中经记者 谭伦 北京报道 筹划近半年的海光信息、中科曙光重组，正式宣告终止。 日前，海光信息（688041.SH）与中科曙光（603019.SH）在投资者说明会上共同披露，因交易规模 大、涉及相关方多，且市场环境较筹划初期发生较大变化，实施条件尚不成熟，经审慎评估决定终止本 次整合。 双方表示，此次重组原意在于推动产业链纵向整合，提升国产算力体系的协同效率与国际竞争力。然 而，鉴于两家公司均为国产算力领域的头部企业，资产体量庞大，方案论证复杂，最终未能达成。公告 指出，双方在终止决策前"到最后一刻仍在积极努力"，但经与各相关方充分论证，最终基于审慎性原则 做出终止决定。 尽管整合之路暂告一段落，但公告也明确提及，双方长期良好的产业协同与合作不受影响。海光信息总 经理沙超群强调，未来将继续专注高端CPU与DCU芯片设计，巩固其作为独立芯片供应商的地位；中 科曙光总经理历军则表示，公司将持续完善"芯片—服务器—液冷—算力服务"全链条布局。 另一方面，市场竞争加剧，华为昇腾、寒武纪等企业加速技术突破，行业呈现"开放协同"与"全栈生 态"双轨并行的格局，如中科曙光推出的scaleX640超节点已实现单机柜640卡互连 ...

Group 1: Company Announcements - Haiyou New Materials plans to establish a wholly-owned subsidiary and invest 300 million yuan in a polymer special adhesive film production project in Chengdu, which aims to optimize resource allocation and production capacity layout [4] - Dekeli's board member plans to reduce holdings by no more than 100,000 shares, representing a reduction of 0.0632% of the company's total shares [5] - Saiwei Microelectronics announced that its actual controller and associated parties plan to reduce their holdings by no more than 1% of the company's total shares [3] Group 2: Technology Developments - Zhongke Shuguang has launched the world's first single-cabinet 640-card super node scaleX640, which can be combined to form a thousand-card computing unit, achieving a 20-fold increase in computing density compared to traditional solutions [5] - Haiguang Information's Haiguang DCU has over 99% operator coverage, compatible with CUDA, and supports a wide range of model training and inference scenarios [5] Group 3: Market Reactions - The Hang Seng Technology Index experienced a significant drop, with major companies like Alibaba, Tencent, JD.com, and Meituan seeing increased declines due to rumors regarding stricter tax recognition for high-tech companies [2] - Xpeng Motors has obtained an L3 autonomous driving road test license in Guangzhou, marking a step towards regular L3 road testing [2] Group 4: Financing Activities - Jiangfan Guizhi completed nearly 100 million yuan in Pre-A round financing to advance the production line construction and technology iteration of silicon-carbon anode materials [6] - Benait completed several million yuan in A++ round financing, focusing on the development and production of silicon-based liquid crystal optical devices [7] - Aosaire Biopharmaceutical completed several million yuan in Pre-A round financing to support the development of new imaging contrast agents and integrated therapeutic drugs [9]

