Investment Rating - The industry investment rating is "Overweight" [1] Core Insights - Alibaba's Qwen3-Max-Thinking model has achieved significant improvements in various key dimensions, including factual knowledge, complex reasoning, instruction adherence, human preference alignment, and agent capabilities, performing comparably to top models like GPT-5.2-Thinking and Claude-Opus-4.5 in 19 authoritative benchmark tests [3][12] - The model features over one trillion parameters and enhances the native agent capabilities for autonomous tool invocation, significantly reducing hallucinations and laying the groundwork for solving real complex tasks [5][12] - The release of Clawdbot marks a new phase in the development of intelligent agents, allowing users to interact through messaging apps and execute commands via local scripts, thus transitioning from "AI providing suggestions" to "AI taking direct actions" [4][13] Summary by Sections 1. Computer Industry Insights - On January 26, Alibaba released the flagship reasoning model Qwen3-Max-Thinking, which has shown significant enhancements across multiple key performance metrics [12] - The model's core innovations include adaptive tool invocation capabilities and test-time scaling technology, which significantly boosts reasoning performance [12][14] 2. Market Performance Review - The computer industry index fell by 4.77%, underperforming the Shanghai Composite Index by 4.33 percentage points, while the year-to-date performance shows a 6.94% increase [16][17] - The computer sector ranked 28th among 31 industry indices this week, indicating a challenging market environment [16] 3. Technology Software Industry News - The "Smart Computing" initiative in Shanghai aims to enhance the AI infrastructure, with a focus on building a complete industrial chain covering chips, optical communication, and servers [23] - The launch of the "Star Computing" plan by a commercial aerospace company aims to create a space-based computing network to support AI agents with low-latency and high-reliability services [24] 4. Company Dynamics - Companies like Cambricon, Inspur, and Alibaba are highlighted as key players in the AI industry chain, suggesting investment opportunities in these firms [5][14] - Recent stock option and incentive plans from various companies indicate a focus on retaining talent and driving growth in the tech sector [35][36]

Core Insights - The article highlights the successful deployment of three sets of scaleX supercomputing clusters by Zhongke Shuguang, marking the first domestic implementation of over 30,000 cards in an AI computing pool in China [1][12]. Group 1: Deployment and Significance - The scaleX supercomputing cluster was first showcased at the HAIC conference in December last year and became operational within two months, demonstrating rapid advancement in domestic AI computing capabilities [3][14]. - This deployment signifies a critical transition from merely constructing infrastructure to actively utilizing it, representing a substantial leap for domestic supercomputing clusters [4][14]. Group 2: Demand and Evolution - The demand for computing power has surged as AI model parameters have escalated from billions to trillions, necessitating a shift in architecture to meet these requirements [5][15]. - Industry forecasts predict that by 2025, China's demand for intelligent computing power will increase nearly 20 times compared to 2020, with sustained high growth expected in the following years [6][16]. Group 3: Technological Advancements - The scaleX supercomputing cluster not only achieves a significant scale increase but also makes systematic breakthroughs in system architecture, energy efficiency management, and resource scheduling, pushing domestic AI computing into a new phase of quality and quantity [6][16]. - The cluster is designed based on an open architecture that fully supports mainstream software ecosystems like CUDA, facilitating mixed deployment of various domestic acceleration cards and lowering the adaptation threshold for developers [10][19]. Group 4: Application and Impact - The scaleX supercomputing cluster provides deep empowerment across multiple scenarios, including support for trillion-parameter model training, high-throughput inference for major internet companies, and advancements in AI for scientific research [11][20]. - It significantly enhances research efficiency in fields such as materials science, achieving improvements in protein research efficiency by 3 to 6 orders of magnitude [11][20]. Group 5: Future Outlook - The ongoing construction of the national supercomputing internet and the integration of computing power scheduling mechanisms are gradually establishing a self-controlled, open, and efficient AI computing system in China [12][20]. - The successful deployment of the scaleX supercomputing clusters is expected to leverage national-level computing hubs to provide high-quality AI computing services globally [12][20].

