Core Insights - The company reported a revenue of 2.351 billion yuan for the first half of 2025, representing a year-on-year growth of 2.19% [1] - The net profit attributable to shareholders reached 373 million yuan, showing a significant increase of 25.33% year-on-year [1] - Operating cash flow net amount was 376 million yuan, reflecting a robust growth of 52.41% compared to the previous year [1] Business Development - The company achieved notable progress in overseas market expansion, security business development, and technological innovation [1] - It actively expanded into Southeast Asia and the Middle East, establishing a subsidiary in Dubai to enhance overseas service capabilities [1] - The company focused on its core businesses of CDN and edge computing, optimizing its business structure by divesting from MSP operations and selling shares in Cloudsway Pte. Ltd. [1] Security Business - The security business segment generated revenue of 646.71 million yuan in the first half of 2025, marking a year-on-year increase of 13.96% [1] - The company launched a deep assessment service for large model security, providing a comprehensive security solution for large language models and AI applications [2] - The company was positioned as a leader in the IDC MarketScape for Chinese intelligent security access service edge vendors in 2025 [2] Technological Innovation - The company upgraded its next-generation edge AI platform, focusing on a four-layer capability matrix of "resources-model-services-applications" [2] - It developed core products such as edge AI gateways, edge model inference, and edge AI applications, enhancing its technical strength and market competitiveness in edge computing [2] - The company introduced a restricted stock incentive plan in 2025, with share-based payment costs amounting to 65.58 million yuan, an increase of 19.10 million yuan year-on-year [2] Company Overview - Founded in January 2000, the company aims to become a global leader in IT infrastructure services [2] - It leverages core technologies and service capabilities in computing, storage, networking, and security to provide efficient, stable, and secure IT infrastructure and services for internet, government, and enterprise clients [2]

本报讯 （记者谢岚）8月14日晚，网宿科技股份有限公司（以下简称"网宿科技"）发布了2025年半年 报。报告期内，公司实现营业收入23.51亿元，同比增长2.19%；实现毛利额7.86亿元，同比增长 7.71%；实现归属于上市公司股东的净利润3.73亿元，同比增长25.33%；实现扣非净利润2.61亿元，同 比增长22.53%。报告期内，公司首次披露了安全业务营收，安全及增值服务收入6.45亿元，同比增长 13.96%。营收和净利润的双增既体现了公司核心业务护城河的扎实根基和抗风险能力，也反映出公司 具备优质稳健的运营能力。 公司秉承深耕主业，精细化运营的经营思路，全面聚焦CDN及边缘计算、安全两大核心业务。对于业 绩增长原因，报告可以归结为两个方面，一是首次披露的安全业务营收凸显，二是海外业务稳步发展。 边缘AI平台进阶 网络资源100%覆盖全球 报告期内，网宿科技升级新一代边缘AI平台，以"资源-模型-服务-应用"四层能力矩阵为核心，打造边缘 AI网关、边缘模型推理、边缘AI应用等核心产品，构建AI落地全链路能力体系。其次，边缘AI平台全 面支持MCP协议，推出一站式MCP协议转换+边缘托管服务，0门槛打 ...

子品牌网宿安全自2011年启动安全战略，陆续推出云抗D、云WAF、SD-WAN等拳头产品，得到了市场 的有效验证。2021年实现安全品牌升级，宣布投入10亿专项资金，并提出"体系化主动安全"理念，先后 升级体系化安全解决方案，包括WAAP(Web应用与API保护)、SASE(安全访问服务边缘)，以及综合安 全服务等核心产品服务，从而更深入企业业务。这也标志着网宿安全从防护型厂商向综合服务型厂商的 迈进，当前网宿安全已具备覆盖云、网、端、应用等多维度的防护能力。 报告期内，安全业务发布了大模型安全深度评估服务，覆盖模型输出安全、数据安全、算法安全及应用 安全多维度，助力企业构建AI智能体应用生态。升级一体化全球安全加速方案，突破地理围栏，助力 出海企业实现全球一致的访问与安全体验。基于"安全有效性验证理念"，推出《网络安全体检服务方 案》，实现企业全栈检测+治理闭环，量化企业投入比。上半年，网宿安全入选了《IDC MarketScape: 中国智能安全访问服务边缘(SASE)2025年厂商评估》领导者象限。 公开信息显示，上半年，网宿SASE服务继续为医药健康、服装、高校及教育机构、新闻资讯、央国企 等多个行业 ...

Core Insights - The competition in the AI large model sector is shifting towards AI inference, marking the beginning of the AI inference era, with edge computing emerging as a new battleground in this field [1][2]. AI Inference Era - Major tech companies have been active in the AI inference space since last year, with OpenAI launching the O1 inference model, Anthropic introducing the "Computer Use" agent feature, and DeepSeek's R1 inference model gaining global attention [2]. - NVIDIA showcased its first inference model and software at the GTC conference, indicating a clear shift in focus towards AI inference capabilities [2][4]. Demand for AI Inference - According to a Barclays report, the demand for AI inference computing is expected to rise rapidly, potentially accounting for over 70% of the total computing demand for general artificial intelligence, surpassing training computing needs by 4.5 times [4]. - NVIDIA's founder Jensen Huang predicts that the computational power required for inference could exceed last year's estimates by 100 times [4]. Challenges and Solutions in AI Model Deployment - Prior to DeepSeek's introduction, deploying and training AI large models faced challenges such as high capital requirements and the need for extensive computational resources, making it difficult for small and medium enterprises to develop their own ecosystems [4]. - DeepSeek's approach utilizes large-scale cross-node expert parallelism and reinforcement learning to reduce reliance on manual input and data deficiencies, while its open-source model significantly lowers deployment costs to the range of hundreds of calories per thousand calories [4]. Advantages of Edge Computing - AI inference requires low latency and proximity to end-users, making edge or edge cloud environments advantageous for running workloads [5]. - Edge computing enhances data interaction and AI inference efficiency while ensuring information security, as it is geographically closer to users [5][6]. Market Competition and Player Strategies - The AI inference market is rapidly evolving, with key competitors including AI hardware manufacturers, model developers, and AI service providers focusing on edge computing [7]. - Companies like Apple and Qualcomm are developing edge AI chips for applications in AI smartphones and robotics, while Intel and Alibaba Cloud are offering edge AI inference solutions to enhance speed and efficiency [7][8]. Case Study: Wangsu Technology - Wangsu Technology, a leading player in edge computing, has been exploring this field since 2011 and has established a comprehensive layout from resources to applications [8]. - With nearly 3,000 global nodes and abundant GPU resources, Wangsu can significantly improve model interaction efficiency by 2 to 3 times [8]. - The company's edge AI platform has been applied across various industries, including healthcare and media, demonstrating the potential for AI inference to drive innovation and efficiency [8].