Core Viewpoint - The domestic chip industry in China is undergoing significant transformation, moving from a perception of being "stuck" or "ineffective" to showcasing advancements and capabilities by 2025 [1][3]. Group 1: Consumer Electronics and Automotive - The gaming performance of domestic processors is improving, with the Haiguang C86 processor achieving frame rates of nearly 200 and 300 for major games, indicating readiness for high-performance gaming [2][3]. - The Haiguang C86 processor, featured in the "Black Warrior·Hunting Blade Pro" gaming PC, has a base frequency of 2.8GHz and supports PCIe 5.0, demonstrating its capability to handle high-load tasks [5][6]. - The GAC Aopao GT "Climbing Edition" achieved 100% domestic chip design, utilizing the RK3588M chip for its intelligent cockpit, showcasing the reliability and performance of domestic chips in high-end vehicles [12][13]. Group 2: Storage and Memory Chips - Changxin Storage launched DDR5 products with speeds up to 8000Mbps, marking a significant advancement for domestic manufacturers in the high-end memory market [9][10]. - The introduction of DDR5 technology represents a leap from DDR4, with performance improvements and the ability to address high-frequency signal interference [10][11]. - Longjiang Storage's TiPlus7100s SSD achieved read speeds of 7400MB/s and write speeds of 6900MB/s, indicating competitive performance against international brands [11]. Group 3: AI and Computing Power - The exit of international giants from the AI chip market has created opportunities for domestic companies, with Cambrian Technologies reporting a 1332.52% year-on-year revenue increase in Q3 2025 [15][16]. - Domestic firms are adopting "super node" technology to enhance computing power by integrating multiple AI acceleration cards into a single cabinet, addressing performance bottlenecks in large model training [17][18]. - The demand for storage has shifted from being a cost component to a strategic asset, with significant implications for the supply chain and market dynamics [18][19]. Group 4: Semiconductor Manufacturing and Equipment - Domestic companies are making strides in semiconductor manufacturing equipment, with the shipment of a 350nm lithography machine that supports the production of power devices and RF chips [23][24]. - The development of high-speed oscilloscopes and EDA tools is filling critical gaps in the chip design and testing process, enhancing the capabilities of domestic semiconductor firms [25][26]. - The Chinese semiconductor industry is transitioning from "point breakthroughs" to "chain collaboration," indicating a shift towards more integrated and cooperative development efforts [20][27].

Core Insights - The article highlights significant advancements in the domestic chip industry, showcasing breakthroughs in gaming, automotive, and AI sectors, indicating a shift from reliance on foreign technology to a more self-sufficient and competitive domestic market [2][3][4]. Group 1: Gaming and Consumer Electronics - The domestic chip, Haiguang C86, demonstrated impressive performance in gaming, achieving frame rates of nearly 200 and 300 for major titles, indicating its capability to meet high-performance gaming demands [2]. - Thunderobot's new gaming PC, featuring the Haiguang C86 processor, marks a significant entry into the consumer gaming market, showcasing the processor's specifications that support high-performance tasks [5][6]. - The shift in perception of domestic chips from being seen as inferior to now being recognized for their performance and compatibility with mainstream software and games is emphasized [6]. Group 2: Automotive Sector - The GAC Aopao GT "Climbing Edition" achieved 100% domestic chip design, utilizing the RK3588M chip from Rockchip, which supports advanced features like multi-screen interaction and 3D rendering [11][12]. - The introduction of domestic chips in high-end vehicles signifies their ability to meet stringent performance and reliability standards required in the automotive industry [12]. Group 3: AI and Computing - The domestic AI chip market is experiencing a surge, with companies like Cambricon reporting significant revenue growth, indicating a shift in market dynamics following the exit of international competitors [15][16]. - The adoption of "super node" technology by domestic firms aims to enhance computing power by integrating multiple AI acceleration cards, addressing the challenges of performance and efficiency in AI training [16]. - The need for cost-effective solutions in AI computing is highlighted, with innovations that significantly reduce hardware costs for training large models [17]. Group 4: Storage and Memory - Changxin Storage's launch of DDR5 products marks a significant advancement in domestic memory technology, achieving speeds of up to 8000 Mbps, thus entering the high-end market previously dominated by international brands [9][10]. - The demand for high-performance storage solutions is increasing, with domestic manufacturers stepping up to fill the gap left by international suppliers [18][19]. Group 5: Semiconductor Manufacturing and Materials - The development of domestic semiconductor manufacturing equipment, such as the AST6200 lithography machine, represents a crucial step towards self-sufficiency in chip production [23]. - The emergence of domestic materials for semiconductor manufacturing, like those produced by Hengkun New Materials, indicates progress in reducing reliance on foreign suppliers [24]. - Innovations in testing equipment and EDA tools are also being made, with companies like Wanliyan Technology and Huada Jiutian leading efforts to enhance domestic capabilities in chip design and testing [25][26]. Group 6: Industry Challenges and Future Directions - Despite advancements, the domestic chip industry faces challenges in high-end manufacturing and the need for substantial R&D investment to keep pace with global competitors [27][28]. - The article concludes that while the domestic chip industry has made significant strides, ongoing investment and innovation are essential to overcome existing gaps and achieve long-term competitiveness [28].