Core Insights - The National Supercomputing Internet Core Node has launched in Zhengzhou, marking the first operational deployment of a 30,000-card domestic AI computing pool in China [1] - The scaleX 10,000-card super cluster is a significant advancement in AI computing, achieving a 20-fold increase in cabinet-level computing density and a 30% to 40% performance improvement for MoE trillion-parameter model training and inference [1][2] - The scaleX640 super node, which supports multi-brand acceleration cards and is compatible with mainstream computing ecosystems, aims to lower the R&D threshold for AI clusters and avoid redundant investments [2] Technological Advancements - The scaleX640 super node features an "open architecture" that enhances communication speed and reduces latency, enabling the formation of thousand-card computing units [1][2] - The supercomputing pool supports various large-scale AI computing scenarios, including trillion-parameter model training, high-throughput inference, and AI for Science applications, significantly improving research efficiency in fields like protein studies [2] Future Developments - The company plans to establish an Advanced Computing Technology Research Institute in Zhengzhou, with a 160,000 square meter R&D space and an initial goal of gathering 1,000 researchers focused on AI and high-performance computing applications [3]

Core Viewpoint - The domestic intelligent computing infrastructure is crossing a critical watershed, marking a significant advancement in the deployment and operationalization of large-scale AI computing clusters in China [1][5]. Group 1: Scale of Deployment - The first domestic AI computing pool with a deployment of 30,000 cards has officially formed, representing the largest operational domestic AI computing pool [3][5]. - The transition from single-point breakthroughs to large-scale deployment indicates a maturity in engineering capabilities for domestic supercomputing clusters [5][9]. Group 2: System Engineering Capabilities - The competition in the large-scale computing cluster market has shifted from merely achieving high card counts to focusing on system-level collaboration, including network, storage, cooling, power supply, and operational optimization [8][9]. - Key capabilities such as controllable cycles, reproducible performance, fault localization, and cost accounting are essential for long-term players in the market [8][12]. Group 3: Real-World Application - The true test for large-scale computing clusters lies in their ability to convert computing power into real business productivity, moving beyond mere demonstrations to practical applications [14][15]. - Successful large-scale applications require open compatibility, making it easier for users to adapt and integrate into existing systems [17][19]. Group 4: Public Infrastructure - The perception of large-scale computing clusters is evolving from being exclusive to large corporations to becoming public infrastructure, serving various sectors such as manufacturing, energy, transportation, research, education, healthcare, and finance [20]. Group 5: Performance in Various Scenarios - The scaleX computing cluster demonstrates its value across three dimensions: stability in large model training, practical service capabilities in high-throughput inference, and accelerated scientific discovery in AI for Science applications [23][26]. - The cluster has successfully supported over 400 mainstream models and thousands of applications, showcasing its ability to integrate with the AI industry ecosystem [21][26]. Group 6: Future Outlook - The release of three scaleX computing clusters signals that merely stacking computing power is no longer the core competitive advantage; future winners must ensure that these clusters continuously deliver value in real-world business applications [27][28].

Core Insights - The National Supercomputing Internet Core Node has launched in Zhengzhou, marking the first operational deployment of a 30,000-card domestic AI computing pool in China [1] - The scaleX 10,000-card supercluster has achieved a significant milestone in AI computing, with a 20-fold increase in cabinet-level computing density and a 30% to 40% performance improvement for MoE trillion-parameter model training and inference scenarios [1][2] - The scaleX640 super node, which supports multi-brand acceleration cards and is compatible with mainstream computing ecosystems, aims to lower the R&D threshold for AI clusters and avoid redundant investments [2] Technological Advancements - The scaleX640 super node features an "open architecture" that enhances high-bandwidth, low-latency communication domains, enabling the formation of thousand-card computing units [1][2] - The supercomputing pool supports various large-scale AI computing scenarios, including trillion-parameter model training, high-throughput inference, and AI for Science applications, significantly improving research efficiency in fields like protein studies [2] Future Plans - The company plans to establish an Advanced Computing Technology Research Institute in Zhengzhou, with a 160,000 square meter R&D space and an initial goal of gathering 1,000 researchers focused on AI and high-performance computing applications [3] - The company aims to deepen technology research and application practices to provide more efficient, stable, and inclusive domestic intelligent computing services across various sectors of economic and social development [3]

Group 1 - The China Securities Information Technology Application Innovation Industry Index decreased by 0.05% as of February 6, 2026, with mixed performance among constituent stocks [1] - Geer Software led the gains with an increase of 8.45%, while ZTE Information fell by 2.81%, indicating volatility in the sector [1] - The Xinchuang ETF (562570) experienced a decline of 0.27%, with the latest price at 1.47 yuan [1] Group 2 - The Xinchuang ETF saw a significant growth in scale, increasing by 24.46 million yuan over the past week, leading its peers [2] - The ETF has recorded continuous net inflows over the past four days, with a peak single-day net inflow of 30.01 million yuan, totaling 52.30 million yuan and an average daily net inflow of 13.08 million yuan [1] - Financial analysts believe that the rapid iteration of domestic models is capturing user AI interaction points, which is expected to accelerate the demand for reasoning-side computing power [2] Group 3 - 2026 is projected to be a pivotal year for the deployment of domestic super nodes, with numerous domestic manufacturers releasing next-generation super node solutions [2] - The Xinchuang ETF closely tracks the China Securities Xinchuang Index, emphasizing domestic full-stack replacement and integrating key components such as storage chips, CPUs, and AIPC [2] - The ETF is currently the largest in its category, reflecting strong policy certainty and a comprehensive approach from hardware to industry intelligence [2]

