有消息称，昆仑芯即将完成股改，加速推进冲刺上市的步伐。对此事，接近昆仑芯的人士对 《科创板日报》表示，一切以公告为准。 又一AI芯片企业或将启动IPO。 有消息称，昆仑芯即将完成股改，加速推进冲刺上市的步伐。对此事，接近昆仑芯的人士对《科创板日 报》记者表示，一切以公告为准。 此前，百度集团港股公告称，目前正就拟议分拆及上市进行评估。若进行分拆及上市，将须经相关监管 审批程序，而公司并不保证分拆及上市将会进行。 昆仑芯科技前身为百度智能芯片及架构部，于2021年4月完成独立融资，首轮估值约130亿元。截至2025 年7月，昆仑芯经历了D轮融资，投资方包括上河动量资本、山证投资、国新基金下属的高层次人才基 金、中移和创等。 《科创板日报》记者注意到，从股权结构来看，百度为昆仑芯控股股东，持股比例为59.45%。北京昆 仑传奇科技合伙企业（有限合伙）与天津九章昆仑企业管理合伙企业（有限合伙）分别持股约4.61%和 3.57%。 在11月举行的百度世界大会上，新一代昆仑芯M100和M300发布。其中，昆仑芯M100 针对大规模推理 场景优化设计，将于2026年上市；昆仑芯M300面向超大规模的多模态模型的训练和推理 ...

Core Viewpoint - Kunlun Core, a self-developed chip project under Baidu, is accelerating its path to IPO following its upcoming share reform [1][3]. Group 1: Company Overview - Kunlun Core was established in 2011 and began independent financing in 2021, with Ouyang Jian as CEO [1]. - Baidu is the controlling shareholder of Kunlun Core, which has completed six rounds of financing, the latest in July this year [1]. Group 2: Product Development - The main product of Kunlun Core is the P800 chip, set to launch in 2024, which has been validated within Baidu's operations [1]. - In the first half of this year, Baidu activated a 30,000-card cluster based on the P800 chip, achieving high cost-performance in training a multimodal model [1]. Group 3: Future Product Roadmap - Kunlun Core plans to release the M100 chip in 2026, optimized for large-scale inference scenarios, and the M300 chip in 2027, aimed at ultra-large multimodal model training and inference [1][3]. - Baidu will launch the "Tianchi 256 Super Node" in the first half of 2026, which supports 256 interconnected cards, enhancing total interconnect bandwidth by four times and improving performance by over 50% compared to the previous model [3]. - The "Tianchi 512 Super Node" is expected in the second half of 2026, supporting 512 interconnected cards and capable of training trillion-parameter models [3]. Group 4: Long-term Vision - According to Baidu's roadmap, Kunlun Core anticipates launching a new generation of N series chips by 2029 and achieving a million-card Kunlun Core single cluster by 2030 [4].

拟分拆昆仑芯赴港上市？百度进行了回应。 12月7日晚间，百度集团发布一则"官宣式"公告：公司注意到于2025年12月5日有媒体报道公司拟分拆非全资附属公司昆仑芯（北京）科技有限公司（简 称"昆仑芯"）进行独立上市。公司澄清，目前正就拟议分拆及上市进行评估。若进行分拆及上市，将须经相关监管审批程序，而公司并不保证分拆及上市 将会进行。 百度回应"昆仑芯赴港上市" 而就在两天前，路透社发布消息称，百度拟分拆昆仑芯并筹备上市，计划最早于2026年一季度向港交所递交上市申请，目标是在2027年初完成IPO。此 前，昆仑芯刚刚完成一笔融资，投后估值达210亿元。 受该消息影响，百度港股股价一度大涨超过7%。截至12月5日收盘，百度上涨5.01%，市值达3344.2亿港元。 | 今开 | 115.800 | 最高 | 124.800 | 成交量 | 3062万股 | | --- | --- | --- | --- | --- | --- | | 昨收 | 115.800 | 最低 | 115.100 | 成交额 | 37.16亿 | | 换手率 | 1.11% | 市盈(TTM) | 33.93 | 总市值 | 3344 ...

来源：证券时报 证券时报记者 吴瞬 12月7日晚间，百度集团发布公告，就市场关于公司拟分拆非全资附属公司昆仑芯（北京）科技有限公 司进行独立上市传闻作出澄清。公告表示，目前正就拟议分拆及上市进行评估。倘进行拟议分拆及上 市，将须经相关监管审批程序，而公司并不保证拟议分拆及上市将会进行。 昆仑芯（北京）科技有限公司前身为百度智能芯片及架构部，于2021年4月完成独立融资，首轮估值约 130亿元。公司团队在国内最早布局AI加速领域，深耕十余年，是一家在体系结构、芯片实现、软件系 统和场景应用均有深厚积累的AI芯片企业。 近期，市场上对于百度昆仑芯的关注度持续上升。在11月举行的2025百度世界大会上，百度正式发布全 新一代昆仑芯，以及基于昆仑芯的超节点产品天池。据介绍，全新一代昆仑芯包括两款产品。其中，昆 仑芯M100针对大规模推理场景优化设计，提供极致性价比，将于2026年上市；昆仑芯M300面向超大规 模多模态模型的训练和推理需求提供极致性能，预计2027年上市。 同步发布的天池256超节点与天池512超节点将于明年正式上市，单个天池512超节点就能完成万亿参数 模型训练。百度表示，未来五年计划按年推出新款产 ...

