岁末年初，中国算力产业在资本领域的运作骤然提速。 1月8日，上海天数智芯半导体股份有限公司（下称"天数智芯"，09903.HK）在港股挂牌上市，其此次 公开发售获超400倍认购，充分显示了资本市场的热情。 与GPU厂商的二级市场热潮相呼应，国产存储芯片厂商也在2025年末完成了关键一跃。2025年12月30 日，长鑫科技集团股份有限公司（以下简称"长鑫科技"）正式向上交所递交科创板招股书，并披露了其 2025年前三季度320.84亿元的营收数据，这一数字直观展示了国产DRAM（动态随机存取存储器）产能 释放的规模。 更早之前的2025年9月25日，长江存储科技控股有限责任公司（以下简称"长存集团"）完成了股份制改 革，其1600亿元的估值一度刷新了半导体独角兽的纪录，也标志着这家NAND Flash（闪存）龙头进入 了发展新阶段。 从芯片设计到存储颗粒，从科创板到港交所，一浪接一浪的资本热潮间接宣告了国产算力产业的快速进 步。当然，在资本市场的热度之外，国产芯片在实际的智算中心建设与应用适配中，仍面临着复杂考 验。 各司其职 此前不久，另外两家国产GPU头部企业也已接连登陆科创板：2025年12月5日，摩尔线 ...

从芯片设计到存储颗粒，从科创板到港交所，一浪接一浪的资 本热潮间接宣告了国产算力产业的快速进步。当然，在资本市 场的热度之外，国产芯片在实际的智算中心建设与应用适配 中，仍面临着复杂考验。 作者：郑晨烨 封图：图虫创意 岁末年初，中国算力产业在资本领域的运作骤然提速。 1月8日，上海天数智芯半导体股份有限公司（下称"天数智芯"，09903.HK）在港股挂牌上市， 其此次公开发售获超400倍认购，充分显示了资本市场的热情。 此 前 不 久 ， 另 外 两 家 国 产 GPU 头 部 企 业 也 已 接 连 登 陆 科 创 板 ： 2025 年 12 月 5 日 ， 摩 尔 线 程 （688795.SH）上市首日股价一度上涨468.78%，总市值突破3055亿元；2025年12月17日， 沐曦股份（688802.SH）上市首日涨幅达到692.95%，市值站上3300亿元关口。 与GPU厂商的二级市场热潮相呼应，国产存储芯片厂商也在2025年末完成了关键一跃。2025年 12月30日，长鑫科技集团股份有限公司（以下简称"长鑫科技"）正式向上交所递交科创板招股 书，并披露了其2025年前三季度320.84亿元的营收数 ...

经济观察报记者 郑晨烨 岁末年初，中国算力产业在资本领域的运作骤然提速。 1月8日，上海天数智芯半导体股份有限公司（下称"天数智芯"，09903.HK）在港股挂牌上市，其此次 公开发售获超400倍认购，充分显示了资本市场的热情。 此前不久，另外两家国产GPU头部企业也已接连登陆科创板：2025年12月5日，摩尔线程 （688795.SH）上市首日股价一度上涨468.78%，总市值突破3055亿元；2025年12月17日，沐曦股份 （688802.SH）上市首日涨幅达到692.95%，市值站上3300亿元关口。 与GPU厂商的二级市场热潮相呼应，国产存储芯片厂商也在2025年末完成了关键一跃。2025年12月30 日，长鑫科技集团股份有限公司（以下简称"长鑫科技"）正式向上交所递交科创板招股书，并披露了其 2025年前三季度320.84亿元的营收数据，这一数字直观展示了国产DRAM（动态随机存取存储器）产能 释放的规模。 更早之前的2025年9月25日，长江存储科技控股有限责任公司（以下简称"长存集团"）完成了股份制改 革，其1600亿元的估值一度刷新了半导体独角兽的纪录，也标志着这家NAND Flash（闪存 ...

炒股就看金麒麟分析师研报，权威，专业，及时，全面，助您挖掘潜力主题机会！ 来源：风云IPO 作者|刘钦文 编辑|高远山 股东名单已多达44位。 deepseek、豆包、kimi、chatGPT，当数以亿计的用户将"大模型"视作生活百科全书，频繁提问时你或许 不知道，每一次看似简单的提问背后，可能正有上万枚AI芯片进行着浩如烟海的推理计算。 而其中一部分可能正来自百度的昆仑芯（北京）科技股份有限公司（下称"昆仑芯"）。2026年1月2日， 百度集团（9888.HK）在港交所发布公告，昆仑芯已于1月1日以保密形式，向香港联交所提交主板上市 申请。 此次分拆拟通过全球发售方式推进，包括香港公开发售及机构投资者配售，上市完成后昆仑芯仍将维持 百度附属公司地位。也就是说，昆仑芯将成为百度创始人李彦宏所控股的第二家上市公司。 受此消息影响，1月4日百度股价大涨9.35%，报收143.8港元/股，总市值3955亿港元。 公开信息显示，昆仑芯最新一轮融资于今年7月完成，投后估值约210亿元。投资方阵容豪华，包括CPE 源峰、IDG资本、比亚迪、国新高层次人才基金等机构。而这些机构和百度都有着不浅的渊源。 若是昆仑芯完成上市， ...

