstream laptop supply chain and is being shipped in large quantities [3]. - The automotive-grade MCU chip has been adopted by multiple automotive clients and has achieved mass production [4]. - Pressure touch products are being applied in Quark AI glasses [4]. - The company's AI strategy focuses on "chips + algorithms + solutions" and does not involve the development of AI intelligent agents, emphasizing integration with the full signal chain technology [4]. Group 3: Stock Performance - On February 10, 2026, the stock price fell by 2.97% with a trading volume of 148 million yuan and a net outflow of main funds [5]. - On February 11, 2026, the stock price increased by 2.01% with a trading volume of 76.7 million yuan and a net inflow of main funds [5]. - The stock price experienced a single-day drop of 7.45% on February 2, 2026, with a fund heavily invested in this stock [6]. Group 4: Company Status - As of November 18, 2025, the company announced that the share repurchase plan had not resulted in any share reductions, maintaining a current holding ratio of 1.59% [7].
芯海科技(688595.SH):轻量级edge BMC管理芯片正随边缘计算及服务器市场的需求增长而稳步导入客户
Ge Long Hui· 2026-02-11 08:41
格隆汇2月11日丨芯海科技(688595.SH)在投资者互动平台表示,EC、边缘计算及健康管理芯片是公司基 于"芯片+算法+AI"全栈能力打造的战略性产品,其市场导入与上量周期与传统消费芯片不同,需要与 终端生态进行深度协同研发与验证。目前,公司EC芯片已进入全球主流笔电供应链并实现大规模出 货;轻量级edge BMC管理芯片正随边缘计算及服务器市场的需求增长而稳步导入客户;健康管理芯片 及方案则与行业伙伴共同推进从精准测量到健康服务的闭环构建。公司将持续聚焦这些高潜力赛道,通 过深化与核心客户的联合创新、加快场景化方案落地来加速商业化进程,这些布局将为公司带来长期而 独特的增长动能。 ...
公司问答丨芯海科技:公司针对边缘计算及服务器市场的轻量级edge BMC管理芯片 已经实现量产销售
Ge Long Hui A P P· 2026-01-19 07:58
Core Viewpoint - The company has successfully achieved mass production and sales of its lightweight edge BMC management chip for edge computing and server markets, driven by the increasing demand for data analysis and processing in various terminal applications due to the rise of AI large model derivative applications [1]. Group 1 - The company responded to an investor inquiry regarding its collaboration with Intel on edge computing chips, confirming that the chip has entered mass production [1]. - The demand for intelligent experiences in various terminals is leading to a significant increase in data analysis and processing needs [1]. - Business deployment scenarios and data generation processes are gradually shifting towards edge and terminal sides [1].
芯海科技:公司针对边缘计算及服务器市场的轻量级edge BMC管理芯片 已经实现量产销售
Jin Rong Jie· 2026-01-19 07:49
Core Viewpoint - The company has successfully mass-produced and sold lightweight edge BMC management chips for edge computing and server markets in response to the growing demand for data analysis and processing at the edge due to the rise of AI applications [1] Group 1 - The company received inquiries from investors regarding its collaboration with Intel on edge computing chips [1] - The demand for intelligent experiences in various terminals is driving the need for extensive data analysis and processing [1] - Business deployment scenarios and data generation are gradually shifting towards edge and endpoint solutions [1]