Core Viewpoint - China Mobile has awarded a procurement project for a super node testing device to Huawei, with a bid of 135 million yuan, indicating a significant investment in advanced computing infrastructure [1] Group 1: Huawei's Innovations - Huawei's "Scale-up super large-scale super node computing platform" was recognized as its top invention, showcasing a new architecture that allows for flexible resource allocation among AI processors [1] - The Ascend 384 super node features 384 Ascend NPUs and 192 Kunpeng CPUs, achieving a total computing power of 300 Pflops, which is 1.7 times that of NVIDIA's NVL72 [2] - The total network bandwidth of the Ascend 384 super node reaches 269 TB/s, surpassing NVIDIA's NVL72 by 107% [2] Group 2: Industry Trends - The demand for computing power in large models is rapidly increasing, while traditional computing architectures face challenges such as low resource utilization and frequent failures [4] - Super nodes are emerging as a new norm in AI infrastructure, with several domestic manufacturers exploring super node systems [4] - Inspiring innovations include the launch of the world's first single-cabinet 640-card super node by Sugon, which enhances computing density by 20 times compared to traditional solutions [4][5] Group 3: Future Developments - Huawei plans to launch the Atlas 950 super node in Q4 2026, featuring 8192 Ascend 950DT chips and achieving FP8 computing power of 8 EFLOPS [12] - The Atlas 950 super node is projected to be significantly more powerful than NVIDIA's upcoming NVL144, with a total computing power 6.7 times greater and memory capacity 15 times larger [14] - Future plans include the Atlas 950 SuperCluster, which will consist of 64 Atlas 950 super nodes, achieving a total FP8 computing power of 524 EFLOPS, surpassing the current largest cluster, xAI Colossus [14]

Core Viewpoint - DeepSeek has officially released versions V3.2 and V3.2-Speciale, significantly enhancing its Agent capabilities and integrating reasoning and thinking [1] Group 1: Product Development - The new versions of DeepSeek are based on China's first AI computing open architecture, achieving "cross-layer collaboration" across hardware, software, and model layers [1] - The products, including the Shuguang AI supercluster system and scaleX640 super nodes, have completed deep adaptation and tuning for the new DeepSeek versions [1] Group 2: Market Application - The enhancements in DeepSeek support full-scale deployment for clients across various industries [1]

公司首次授予激励对象 公司于2025 年11 月21 日召开董事会，审议通过了《关于向激励对象首次授予限制性股票的议案》，同 意确定2025 年11 月21 日为首次授予日，并同意以90.25 元/股的授予价格向符合授予条件的878 名激励 对象授予1653.54 万股限制性股票，约占本激励计划草案公告时公司股本总额的0.71%。 截至2025 年6 月30 日，公司共有员工2803 人，激励对象占比超30%。本次激励授予范围广，股权价值 高，回报力度大，有利于加深员工与公司的深度绑定，巩固核心人才壁垒，为公司长期发展注入持久动 能。 算力领军企业的强强联合或将实现技术发展成果的共享，促进产业链上下游优质资源的整合，进一步推 动国产算力做大做强。 盈利预测与估值 我们预计公司25-27 年分别实现收入142.1 亿、207.0 亿、291.5 亿，同比增速为55%、46%、41%；归属 母公司股东的净利润为29.8 亿、43.4 亿、64.1 亿。对应25-27 年PE 估值分别为161、111、75 倍，维 持"买入"评级。 风险提示 产品研发不及预期、下游需求不及预期、业绩增长不及预期、政策落地不及预期、 ...

Core Viewpoint - Zhongke Shuguang's Q3 2025 report shows impressive performance with steady revenue growth and a significant year-on-year increase in net profit excluding non-recurring items [1] Group 1: Financial Performance - The company reported robust revenue growth and a substantial increase in net profit year-on-year [1] - The non-recurring net profit showed a high growth rate compared to the previous year [1] Group 2: Product Development - Zhongke Shuguang recently launched the scaleX640 super node, which significantly enhances single cabinet computing power density [1] - The new product supports multiple brand acceleration cards and mainstream computing ecosystems, potentially establishing a new paradigm for domestic intelligent computing [1] Group 3: Strategic Initiatives - The company is actively advancing the merger with Haiguang Information, aiming to create a leading domestic computing power industry chain [1] - The goal is to achieve deep integration and synergy from chips to services, which is expected to significantly enhance core competitiveness [1] Group 4: Investment Rating - The company maintains a "buy" rating based on its strong performance and strategic initiatives [1]