记者丨叶映橙 见习记者林健民 编辑丨谭婷 12月5日，百度港股午后突然直线拉涨，一度涨近8%。 随后涨幅收窄，截至收盘涨超5%，报121.6港元/股，总市值为3344亿港元。 截至收盘， 港股算力硬件概念出现拉涨行情。除了百度，英诺赛科也大涨逾5%，鸿腾精密、联想集团等公司也纷纷跟涨。 消息面上，据财联社，有报道称， 百度旗下半导体子公司昆仑芯计划在香港上市，昆仑芯近期融资2.83亿美元，估值达29.7亿美元（ 折合人民 币约210亿元 ）。 天眼查显示，昆仑芯是由百度内部孵化的AI芯片公司，于2021年4月完成独立融资， 首轮估值约130亿元， 百度为控股股东，持股比例为 59.45%。 截至2025年7月，昆仑芯已经历了D轮融资， 投资方包括上河动量资本、山证投资、国新基金下属的高层次人才基金、中移和创等 。 另据腾讯财经，多位产业人士表示，昆仑芯技术和营收在国内一众AI芯片公司中均位于前列。 2024年公司营收超过10亿元，超过此前已申报 上市的燧原科技、壁仞科技、沐曦集成电路，也超过已经上市的摩尔线程和寒武纪。 此前摩根大通预计，百度昆仑芯片收入将从2025年的约人 民币13亿元飙升至2026年的83 ...

（文章来源：21世纪经济报道） 据悉，昆仑芯已累计完成数万卡部署，成为了百度AI关键底座。百度智能云也通过昆仑芯和百舸AI计 算平台，为大批企业提供AI算力。 公开资料显示，昆仑芯前身为百度智能芯片及架构部，于2021年4月完成独立融资，首轮估值约130亿 元。 东吴证券表示，算力基础层面，公司以自研能力不断夯实算力底座。依托昆仑芯、百度天池超节点以及 百度百舸，百度智能云不断夯实AI基础设施能力，持续为客户解决算力供给的问题，支撑大模型训练 与推理的稳定运行，帮助更多行业以可承受的成本可预期的效率加速内化AI能力。东吴证券看好AI给 公司业务带来新的发展机遇，且持续回购体现注重股东回报，维持"买入"评级。 12月5日，百度港股午后突然直线拉涨，1分钟涨近5%，随后涨幅收窄，截至13:31，涨4.49%，报121港 元/股，总市值为3328亿港元。 消息面上，据智通财经，有报道称，百度旗下半导体子公司昆仑芯计划在香港上市，昆仑芯近期融资 2.83亿美元，估值达29.7亿美元。 此前，在今年11月的百度世界大会上，百度集团执行副总裁沈抖发布新一代昆仑芯和超节点产品天池。 沈抖介绍，全新一代昆仑芯包括两款产品。其 ...

Investment Rating - The report maintains an "Outperform" rating for the computer sector, recommending specific stocks including Wuxi Unicomp Technology, Kingdee International, Iflytek, Newland Digital Technology, Hand Enterprise, ArcSoft Corporation, and Hygon, with Dawning Information Industry as a related target [2][7]. Core Insights - Alibaba has launched the "Qwen" project to compete with ChatGPT, marking a significant strategic expansion into the C-end AI application market after previously focusing on B-end services [8]. - Baidu emphasizes the value of AI applications, showcasing new self-developed hardware and a roadmap for its Kunlun chips, aiming to build a robust autonomous computing power system [9]. - Muxi Integrated Circuit's IPO registration has been approved, indicating progress in the domestic high-end chip market, while space computing emerges as a new frontier in global tech competition [10]. Summary by Sections Alibaba's Initiatives - Alibaba has initiated the "Qwen" project, developing a personal AI assistant app to compete globally, with significant investment in AI infrastructure [8]. Baidu's Developments - At the Baidu World Conference, the company highlighted AI's potential to create substantial value, launching new AI chips and applications [9]. Muxi's IPO and Space Computing - Muxi's IPO approval for raising RMB 3.90 billion for GPU development signifies a key step for domestic chip advancement, alongside the rise of space computing as a competitive technology frontier [10].

