Group 1 - The Terahertz concept sector increased by 2.90%, ranking fifth among concept sectors, with 22 stocks rising, including Sifang Electronics which hit the daily limit, and others like Leike Defense and Yaguang Technology showing significant gains of 7.69% and 7.46% respectively [1] - The top gainers in the Terahertz concept sector included Sifang Electronics, ZTE Corporation, and Yaguang Technology, with net inflows of 9953.89 million, 7174.28 million, and 4470.21 million respectively [2][3] - The overall market saw a net inflow of 2.02 billion into the Terahertz concept sector, with 13 stocks receiving net inflows, and 6 stocks exceeding 3000 million in net inflows [1] Group 2 - The leading stocks by net inflow ratio included Sifang Electronics at 17.39%, Tongfang Co. at 10.47%, and Yaguang Technology at 9.35% [2] - The trading volume and turnover rates for the top stocks in the Terahertz concept sector were notable, with Sifang Electronics showing a turnover rate of 7.20% and ZTE Corporation at 1.79% [2][3] - The stocks with the largest declines included Juguang Technology and Shuo Beid, with declines of 0.80% and 0.07% respectively [1]

证券代码（A/H）：000063/00763 证券简称(A/H)：中兴通讯 公告编号：202544 中兴通讯股份有限公司 关于按照《香港上市规则》公布 2025 年 4 月份证券变动月报表的公告 本公司及董事会全体成员保证信息披露的内容真实、准确和完整，没有虚假记载、误导 性陈述或重大遗漏。 中兴通讯股份有限公司根据《香港联合交易所有限公司证券上市规则》（简 称"《香港上市规则》"）规定，在香港联合交易所有限公司披露易网站 （www.hkexnews.hk）刊登了截至 2025 年 4 月 30 日的证券变动月报表。 根据《深圳证券交易所股票上市规则》关于境内外同步披露的要求，特将有 关公告同步披露如下，供参阅。 特此公告。 呈交日期: 2025年5月7日 I. 法定/註冊股本變動 | 1. 股份分類 | 普通股 | 股份類別 | H | | | 於香港聯交所上市 (註1) | 是 | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 證券代號 (如上市) | 00763 | 說明 | | | | | | | | | | 法定/註冊股份數目 ...

Group 1 - The Zhongzheng Guangdong-Hong Kong-Macao Greater Bay Area Development Theme Index (931000) increased by 0.25% as of May 7, 2025, with notable gains from Huali Group (300979) up 4.64% and Guangdong Hongda (002683) up 4.52% [2] - The Greater Bay Area ETF (512970) rose by 1.02%, marking its third consecutive increase, with the latest price at 1.18 yuan and a total scale reaching 67.06 million yuan, a new high in nearly a month as of May 6 [2] - As of April 30, 2025, the top ten weighted stocks in the Zhongzheng Guangdong-Hong Kong-Macao Greater Bay Area Development Theme Index accounted for 53.26% of the index, including BYD (002594) and China Ping An (601318) [7] Group 2 - As of the end of 2024, only 46.34% of the market value of listed state-owned enterprises in Shandong Province experienced growth, with only one enterprise exceeding a market value of 100 billion yuan showing an increase [4] - The Shandong State-owned Assets Supervision and Administration Commission signed a memorandum of cooperation with the Shandong Securities Regulatory Bureau to encourage state-owned enterprises to enhance investment value through share buybacks, increased dividends, and other measures [4] Group 3 - The state-owned enterprise co-win ETF (159719) includes various stocks with notable weightings such as China Petroleum (601857) at 15.58% and China Shenhua (601088) at 2.91% [6] - The performance of major stocks in the state-owned enterprise ETF shows slight increases, with China Petroleum up 1.13% and China Mobile (600941) up 0.39% [6]

沪指5月6日上涨1.13%，申万所属行业中，今日上涨的有30个，涨幅居前的行业为计算机、通信，涨幅 分别为3.65%、3.59%。通信行业位居今日涨幅榜第二。跌幅居前的行业为银行，跌幅分别为0.13%。 通信行业资金流出榜 | 代码 | 简称 | 今日涨跌幅（%） | 今日换手率（%） | 主力资金流量（万元） | | --- | --- | --- | --- | --- | | 688313 | 仕佳光子 | 11.14 | 13.50 | -11185.56 | | 600941 | 中国移动 | 0.72 | 1.06 | -10553.64 | | 300570 | 太辰光 | 6.82 | 11.22 | -8451.44 | | 600522 | 中天科技 | 1.08 | 1.17 | -3375.26 | | 300502 | 新易盛 | 4.28 | 6.14 | -2352.35 | | 603602 | 纵横通信 | 1.87 | 3.56 | -2308.74 | | 601728 | 中国电信 | 1.17 | 0.17 | -1399.92 | | 688182 | 灿勤科技 | ...