Core Viewpoint - The article discusses the emergence and significance of the "SuperNode" concept in the AI computing market, highlighting the competitive landscape among domestic manufacturers aiming to match or surpass Nvidia's offerings [1][11]. Group 1: SuperNode Concept - The term "SuperNode" refers to high-performance computing systems that integrate multiple AI training chips within a single cabinet, enabling efficient parallel computing [5][7]. - Domestic manufacturers have rapidly adopted the SuperNode concept, with various companies showcasing their solutions at industry events, indicating a collective push towards advanced AI computing capabilities [2][4]. Group 2: Performance Metrics - Companies are emphasizing the performance metrics of their SuperNode products, with Huawei's 384 SuperNode reportedly offering 1.67 times the computing power of similar Nvidia devices [3][12]. - The scale of integration, indicated by numbers like "384" or "640," reflects the number of AI training chips within a single system, serving as a key performance indicator for manufacturers [7][8]. Group 3: Challenges and Solutions - The industry faces a "communication wall" where a significant portion of computing time is spent waiting for data transfer, necessitating the development of SuperNodes to enhance communication efficiency [6][9]. - The transition from traditional computing methods to SuperNode architectures is driven by the need for higher performance in training large AI models, with manufacturers exploring both Scale-Up and Scale-Out strategies [7][8]. Group 4: Competitive Landscape - Domestic firms are positioning their SuperNode products against Nvidia's offerings, with Huawei's Atlas950 expected to outperform Nvidia's NVL144 in several key metrics [11][12]. - The competition is not only about performance but also about innovative engineering solutions to manage power consumption and heat dissipation in densely packed systems [13][15]. Group 5: Market Demand - The primary demand for AI computing resources is expected to come from large internet companies and state-led cloud services, which are likely to drive the market in the next few years [20][21]. - There are concerns about the sustainability of this demand, as companies may face challenges in justifying high capital expenditures for advanced computing resources [21][22]. Group 6: Future Outlook - The article suggests that while hardware challenges exist, the real test for domestic manufacturers will be in developing robust software ecosystems to support their SuperNode offerings [19][22]. - There is optimism about the potential for AI applications in sectors like robotics and advanced manufacturing, which could drive sustained demand for high-performance computing solutions [22].

Core Insights - The AI computing power market is increasingly focused on "SuperNode" technology, with multiple companies showcasing their solutions at various conferences throughout 2023 [2][3] - The emergence of SuperNodes is driven by the need to overcome bottlenecks in training large AI models, particularly the "communication wall" that arises during parallel computing [4][9] - Domestic companies are adopting SuperNode technology as a practical solution to enhance overall computing power, compensating for limitations in single-chip performance [10][12] Group 1: SuperNode Technology - SuperNode refers to a high-density computing solution that integrates multiple AI chips within a single cabinet, allowing them to function as a unified system [6][7] - The design of SuperNodes involves two main approaches: Scale-Up, which increases resources within a single cabinet, and Scale-Out, which connects multiple cabinets [5][8] - The numbers associated with SuperNodes (e.g., "384", "640") indicate the number of AI training chips integrated within a single system, serving as a key metric for performance and density [7][8] Group 2: Industry Competition - Companies like Huawei and Inspur are positioning their SuperNode products as superior to NVIDIA's offerings, with Huawei claiming its Atlas 950 will outperform NVIDIA's NVL144 in multiple performance metrics [10][11] - The competitive landscape is marked by aggressive parameter comparisons, with domestic firms striving to achieve higher integration density within their SuperNode solutions [12][14] - The engineering challenges of integrating numerous high-power chips into a single cabinet necessitate advanced cooling and power supply technologies [12][14] Group 3: Market Demand and Challenges - The primary demand for AI computing power is expected to come from large internet companies and state-led cloud services, which have the infrastructure to support high-end computing needs [19][20] - Despite the strong demand, there are concerns about the sustainability of investments in AI computing infrastructure, particularly regarding the potential for overbuilding [20][22] - The software ecosystem remains a significant challenge for domestic manufacturers, as effective software solutions are crucial for the successful deployment of high-density computing systems [18][22]