Group 1 - The core point of the article is the launch of the scaleX 30,000-card supercluster system by Zhongke Shuguang, marking the largest domestic AI computing power pool in China, capable of supporting trillion-parameter model training and high-throughput inference [1][3] - The scaleX supercluster represents a significant advancement in the deployment and practical application of domestic AI computing infrastructure, having been showcased at the HAIC conference and operational within two months [3] - Zhongke Shuguang has overcome key technical challenges such as high-speed interconnection, tight coupling of storage and computing, and efficient resource scheduling to enable the scaleX supercluster [3] Group 2 - The AI industry is experiencing explosive growth in global intelligent computing demand, necessitating infrastructure that is ecologically compatible and flexible to support diverse applications [3] - The scaleX supercluster is designed to be compatible with mainstream software ecosystems like CUDA, allowing for mixed deployment of various domestic acceleration cards, thus lowering the adaptation barrier for developers [3] - The supercluster has completed optimization for over 400 mainstream large models and can connect to thousands of applications, fostering a collaborative innovation ecosystem in the AI industry [4] Group 3 - The scaleX supercluster provides deep empowerment across multiple scenarios, including support for trillion-parameter model training and fault recovery, and has enhanced inference efficiency for major internet users [5] - In the AI for Science domain, the supercluster has supported a domestic materials research model that achieved top rankings internationally, significantly improving protein research efficiency by 3 to 6 orders of magnitude [5] - Zhongke Shuguang aims to deepen technological research and application practices, promoting domestic intelligent computing to serve various sectors of economic and social development more efficiently and inclusively [5]

Group 1 - The Digital Economy ETF (工银561220) opened at 1.480 yuan, experiencing a decline of 0.47% [1] - Major holdings in the ETF include companies like SMIC, which fell by 1.48%, and Haiguang Information, which dropped by 1.00% [1] - The ETF's performance benchmark is the China Securities Index for State-Owned Enterprises in the Digital Economy, managed by ICBC Credit Suisse Asset Management [1] Group 2 - Since its inception on May 21, 2025, the ETF has achieved a return of 48.72%, with a monthly return of 0.79% [1]

日前，国家超算互联网核心节点在郑州正式上线试运行，这一全国一体化算力网络的重大基础设施，凭 借3套中科曙光scaleX万卡超集群系统的同步部署，一举成为全国首个实现3万卡规模部署、且可实际投 入运营的最大国产AI算力池。 作为国家部委、河南省、郑州市多方协同发力、重点部署的战略工程，该核心节点的落地承载着打破算 力壁垒、优化资源配置的重要使命，其战略价值不言而喻。此次开创性完成国产万卡超集群的规模化部 署，不仅创下多项业界纪录，更打造了一个可复制、可验证、可普及的国家级算力建设样板间，为全国 一体化算力网络发展提供了宝贵的实践参考。 中科曙光scaleX万卡超集群的三大核心优势，构筑起这一国产算力底座的硬核实力，全方位领跑业界发 展。在集成度上，该集群采用全球首创的高密度单机柜设计，融合超高密度刀片、浸没相变液冷等前沿 技术，将单机柜算力密度提升20倍之多，同时将电能利用效率（PUE）控制在1.04的超低水平，实现了 算力与节能的双向突破，呼应了"双碳"目标下算力基础设施绿色发展的要求。 众所周知，算力作为数字经济时代的核心生产力，堪比农业时代的水利、工业时代的电力，而我国算力 网络建设的核心目标，正是打破算 ...

面对行业算力供给不足、供需脱节、生态不兼容等痛点，该节点搭载的曙光scaleX万卡超集群基于AI计 算开放架构，兼容主流生态、支持多品牌国产加速卡混合部署，已完成400多个主流大模型适配优化， 实现"开箱即用"，大幅降低算力使用门槛；同时，依托国家超算互联网实现一体化算力调度，可接入上 千款应用，为全球用户提供好用易用的中国AI算力。 经济观察网2月5日，国家超算互联网核心节点在郑州上线试运行，该节点采用中科曙光scaleX万卡超集 群，可提供超3万卡国产AI算力，是国家超算互联网平台接入的全国最大单体国产AI算力资源池，可支 撑万亿参数大模型训练、高通量推理、AI for Science等大规模AI计算场景。 ...