Core Insights - The industry is expected to experience accelerated development in AI inference driven by DeepSeek, with over a hundred intelligent computing integrated machines already in the market, although challenges in practical applications remain [2][6] - ZTE Corporation outlined its strategic plans in AI, focusing on infrastructure, enterprise business development, and the application of intelligent computing capabilities during the 2025 ZTE China Ecosystem Partner Conference [2] AI Market Growth - According to IDC, the global AI market is projected to exceed $800 billion by 2028, with a compound annual growth rate (CAGR) of over 32% over the next five years [2] - Domestic operators have indicated that computing power investments will maintain growth of over 20% by 2025, with leading internet companies expected to invest over 500 billion yuan in AI over the next three years, indicating significant growth potential for ICT infrastructure [2] ZTE's AI Strategy - ZTE's strategy in AI focuses on three main areas: infrastructure, edge deployment, and application innovation [4] - The company is advancing ICT infrastructure solutions through innovations in 5G-A, 6G, and optical network technologies, integrating heterogeneous computing power with large model technologies [4] - ZTE has introduced a series of intelligent computing servers and energy solutions, along with a self-developed unified cloud management platform for efficient scheduling of heterogeneous computing resources [4] Enterprise Business Development - ZTE's enterprise business, viewed as its "second curve," is driven by the dual forces of digital transformation across industries and domestic policies promoting localization [5] - The company aims for a nearly 60% year-on-year growth in its domestic enterprise business by 2024, with a projected doubling of revenue in the first quarter of 2025 [5] - ZTE is focusing on key sectors such as internet, finance, and energy, leveraging agile models to enhance its market presence [5] AI Application Demand - This year is considered a significant year for AI applications, with over a hundred intelligent computing integrated machines launched, driven by DeepSeek's deployment in various vertical industries [6] - DeepSeek has significantly lowered the barriers to AI application, allowing users to train models using intelligent computing integrated machines [6] - The demand for AI inference capabilities has surged, with DeepSeek's models being comparable to those released by OpenAI, indicating a rapid evolution in AI applications [6] Challenges in AI Implementation - Despite the growth, industry clients face challenges such as severe internet data pollution, difficulties in data sharing, and high costs of data collection [7] - ZTE has upgraded its digital cloud platform to address these challenges, enhancing data management and utilization through digital matrices and intelligent platforms [7] - The upgraded platform aims to bridge the "last mile" in AI implementation, ensuring that AI solutions are effectively integrated into business operations [7]

Group 1 - The rapid development of AI is increasingly emphasizing its application in home scenarios, expanding the market space from "network" to "network-computing-screen" [2] - The four key components of AI smart home products are AI home network, AI home computing, AI home smart screens, and AI home robots, which create a closed loop of "perception-computation-interaction-execution" [2] - The transition from single-point mechanical devices in the feature phone era to IoT-connected devices in the smart phone era, and now to AI-native devices that provide proactive services, marks a significant evolution in home technology [2] Group 2 - ZTE has launched the Wentiant series WiFi 7 routers, which support dual 2.5G ports and dual WAN functions, addressing the need for data processing capabilities in home computing products [3] - The current focus is on weak computing power products, with a strategy to handle local privacy computing issues through a cloud-based approach, offering a better experience at a lower cost [3] - The introduction of FTTR all-optical smart screens is part of ZTE's strategy to enhance home computing capabilities [3] Group 3 - ZTE has released a two-in-one cloud laptop and a 5G free screen, which leverage cloud computing to overcome the limitations of personal data and hardware devices [4] - The cloud computer market is rapidly growing, with a potential sales space of over 10 million units in China, redefining traditional computers by integrating cloud, network, AI, and terminal components [5] - The focus on cloud computing is expected to lead to a significant transformation in the PC industry, with the potential for low-cost sharing and high network support in home environments [5] Group 4 - ZTE is concentrating on the companionship and safety sectors within the AI home robot market, which is still in its early stages [5]

Core Viewpoint - The article discusses the development of a novel method for generating high-quality Chain of Thought (CoT) data, focusing on the adaptive difficulty grading of questions for large language models (LLMs) to enhance the reasoning capabilities of smaller models [2][6][41]. Group 1: Research Motivation and Challenges - The emergence of large models like DeepSeek-R1 (671 billion parameters) has highlighted the challenges of deploying such models in real-time systems and edge devices [6]. - There is a pressing need for research on smaller models with fewer than 7 billion parameters, particularly in complex reasoning tasks such as mathematical problem-solving and code generation [7]. - Current CoT data generation methods face challenges, including high computational and annotation costs associated with large-scale data-driven approaches and limited performance gains from high-quality sample-driven methods [8][9]. Group 2: Proposed Methodology - The article introduces a new method called "LLM Adaptive Question Difficulty Grading," which aims to improve the quality of CoT data by dynamically matching model capabilities with data difficulty [12][13]. - The method includes four key innovations: establishing a question difficulty grading system based on inherent model reasoning capabilities, creating an adaptive question bank, designing a difficulty distribution sampling strategy, and generating high-quality CoT data using DeepSeek-R1 [15][18]. Group 3: Experimental Results - The proposed method has shown significant improvements in reasoning performance across various model sizes, with accuracy increases ranging from 6.66% to 26.7% on the AIME24 mathematics competition dataset compared to traditional non-adaptive strategies [18][20]. - Detailed experimental results indicate that models trained with the adaptive CoT data outperform baseline models in multiple mathematical reasoning benchmarks, achieving up to 94.6% accuracy on MATH500 [37]. - The ZCode-32B model demonstrated superior performance across different difficulty levels, indicating that smaller models can achieve competitive results through adaptive data training [38]. Group 4: Conclusion and Future Work - The article concludes that the proposed framework for generating high-quality CoT data is efficient and effective, requiring only about 2,000 high-quality samples to significantly enhance model performance while reducing data and computational costs [41]. - Future work will focus on further integrating reinforcement learning to explore deeper reasoning capabilities and extending applications to more complex cross-domain tasks such as communication fault diagnosis [42].

