Core Insights - AI technology is reshaping various industries, with storage technology becoming increasingly critical as a backbone for AI applications. Jiangbolong has emerged as a key player in the AI storage transformation with innovative solutions and precise market positioning [1]. Group 1: Full-Stack Solutions - Jiangbolong provides a full-stack solution for AI servers and computing integrated machines, covering all scenarios of AI training and inference. Key products include eSSD, RDIMM, SOCAMM2, and innovative memory solutions, which offer efficient and reliable storage performance tailored to complex AI needs [1]. - The new UNCIA 3856 SATA eSSD features high-quality 3D eTLC NAND and self-developed firmware algorithms, achieving a balance of large capacity, low power consumption, and high endurance, thus providing a solid data storage foundation for AI servers [1]. Group 2: Memory Solutions - Jiangbolong's DDR5 RDIMM and MRDIMM memory modules are core choices for general servers and AI infrastructure due to their high bandwidth, low latency, and excellent compatibility. The DDR5 MRDIMM significantly enhances data transfer rates through a multi-channel architecture, delivering unprecedented performance for AI computing integrated machines [3]. - The SOCAMM2 memory product, based on LPDDR5/5x particles and CAMM modular design, meets the stringent performance and energy efficiency requirements of data centers. It offers ultra-high transmission rates (up to 8533 Mbps) and low power consumption (one-third of standard DDR5 RDIMM), providing dual enhancements in capacity and bandwidth for intelligent computing centers [3]. Group 3: Edge AI Solutions - Jiangbolong has introduced the integrated packaging mSSD for edge AI applications, utilizing wafer-level system-in-package (SiP) technology to integrate the controller, NAND, PMIC, and other components into a single package. This makes mSSD an ideal storage solution for edge AI devices such as AI PCs and robots, offering flexibility and efficiency [5]. Group 4: Strategic Vision - In the AI era, mere improvements in storage performance are insufficient to meet the complex and changing application demands. Jiangbolong aims to achieve efficient utilization of storage resources and flexible release of computing power through an edge-cloud collaborative strategy. The company strengthens partnerships within the industry chain to inject critical storage capabilities into AI intelligent computing center construction and promote the continuous advancement and widespread application of edge AI storage technology [7]. - Jiangbolong's outstanding performance in the AI storage sector is reflected not only in the continuous launch of innovative products but also in its deep insights into industry trends and precise understanding of customer needs. The company will continue to adhere to an innovation-driven development strategy, focusing on core media like mSSD to iterate more forms and scenarios of innovative packaged storage, contributing further to the popularization and application of AI technology [7].

公众号记得加星标⭐️，第一时间看推送不会错过。 三星及SK海力士近日揭晓，DRAM与NAND可能有双位数涨幅，价格循环持续上升。 AI数据中心需求持续扩张，带动存储产业供需结构加速翻转，价格走势成为市场高度关注焦点。业者 透露，韩厂三星及SK海力士最新合约价报价，预计1月底或2月初揭晓，价格趋势向上。 针对近日市场盛传「三星存储全面涨价80％」一说，台系模组厂及代理商皆反应，目前尚未收到三星 正式报价通知，不清楚该数字实际适用对象为何。 但可以确定的是，2026年第一季价格趋势明确向上，DRAM与NAND均朝双位数涨幅方向发展，价 格循环持续进入上升段。 在价格结构方面，业界也认为，DRAM与NAND第一季均呈双位数涨幅方向，但实际涨幅依客户层级 而异，CSP与高阶应用端承受较高涨幅，模组与通路端则相对温和。 业者强调，价格判断应以实际成交价与现货价走势为依据，近期RDIMM现货价格快速上扬，与部分 NAND客户须预付现金（deposit）才能取得配额，皆显示供应结构已转为卖方市场，价格形成逻辑 已与过去景气循环明显不同。 业者亦指出，当前原厂与客户普遍采取「包全年产能」的长约策略，但过往经验显示，若市况反转 ...