Core Insights - The AI industry structure is currently unhealthy, with the chip layer capturing most of the value, while the model and application layers earn significantly less. This imbalance is unsustainable, and companies like Baidu are compelled to develop their own chips to regain control over value creation [1][4]. Group 1: Chip Development and Strategy - Baidu has launched two self-developed AI chips, Kunlun M100 and M300, as part of its strategy to enhance its AI capabilities [2]. - The Kunlun chip team has been active since 2011, evolving from early AI models to developing chips specifically for large models, such as the P800 [1][8]. - The M100 chip is optimized for large-scale inference and is set to be released in early 2026, while the M300 chip, designed for high-end training and inference tasks, will be available in early 2027 [8][10]. Group 2: Industry Challenges and Opportunities - The emergence of the Transformer model has unified the architecture of AI models, making it easier for chip manufacturers to target performance improvements [4]. - However, the rapid growth of AI applications presents challenges, as the future direction of the AI industry remains uncertain, leading to increased costs in computing power, energy, and infrastructure [5][6]. - The industry is moving towards a new engineering and scientific exploration route, where simply stacking chips is no longer sufficient [7]. Group 3: System Integration and Performance - The concept of "super nodes" is crucial for optimizing chip performance, allowing multiple chips to work together as a single unit, significantly enhancing communication efficiency [9]. - Baidu's super node solutions, such as the Tianchi 256 and 512, are designed to handle trillion-parameter models, with performance improvements of over 50% compared to previous iterations [9][10]. - The integration of chips, memory, communication, power supply, and cooling systems is essential for the success of AI infrastructure [9].

Core Insights - The article discusses the current structure of the AI industry, highlighting a "pyramid" model where the majority of value is captured at the chip level, while models and applications capture significantly less value. The ideal structure proposed is an "inverted pyramid" where models generate ten times the value of chips, and applications generate one hundred times the value of models [2][14]. Company Developments - Baidu has launched two new chips, Kunlun M100 and Kunlun M800, aimed at enhancing performance in large-scale inference and training of multimodal models. The M100 is set to be released in early next year, while the M800 is a high-performance version of the M100 [5][6]. - Baidu's AI cloud business has shown significant growth, with non-online marketing revenue surpassing 10 billion yuan, reflecting a 34% increase, despite a slight decline in overall revenue due to weak advertising performance [17]. Technological Innovations - Baidu introduced "Tianchi 256 Super Node" and "Tianchi 512 Super Node," capable of supporting trillion-parameter model training. The 512 Super Node boasts a 95% performance improvement per card and an eightfold increase in single-instance inference performance [9][10]. - The emergence of super nodes is a response to the increasing size of models and the limitations of traditional server interconnects. Baidu's approach to super nodes indicates a strong underlying capability in chip design and communication technology [10][13]. Industry Context - The article references a Morgan Stanley estimate predicting that the generative AI industry will generate approximately $153 billion in total revenue by 2025, with Nvidia projected to account for $130.5 billion of that revenue [15]. - The current "pyramid" structure of the AI industry is acknowledged, but there are signs of a shift in value distribution, with companies like Baidu actively working to enhance their AI capabilities across the entire value chain [17][20].

Core Insights - The core viewpoint of the article is that artificial intelligence (AI) is transitioning from a phase of "intelligent emergence" to "effect emergence," indicating that AI solutions are becoming practical and impactful for businesses and individuals [4][5]. Group 1: AI Industry Structure - The AI industry structure is shifting from an unhealthy "pyramid" model to a healthy "inverted pyramid" model, where the value generated by applications and models significantly exceeds that of the underlying chips [5]. - In the previous structure, chip manufacturers captured most of the value, while models and applications received diminishing returns, leading to skepticism about AI's sustainability [5]. - The new structure emphasizes that models should generate ten times the value of chips, and applications should create one hundred times the value of models, fostering a healthier ecosystem [5]. Group 2: AI Capabilities and Applications - AI capabilities have expanded beyond chatbots to include digital human technology and self-evolving algorithms that seek global optimal solutions in various fields such as transportation, energy, finance, and drug development [4][8]. - The newly launched Baidu "self-evolving" super-intelligent agent, Baidu Famo, is designed to find global optimal solutions in real-world industrial scenarios [8][10]. - Baidu's search results are increasingly AI-generated, with 70% of the top search results now featuring rich media content rather than just text links [5]. Group 3: New Product Launches - Baidu has introduced the next generation of Kunlun chips, M100 and M300, aimed at optimizing large-scale inference and training for multimodal models, with M100 set to launch in 2026 and M300 in 2027 [18]. - The new Wenshin 5.0 model features 2.4 trillion parameters and supports multimodal understanding and generation, demonstrating capabilities comparable to leading models in the industry [11][16]. - Baidu's AI API has been integrated by 625 companies, establishing it as a foundational technology in the industry [6]. Group 4: Future of Autonomous Driving - Baidu's advancements in autonomous driving are expected to revolutionize urban life, with projections indicating that the cost of robotaxi services in the U.S. could drop to approximately $0.25 per mile by 2030, significantly increasing demand [20]. - The company reported that its fully autonomous orders have surpassed 250,000 weekly, with total autonomous driving mileage exceeding 240 million kilometers [20].