香港交易及結算所有限公司及香港聯合交易所有限公司對本公告的內容概不負責，對其準確性或完整 性亦不發表任何聲明，並明確表示，概不對因本公告全部或任何部份內容而產生或因倚賴該等內容而 引致的任何損失承擔任何責任。 ZTE CORPORATION 中興通訊股份有限公司 （於中華人民共和國註冊成立的股份有限公司） （股份代號：00763） 須予披露交易 本公司第九屆董事會第四十一次會議及二零二四年度股東大會審議通過《二零二五年度擬使用自有 資金進行委託理財的議案》，同意授權本集團 2025 年度使用自有資金在銀行、證券公司、基金公司 等金融機構購買安全性高、流動性好、中低風險的理財產品，資金總額不超過 300 億元人民幣，在 此額度內可滾動使用，期限內任一時點的交易金額不超過上述投資額度，授權有效期自本公司二零 二四年度股東大會審議通過之日起至二零二五年度股東大會召開之日止。 茲提述本公司於 2024 年 9 月 9 日發佈的《須予披露交易-認購理財產品》，內容有關於 2024 年 5 月 9 日至 2024 年 9 月 9 日期間，本公司及附屬公司中興康訊共認購 6 筆杭州銀行理財產品，認購金額 合計為 70 億元 ...

Investment Rating - The report maintains a "Buy" rating for the company, indicating an expected stock price increase of over 15% relative to the industry index in the next six months [4]. Core Viewpoints - The company is experiencing steady revenue recovery, with a projected revenue of 124.25 billion yuan in 2023, slightly increasing to 150.12 billion yuan by 2027, reflecting a compound annual growth rate (CAGR) of approximately 7.5% from 2025 to 2027 [1]. - The net profit attributable to the parent company is expected to decline from 9.33 billion yuan in 2023 to 8.43 billion yuan in 2024, before gradually increasing to 9.46 billion yuan by 2027, indicating a focus on long-term growth despite short-term challenges [1]. - The company is undergoing a structural transformation, shifting from a primary focus on operator networks to a collaborative development model involving "network + computing power + terminals," with over 35% of revenue coming from the second curve business [2][3]. Financial Summary - Revenue is projected to decrease by 2.4% in 2024, followed by a recovery with a growth rate of 7.0% in 2025 and maintaining similar growth rates through 2027 [1]. - The gross margin is under pressure during the transformation phase, with a reported gross margin of 34.27% in Q1 2025, down 7.75 percentage points year-on-year, primarily due to intense competition in the computing power and terminal markets [2]. - The company anticipates that the computing power business will become a major growth driver, particularly with the launch of DeepSeek, which is expected to shift demand from training to inference, thus expanding the market size [2]. Earnings Forecast - The forecasted net profit for the company is 8.58 billion yuan in 2025, 8.88 billion yuan in 2026, and 9.46 billion yuan in 2027, with corresponding price-to-earnings (P/E) ratios of 17.5, 16.9, and 15.9 respectively [3][4].

Core Insights - The development of large AI models is driving a significant increase in demand for computing power, with a projected annual growth rate of 10 times as AI evolves from version 1.0 to 2.0 [1] - ZTE Corporation has established a dual-driven strategy of "Connectivity + Computing Power" to become a leader in the "network connectivity + intelligent computing power" sector, emphasizing the importance of AI integration in various industries [3][4] - The global AI market is expected to exceed $800 billion by 2028, with a compound annual growth rate (CAGR) of over 32%, indicating substantial investment opportunities in AI technologies [4] Industry Developments - ZTE's revenue for Q1 this year reached 32.97 billion yuan, a year-on-year increase of 7.8%, with over 35% of revenue coming from its second curve business focused on computing power and terminals [5] - The company is focusing on three key areas in AI: enhancing ICT infrastructure solutions, developing AI terminal applications, and promoting AI innovation for broader application [5][6] - ZTE has launched the AiCube DeepSeek intelligent computing integrated machine, which is already being applied in sectors such as education, healthcare, steel, and automotive [5] Challenges and Solutions - Industry clients face challenges such as data pollution, high costs of data collection, and long business cycle times for AI technology updates [9] - ZTE has upgraded its digital cloud platform to address these challenges, facilitating better integration of AI into business operations [9] - The introduction of the "Xingyun Intelligent Agent" marks a new phase in the deployment of enterprise-level intelligent agents, aimed at lowering the technical barriers for AI model commercialization across various industries [10]