Core Viewpoint - The article highlights the rapid growth and market potential of domestic AI chip companies, particularly focusing on Wallen Technology, which has successfully launched its GPU products and is experiencing significant revenue growth due to increasing demand for AI computing power [1][3]. Company Overview - Wallen Technology, known as the "first GPU stock in Hong Kong," debuted on the Hong Kong Stock Exchange on January 2, 2026, with a market capitalization exceeding HKD 100 billion and a subscription rate of over 2300 times during the offering phase [1]. - The company has developed its first-generation GPGPU architecture and two chip models, BR106 and BR110, and is advancing towards its second-generation architecture products [2][8]. Revenue Growth - In 2022, Wallen Technology reported revenue of approximately RMB 500,000, which surged to about RMB 62.03 million in 2023, marking a growth of 443.29% to approximately RMB 337 million in 2024 [2]. - The average transaction amount per customer increased by 113.64% to RMB 940,000, reflecting the company's successful market penetration and product acceptance [2]. Market Potential - The Chinese smart computing chip market is projected to grow from USD 1.7 billion in 2020 to USD 30.1 billion by 2024, with a CAGR of 105%, and is expected to reach USD 201.2 billion by 2029 [3]. - Domestic AI chip manufacturers are anticipated to increase their market share from approximately 20% in 2024 to about 60% by 2029, indicating significant growth opportunities for competitive players [3]. Technological Advancements - Wallen Technology is focusing on enhancing its cluster capabilities and has successfully commercialized its AIDC thousand-card GPU cluster project, collaborating with major telecom operators [6][9]. - The company plans to launch its next-generation flagship data center chip, BR20X, by 2026, which is expected to provide improved single-card computing power and support for various data formats [8]. Industry Collaboration - Wallen Technology is actively participating in industry collaborations, including the establishment of the OISA ecosystem and the development of mixed training solutions to address challenges in heterogeneous computing environments [9][10]. - The company is involved in the formulation of national standards for AI computing, which will facilitate the adoption of domestic GPUs and support the innovation of large models [10]. Future Strategy - The company aims to continue investing in R&D, particularly in core technologies to enhance its autonomous capabilities, while fostering partnerships to improve brand recognition and accelerate solution commercialization [10][11]. - The competitive landscape for domestic GPUs is evolving beyond hardware specifications to encompass reliable deployment, open-source ecosystem development, and forward-looking technical standards [10].

Core Insights - Google is attempting to sell its self-developed AI chip, TPU (Tensor Processing Unit), to a broader market, posing a significant challenge to Nvidia, the current leader in AI chips [1] - The advanced AI models from Google and Anthropic utilize Google's TPU chips, which has prompted major clients like Meta to consider using TPUs for new model development [1] - Morgan Stanley predicts that Google plans to produce over 3 million TPUs by 2026 and around 5 million by 2027, while Nvidia's current GPU production is approximately three times that of Google's TPUs [1][7] Performance Comparison - Although a single TPU chip is less powerful than Nvidia's strongest GPU, Google's strategy leverages large-scale clusters to enhance performance and cost-effectiveness [2][3] - Thousands of TPUs can be connected to form a "super pod," providing superior performance in training large models compared to Nvidia's GPU systems, which can connect a maximum of about 256 GPUs directly [3] Software Ecosystem - Nvidia's competitive advantage lies in its deeply integrated CUDA software ecosystem, making it more cost-effective for existing users to rent Nvidia chips [4] - TPU's compatibility challenges arise as it primarily works with specific AI software tools like TensorFlow, while most AI researchers prefer PyTorch, which performs better on GPUs [4] Cost Dynamics - The manufacturing costs of TPU and GPU are comparable, with TPU using advanced but more expensive manufacturing technology [5] - Nvidia's hardware business maintains a gross margin of 63%, while Google's cloud services have a margin of only 24%, explaining Nvidia's strong profitability in price competition [6] Capacity Competition - TSMC does not allocate all its production capacity to a single client, allowing space for alternatives like TPU in the market [7] - As Google ramps up TPU production, the gap between TPU and Nvidia's GPU production is narrowing, encouraging clients to explore multiple options [7] Commercialization Challenges - Google faces significant challenges in building a complete supply chain for TPU sales, including partnerships with server manufacturers and distribution networks [8] - Deploying TPUs in client data centers could lead to a loss of cloud service revenue for Google, indicating that TPUs may not follow a low-cost strategy but rather a complex strategic approach [8] - The broader significance of TPU for Google lies in its potential to negotiate with Nvidia and promote its Gemini AI ecosystem, enhancing Google's autonomy in AI infrastructure [8]