Core Viewpoint - Jiangbolong (301308) is positioned as a key player in the storage solutions market, offering a diverse range of products from consumer-grade to enterprise-level server storage, catering to high-performance demands in data centers [1] Group 1: Product Offerings - The company provides a variety of storage products, including consumer-grade, industrial-grade, automotive-grade, and enterprise-level server storage [1] - Jiangbolong is one of the few domestic companies capable of designing and supplying "eSSD+RDIMM" product combinations at scale [1] Group 2: Clientele and Market Position - The company serves numerous leading clients across various sectors, indicating a strong market presence and reputation [1] - Jiangbolong aims to deepen collaborations with well-known clients in multiple fields, enhancing its competitive edge [1]

Core Viewpoint - The storage industry is experiencing a "super cycle" driven by AI demand, leading to significant expansion plans from major companies like Jiangbolong and Demingli, with expectations of continued price increases into the first half of next year [1][5]. Group 1: Expansion Plans - Jiangbolong has announced a fundraising plan of 3.7 billion yuan, while Demingli has proposed a 3.2 billion yuan expansion plan [1]. - Jiangbolong's fundraising will focus on three key areas: storage product application technology development, NAND Flash main control chip design, and storage chip packaging and testing [1]. - Demingli aims to enhance its full-chain technical capabilities from storage main control chip R&D to storage module delivery through its fundraising projects [1]. Group 2: AI Market Focus - Jiangbolong's fundraising will support high-end storage development and industrialization projects aimed at the AI sector, with a total investment of 930 million yuan for AI-related storage solutions [3][4]. - The demand for storage in AI servers is significantly higher than in traditional servers, with DRAM usage approximately eight times and NAND Flash usage three times that of conventional servers [3]. - Both companies are targeting high-capacity and high-performance solid-state drives (SSDs) and memory products to meet the growing needs of AI applications [4]. Group 3: Market Outlook - The global semiconductor storage market is projected to grow by 16.2% by 2026, reaching a size of 214.8 billion USD, presenting opportunities for domestic storage manufacturers [5]. - Jiangbolong and Demingli are both focusing on enhancing their production capabilities to meet the increasing demand from data centers and AI applications [5]. - The storage industry is characterized by a supply-demand imbalance, with expectations of limited supply from upstream manufacturers in the coming years [6]. Group 4: Financial Health and Strategy - Both companies are facing cash flow challenges, with Demingli reporting negative operating cash flow for several consecutive quarters and a high debt ratio of 73.28% [7]. - Jiangbolong has initiated a plan for H-share listing to address its urgent funding needs, indicating a strong demand for capital in the storage sector [7]. - Companies are adopting inventory management strategies to ensure supply chain stability amid market volatility, with a focus on aligning procurement with sales plans [7][8].

Core Viewpoint - Jiangbolong plans to raise 3.7 billion yuan through a private placement to actively invest in high-end AI storage, storage controller chips, and advanced packaging and testing [1] Group 1: Fundraising and Investment Plans - The company intends to use 880 million yuan of the raised funds to develop storage products targeting the AI sector, including enterprise-level SSDs and high-end consumer SSDs [1] - The company is expanding its enterprise storage business by leveraging self-developed technology and actively participating in major client technology and new product bidding [1] Group 2: Market Growth and Opportunities - The global AIGC wave and the "Digital China" top-level planning are providing new growth momentum for the storage market [1] - As a leading independent memory manufacturer in China, the company is advancing its domestic and international dual-wheel layout in the storage industry, indicating significant growth potential [1] Group 3: Financial Projections - The company's projected net profit attributable to shareholders for 2025, 2026, and 2027 is expected to be 1.16 billion, 1.85 billion, and 2.32 billion yuan, respectively [1] - Corresponding price-to-earnings ratios for 2025, 2026, and 2027 are forecasted to be 99, 62, and 49 times, respectively, maintaining a "buy" rating [1]

Core Viewpoint - The article highlights the strategic move by Jiangbolong, a leading independent storage company in China, to raise up to 3.7 billion yuan for AI-related storage research and industrialization projects, amidst a surge in AI computing power demand [1][4]. Group 1: Fundraising and Investment Plans - Jiangbolong plans to raise funds through a private placement, targeting a total of 3.7 billion yuan, with a focus on AI-related storage development [1][4]. - The funds will be allocated to four key areas: high-end storage for AI, semiconductor storage control chip development, high-end packaging and testing projects, and working capital [3][4]. Group 2: Market Position and Growth - Jiangbolong is the second-largest independent storage company globally, with significant market presence through its brands FORESEE and Lexar [5]. - The company reported a 138.66% year-on-year increase in enterprise storage business revenue, reaching 693 million yuan in the first half of 2025 [5][7]. Group 3: Technological Advancements - The company aims to address the challenges of performance, capacity, and cost in storage technology, particularly for AI applications [4]. - Jiangbolong's self-developed control chips have surpassed 100 million units deployed, with ongoing validation by major manufacturers [5]. Group 4: Financial Performance - For the first three quarters of 2025, Jiangbolong achieved revenue of 16.734 billion yuan, a 26.12% increase year-on-year, and a net profit of 713 million yuan, up 27.95% [7].

