Group 1: Company Technology and Products - The company has launched multiple main control chips for UFS, eMMC, SD cards, and high-end USB, utilizing advanced foundry processes and self-developed core IP, resulting in superior performance and power efficiency [3] - The company is one of the few capable of developing UFS4.1 products at the chip level, with its UFS4.1 products outperforming comparable market products in terms of process, read/write speed, and stability [3] - The mSSD product, as an upgraded form of traditional SSD, offers significant market potential due to its compact design and superior physical characteristics, while maintaining performance levels comparable to traditional SSDs [3][4] Group 2: Supply Chain and Market Dynamics - The company has established deep, multi-faceted cooperation with major global storage wafer manufacturers, supported by long-term supply agreements, ensuring a solid foundation for wafer supply [4] - In a structurally tight wafer supply environment, the company has built differentiated supply assurance capabilities and growth potential through its full-stack capabilities in main control chips, firmware algorithms, and packaging testing [4] - The demand for storage is expected to surge due to the expansion of AI infrastructure and the shortage of HDD supply, despite limited short-term contributions from capital expenditure recovery in storage manufacturers [4] Group 3: Inventory and Shipping Strategy - The company has developed a production and operation rhythm that aligns with market conditions, product characteristics, and customer structure, allowing for timely inventory procurement [4]

Group 1: Company Technology and Product Development - The company has launched multiple main control chips for UFS, eMMC, SD cards, and high-end USB, utilizing advanced foundry processes and self-developed core IP, resulting in significant performance and power consumption advantages [3] - As of Q3 2025, the cumulative deployment of the company's self-developed main control chips has exceeded 100 million units, indicating strong market penetration [3] - The mSSD product, as an upgrade to traditional SSDs, offers advantages such as lightweight design, low power consumption, and competitive performance, with a broad market outlook [3][4] Group 2: Market Trends and Future Outlook - The demand for storage is expected to surge due to the structural changes in AI inference, particularly with the application of key-value caching and retrieval-augmented generation technologies [4] - The rapid expansion of AI infrastructure and HDD supply shortages are anticipated to drive explosive growth in storage demand, although short-term output growth may be limited due to the lag in capacity construction [4] Group 3: New Product Innovations - The company has released several cutting-edge storage products, including MRDIMM and CXL2.0 memory expansion modules, and is actively innovating based on market needs [4] - The company has established a robust intellectual property portfolio around mSSD, facilitating the transition from R&D validation to commercial implementation [3][4] Group 4: Investor Relations and Communication - The investor relations activity was conducted on February 25, 2026, with participation from institutions such as Dongfang Securities and Penghua Fund, indicating active engagement with key stakeholders [2]

Core Viewpoint - The traditional Scaling Law for AI models is facing significant bottlenecks, particularly in China, where infrastructure investment is lagging behind the US, leading to challenges in AI inference performance and commercial viability [1][4][9]. Group 1: AI Inference Challenges - AI inference has become a critical area, with current demand for inference computing power exceeding that for training, as evidenced by GPT-5's API call volume exceeding 20 billion calls per minute [4][6]. - Chinese enterprises face a "push not moving," "push slow," and "push expensive" dilemma, with domestic models outputting less than 60 tokens per second compared to over 200 tokens per second for foreign models [7][9]. - The increasing complexity of AI applications, such as long text processing and multi-turn dialogues, has intensified the demand for improved inference performance [1][4][6]. Group 2: Huawei's UCM Technology - Huawei has introduced the Unified Cache Manager (UCM), a breakthrough technology designed to enhance AI inference performance by optimizing memory management and overcoming HBM capacity limitations [1][11]. - UCM employs a tiered caching strategy that allows for the efficient storage and retrieval of KV Cache data, significantly reducing inference latency and costs [10][11][18]. - The technology has demonstrated substantial improvements in inference speed, with a reported 125-fold increase in processing speed for specific applications in collaboration with China UnionPay [19][21]. Group 3: Industry Implications and Future Prospects - The introduction of UCM is seen as a pivotal move for the Chinese AI industry, potentially leading to a positive cycle of user growth, increased investment, and rapid technological iteration [18][24]. - Huawei's open-source approach to UCM aims to foster collaboration within the AI ecosystem, allowing various stakeholders to integrate and enhance their frameworks [28]. - The technology is expected to be applicable across various industries, addressing the challenges posed by the increasing volume of data and the need for efficient inference solutions [23][24].