Core Insights - Google is shifting its TPU strategy from primarily serving its own AI models to actively selling chips to third parties, directly competing with Nvidia [1][2] - Anthropic has become one of the first significant customers for Google's TPU, involving a deal for approximately 1 million TPUs, which includes both direct hardware purchases and rentals through Google Cloud Platform (GCP) [1][2][3] - The competitive landscape is changing, with OpenAI negotiating a 30% price discount in discussions with Nvidia by considering alternatives like TPUs [1] Group 1: Partnership with Anthropic - Google has mobilized its resources to provide TPUs to external customers, marking a significant step in its strategy to become a differentiated cloud service provider [2] - The partnership with Anthropic aligns with its goal to reduce reliance on Nvidia, with Google having made early investments in Anthropic while limiting its voting rights [2] - Anthropic will deploy TPUs in its own facilities and also rent additional TPUs through GCP, allowing Google to compete directly with Nvidia [3] Group 2: Financial Implications - The deal with Anthropic includes a direct sale of approximately $10 billion worth of TPU systems, with 400,000 TPUv7 chips, making Anthropic a key customer for Broadcom [3] - Anthropic's rental of an additional 600,000 TPUv7 chips through GCP is expected to generate about $42 billion in contract value, significantly contributing to GCP's order backlog [3] Group 3: Technical Advancements - TPUv7 "Ironwood" is nearing parity with Nvidia's Blackwell architecture in theoretical performance and memory bandwidth, with a competitive edge in pricing [5][12] - The total cost of ownership for each TPU is approximately 44% lower than Nvidia's GB200, and even with a premium for external customers, the cost remains 30%-50% lower than Nvidia systems [6][8] - Google is working to eliminate software compatibility barriers by developing native support for frameworks like PyTorch, aiming to make TPUs a viable alternative without requiring developers to overhaul their toolchains [10][12] Group 4: Competitive Landscape - Nvidia is preparing a counterattack with its next-generation "Vera Rubin" chip, which may reshape the competitive landscape [13] - Google plans to develop TPUv8 in two versions, but analysts note that the designs are conservative and may face delays [13] - The success of Nvidia's upcoming chips could challenge Google's current pricing advantages, emphasizing the need for Nvidia to execute its technology roadmap effectively [13]

Core Insights - Nvidia maintains a leading position in technology and market share with its Blackwell architecture, but Google's TPU commercialization is challenging Nvidia's pricing power [1][2] - OpenAI's leverage in threatening to purchase TPUs has led to a 30% reduction in total cost of ownership (TCO) for Nvidia's ecosystem [1] - Google's transition from a cloud service provider to a commercial chip supplier is exemplified by Anthropic's significant TPU procurement [1][4] Group 1: Competitive Landscape - Google's TPU v7 shows a 44% lower TCO compared to Nvidia's GB200 servers, indicating a substantial cost advantage [7][66] - The first phase of Anthropic's TPU deal involves 400,000 TPUv7 units valued at approximately $10 billion, with the remaining 600,000 units leased through Google Cloud [4][42] - Nvidia's defensive posture is evident as it addresses market concerns regarding its "circular economy" strategy of investing in AI startups [5][31] Group 2: Technological Advancements - Google's TPU v7 architecture has been designed to optimize system performance, achieving competitive efficiency despite slightly lower theoretical peak performance compared to Nvidia [12][53] - The introduction of Google's innovative interconnect technology (ICI) allows for dynamic network reconfiguration, enhancing cluster availability and reducing latency [15][17] - Google's shift towards supporting open-source frameworks like PyTorch indicates a strategic move to dismantle Nvidia's CUDA ecosystem dominance [19][20][22] Group 3: Financial Implications - The financial engineering behind Google's TPU sales, including credit backstop arrangements, facilitates a low-cost infrastructure ecosystem independent of Nvidia [9][47] - The anticipated increase in TPU sales to external clients, including Meta and others, is expected to bolster Google's revenue and market position [43][48] - Nvidia's strategic investments in AI startups are seen as a way to maintain its market position without resorting to price cuts, which could harm its margins [35][36][31]