Core Viewpoint - NVIDIA's recent decision to switch from DDR5 to LPDDR memory chips aims to reduce power costs for AI servers, which is expected to significantly boost industry demand and spill over into the consumer electronics market [1][3]. Group 1: Memory Chip Transition - NVIDIA is replacing traditional DDR5 with low-power LPDDR memory to lower AI server power costs, which is anticipated to increase demand in the industry [1]. - The shift to LPDDR is expected to enhance memory value in AI servers, which typically have a higher memory unit value compared to smartphones [1]. Group 2: SOCAMM Performance - SOCAMM, based on LPDDR, is designed for AI servers and offers a 2.5x increase in bandwidth while reducing power consumption by one-third [2]. - SOCAMM's compact design (14x90mm) allows for more efficient server configurations, and it supports a maximum capacity of 128GB per module, enhancing AI model training and inference performance [2]. Group 3: Memory Price Trends - Memory prices have increased by 50% this year, with expectations of a further 30% rise by Q4 2025 and an additional 20% increase early next year [3]. - The heightened demand for LPDDR from NVIDIA is likely to create broader and more long-term risk factors surrounding advanced chips, affecting the entire consumer electronics market [3].

Core Viewpoint - Nvidia has decided to switch from DDR5 to LPDDR memory chips for AI servers to reduce power costs, which may significantly impact the supply of consumer-grade memory [1] Group 1: Memory Chip Transition - Nvidia is replacing traditional DDR5 RDIMM with LPDDR to lower AI server power consumption costs [1] - The shift to LPDDR, typically used in mobile devices, is expected to increase demand in the industry significantly [1] Group 2: SOCAMM Performance - SOCAMM, based on LPDDR, offers 2.5x bandwidth improvement over traditional RDIMM and reduces power consumption by one-third [2] - SOCAMM is designed for AI servers, with a compact size of 14x90mm and a maximum capacity of 128GB per module [2] Group 3: Memory Price Trends - Memory prices have increased by 50% this year, with expectations of a further 30% rise by Q4 2025 and an additional 20% increase early next year [3] - The heightened demand for LPDDR from Nvidia is likely to extend price increases into the consumer electronics market [3]

Investment Rating - The industry investment rating is "Overweight" [6] Core Viewpoints - NVIDIA's recent decision to switch memory chip types aims to reduce AI server power costs by replacing traditional DDR5 with LPDDR, which is expected to significantly boost demand in the industry [6] - The shift to LPDDR is anticipated to have a ripple effect on the consumer electronics market, as LPDDR is commonly used in mobile devices [6] - Memory prices have increased by 50% this year and are projected to rise an additional 30% in Q4 2025, followed by a further increase of about 20% early next year [6] Summary by Sections - **Industry Overview**: The report highlights the growing demand for LPDDR memory due to NVIDIA's shift in AI server technology, which is expected to enhance memory pricing and availability in the consumer electronics sector [3][6] - **Technological Advancements**: SOCAMM, a memory module based on LPDDR, offers 2.5x bandwidth improvement over traditional RDIMM and reduces power consumption by one-third, making server designs more compact and efficient [6] - **Market Trends**: The report notes that the transition to LPDDR in enterprise solutions may lead to increased supply constraints in consumer-grade memory, further influencing market dynamics [6]

Supply Chain and Market Trends - The company maintains strong relationships with major wafer suppliers through long-term agreements, ensuring supply chain resilience and diversity [2] - Recent trends show a price increase in storage products due to high demand from North American cloud service providers investing in AI, leading to a tightening supply for consumer and embedded storage products [3] Business Performance and Product Development - The company ranks third in total capacity for enterprise SATA SSDs in China and first among domestic brands, with ongoing expansion in enterprise storage product offerings [3] - The company has launched four series of self-developed controller chips, with over 100 million units deployed, indicating rapid growth in deployment scale [5] New Product Innovations - The company is actively developing high-performance storage products for data centers, including the newly released SOCAMM2, designed specifically for AI data centers, which shows significant improvements in bandwidth and power consumption [4] - The UFS4.1 product, developed in collaboration with SanDisk, has demonstrated superior performance in process, read/write speed, and stability compared to market alternatives, with accelerated adoption among Tier 1 clients [5]