Investment Rating - The report maintains a "Buy" rating for the computer industry, specifically for companies like Kingsoft Office, Tonghuashun, and Yonyou Network [7][10][26]. Core Insights - DeepSeek has opened its Infra core code, enhancing model efficiency and hardware compatibility, particularly with domestic GPUs, which is expected to lower application costs and improve performance [1][2][3]. - The report highlights a divergence in strategies between domestic and overseas model companies, with overseas firms focusing on large computing power while domestic firms prioritize efficiency optimization [4]. - The potential for model capabilities to become fundamental resources akin to "water and electricity" is emphasized, suggesting significant advantages for companies leveraging these capabilities [5]. Summary by Sections Investment Rating - The report provides a "Buy" rating for Kingsoft Office (688111 CH), Tonghuashun (300033 CH), and Yonyou Network (600588 CH) with target prices of 351.05, 425.23, and 16.12 respectively [10][26]. DeepSeek Developments - DeepSeek's recent open-source initiatives include core optimizations in MLA, communication-computation, and matrix multiplication, which are expected to enhance global model training and inference efficiency [2][3]. - The report notes that DeepSeek's model training has been optimized for CUDA, with successful adaptations for domestic GPUs, indicating a growing ecosystem for local chip manufacturers [3]. Market Dynamics - The report identifies a trend where overseas companies like xAI and OpenAI are expanding their GPU clusters to enhance performance, while domestic companies are focusing on software and hardware efficiency improvements [4]. - The analysis suggests that the cost-profit margin for DeepSeek's services could reach 545% under optimal conditions, highlighting the financial viability of its model [1][22]. Recommended Companies - Companies with user, data, and scenario advantages are recommended, including Kingsoft Office, Tonghuashun, and Yonyou Network, as well as other relevant players in the 2B and 2C application sectors [5][10][26].

Investment Rating - The industry investment rating is "stronger than the market" (预计6个月内，行业指数表现强于市场表现5%以上) [32] Core Views - The DeepSeek open-source week has concluded, accelerating the application of large models across various industries [2][3] - The competition among global large models remains intense, providing strong support for the continuous growth of AI computing power [8][11] - NVIDIA's FY25Q4 performance is strong, with robust demand on the inference side of the Blackwell architecture [13][15] Summary by Sections Industry News and Commentary - The DeepSeek open-source week launched five open-source software library projects covering computation, communication, and storage, which will facilitate the replication of DeepSeek-V3/R1 by global developers [2][5] - The release of models like Grok-3, Claude 3.7 Sonnet, and GPT-4.5 indicates ongoing fierce competition in the global large model market, which is expected to elevate the capabilities of these models [9][11] - NVIDIA reported FY25Q4 revenue of $39.3 billion, a 12% quarter-over-quarter increase and a 78% year-over-year increase, driven primarily by data center business growth [13][14] Investment Recommendations - The report suggests a positive outlook for the computer industry, anticipating dual improvements in performance and valuation due to accelerating demand recovery [28] - Recommended stocks include: - Innovation and Creation Sector: Haiguang Information, Longxin Zhongke, Zhongke Shuguang, Kingsoft Office, Dameng Data, Foxit Software, Taiji Co., Ltd. - Huawei Supply Chain: Digital China, with a focus on Tuo Wei Information, Kirin Information Security, Runhe Software, and others - AI Sector: Strong recommendations for Zhongke Chuangda, Shengshi Technology, and Qiming Star, among others - Low-altitude Economy: Recommended stocks include Da Tong Technology and others - Financial IT Sector: Strong recommendation for Hengsheng Electronics, with additional suggestions for Tonghuashun and others [28]

Core Insights - DeepSeek's "Open Source Week" has successfully concluded, showcasing its commitment to transparency and collaboration in the AI field [1][7]. Group 1: Open Source Projects - The "Open Source Week" launched five projects from February 24 to February 28, covering various aspects of computing, communication, and storage [3]. - On February 24, the first open-source library, FlashMLA, was released, optimized for Hopper GPU, focusing on variable-length sequences and is now in production [4]. - On February 25, DeepEP was announced for public access, designed for MoE model training and inference, enabling efficient all-to-all communication and supporting low-precision operations [4]. - On February 26, DeepGEMM was open-sourced, a library for FP8 general matrix multiplication, featuring fine-grained scaling and supporting both standard and MoE group GEMM [5]. - On February 27, two tools (DualPipe and EPLB) and a performance analysis dataset were released, along with detailed explanations of parallel computing optimization techniques [5]. - On February 28, the release of 3FS was announced, which serves as an accelerator for all DeepSeek data access [6]. Group 2: API and Pricing Adjustments - DeepSeek reopened its API recharge function on February 25 after a 19-day suspension, accompanied by a structural adjustment in pricing [9]. - The pricing for the DeepSeek-chat based on the V3 model is set at 2 yuan per million input tokens and 8 yuan per million output tokens, while the DeepSeek-reasoner based on the R1 model is priced at 4 yuan per million input tokens and 16 yuan per million output tokens [9]. - On February 26, a peak-shifting discount pricing strategy was introduced, with significant reductions during specific hours, offering V3 at 50% off and R1 at 25% off [10]. Group 3: Market Impact - According to CITIC Securities, DeepSeek's open-source initiatives are expected to catalyze the AI+ theme, enhancing AI penetration across various industries and increasing demand for computing power [7].