Group 1: US-China Economic Talks - The recent US-China economic talks in Kuala Lumpur led to preliminary consensus on key issues such as maritime logistics, shipbuilding, and agricultural trade, setting the stage for the upcoming leaders' meeting [2][3] - Both sides expressed a willingness to resolve differences through respectful dialogue and cooperation, indicating a potential thaw in trade tensions [2][3] Group 2: Industrial Profit Growth - In the first nine months of the year, China's industrial enterprises achieved a total profit of 53,732 billion yuan, a year-on-year increase of 3.2%, with September alone seeing a profit growth of 21.6% [4][5] - The profit growth was driven by strong export demand and a slight recovery in domestic demand, although the sustainability of this growth remains uncertain [5] Group 3: Birth Rate Statistics - In 2024, China's birth population is projected to be 9.54 million, an increase of 520,000 from the previous year, with a birth rate of 6.77‰, up by 0.38‰ [6][7] - The data indicates that western regions have higher birth rates compared to eastern regions, with Guangdong continuing to lead in total births [6][7] Group 4: New Energy Vehicle Subsidies - A competitive subsidy "war" among car manufacturers has emerged, with companies like Chery and Xiaomi offering to cover the additional purchase tax costs for consumers due to policy changes [8][9] - This trend reflects the intensifying market competition in the new energy vehicle sector, as companies aim to boost sales before the tax reduction policy takes effect [8][9] Group 5: Meituan's Bond Issuance - Meituan plans to launch its largest bond issuance to raise approximately $3 billion, primarily for refinancing existing debts and general operational needs [10][11] - The company faces significant competition in the food delivery sector, prompting the need for financial maneuvers to alleviate cash flow pressures [10][11] Group 6: Porsche's Profit Decline - Porsche reported a staggering 99% drop in profit for the first three quarters, with a loss of 9.66 billion euros in Q3, attributed to declining sales in China and Europe [12][13] - The company is undergoing organizational restructuring and plans to cut jobs as part of its strategy to cope with the challenges posed by the shift towards electric vehicles [12][13] Group 7: SoftBank's Investment in OpenAI - SoftBank has approved an additional $22.5 billion investment in OpenAI, part of a larger commitment to invest $40 billion, aiming to capitalize on OpenAI's potential IPO [14][15] - This investment comes amid SoftBank's ongoing financial challenges and highlights the risks associated with high-stakes investments in the tech sector [14][15] Group 8: Stock Market Performance - The stock market experienced a significant rise, with the Shanghai Composite Index reaching a ten-year high, driven by positive sentiment from US-China trade negotiations [16][17] - Despite the overall market uptrend, there were fluctuations, indicating cautious investor sentiment as the index approached the psychological 4000-point mark [16][17]

Core Insights - The competition between the companies is intense, with DJI being both a challenge and a motivator for Insta360, as highlighted by the founder's remarks on the dual nature of DJI's presence in the market [1] - Insta360 has established a strong market position in the consumer panoramic camera segment, holding a 67.2% market share, significantly ahead of competitors like Ricoh and GoPro [4] - The company is adjusting its distribution strategy to enhance its dealer system and optimize its CRM, indicating a proactive approach to competition [1][6] Company Overview - Insta360's product line includes a variety of imaging devices such as consumer and professional panoramic cameras, action cameras, and AI stabilizers, with consumer products contributing 86.59% of revenue in 2024 [2] - The ONE X series is the best-selling product line, showcasing the company's strength in the consumer market [2] Market Position - Insta360 leads the global panoramic camera market, selling 8 out of every 10 panoramic cameras worldwide, thanks to its advanced imaging technology and AI algorithms [4] - Despite its dominance in panoramic cameras, Insta360 faces strong competition from GoPro and DJI in the broader action camera market [5] Financial Performance - Insta360's revenue from the Ace series action cameras increased from 0.97 billion in 2023 to 2.76 billion in the first half of 2024, indicating strong growth [5] - The company’s revenue from non-panoramic action cameras is approximately 1.5 billion, ranking third in the market [5] Distribution Strategy - Insta360 employs a hybrid sales model combining online and offline channels, with a near 1:1 ratio in 2024, and a significant portion of sales coming from third-party e-commerce platforms [6][8] - The company collaborates with major retailers and uses a buyout sales model for most distributors, focusing on enhancing customer experience and trust [9] Marketing Strategy - Insta360 has developed a robust marketing strategy centered around KOLs and user-generated content, significantly increasing brand visibility and engagement [10][11] - The company has initiated various marketing campaigns and collaborations with influencers to enhance its brand image and reach [10] Competitive Landscape - DJI is seen as a formidable competitor, particularly in the action camera segment, with its upcoming Osmo 360 product directly competing with Insta360's offerings [14][18] - The competition has led to price wars, with DJI adopting a low-price strategy while maintaining high performance, which poses a challenge for Insta360 [19] Technological Development - Insta360's core competencies lie in its software ecosystem and advanced algorithms, which provide a competitive edge in the market [17][23] - The company is investing heavily in R&D, with over 12% of its revenue allocated to this area, and a significant portion of its workforce dedicated to research [23] Future Outlook - The market dynamics between Insta360 and DJI are expected to drive innovation and technological advancements in the imaging sector, benefiting the overall industry [26]