如果您希望可以时常见面，欢迎标星收藏哦~ 来 源： 内容来自半导体芯闻综合，谢谢 。 " 继 今 年 年 底 开 始 全 面 商 业 化 的 第 六 代 12 层 高 带 宽 存 储 器 （ HBM ） 4 之 后 ， 高 带 宽 NAND 闪 存 （HBF）将在2030年左右成为主流。包括韩国SanDisk在内的三家全球存储器公司已经开始为HBF 做准备。" 韩国科学技术院（KAIST）电气电子工程系教授金正浩（Kim Jeong-ho）被誉为"HBM之父"，最 近因预测"HBF时代"而备受关注。 金教授是世界知名的AI半导体专家，他创立了HBM的基本概念和结构。他曾预测HBM的集成密度 将每两年翻一番，因此备受关注。 预见到2000年代初HBM技术的到来，我们便开始与SK海力士开展合作研究。这在SK海力士于 2013年首次在全球范围内实现HBM商业化的过程中发挥了主导和决定性作用。 金 教 授对英 伟 达 首 席 执 行 官 黄 仁勋与韩国在最近的亚太经济合 作 组 织 （ APEC ）会议期间开展 的"Kkanbu Chicken"合作作了如下解读。 "向韩国供应26万块GPU的承诺似乎是为了确保从三星 ...

Group 1 - The importance of NAND products in the AI memory market is rapidly increasing, with demand for data center NAND flash expected to surpass mobile applications for the first time next year [2] - Major NAND suppliers, including Samsung and SK Hynix, have reported that customer demand will exceed production capacity, leading to a significant supply shortage [2] - The price of NAND flash products has risen sharply, with the fixed trading price of 128Gb MLC NAND flash increasing by 10.6% in September and 14.9% in October, marking the largest increase in a decade [2] Group 2 - The next-generation memory "HBF" is being developed to combine the advantages of high bandwidth memory (HBM) with NAND characteristics, aiming for mass production in 2027 [3]

截至10:26，科创综指ETF建信（589880）跟踪的上证科创板综合指数权重股中，神工股份20cm涨停， 沃尔德涨超18%，芳源股份、磁谷科技涨超11%，仕佳光子涨超10%，金迪克涨超9%。 相关产品： 科创综指ETF建信（589880） 建信上证科创板综合联接A（023743） 建信上证科创板综合联接C（023744） 近日，闪迪大幅上调NAND闪存合约价格，涨幅高达50%。据悉，此次涨价主要受人工智能数据中心需 求持续爆发及晶圆供应严重受限的双重驱动。美东时间11月10日，存储巨头闪迪、希捷、美光科技等明 星股冲击新高，闪迪当天涨12%。AI芯片龙头英伟达收涨5.8%，创4月份以来最大单日涨幅。 招商证券指出，存储芯片产业正迎来结构性繁荣期。HBM、HBF等高带宽存储技术的快速发展，加之 产能优先向高端产品倾斜，使得供应商掌握定价权，传统DRAM与NAND供给紧张，价格持续上行。行 业巨头如SK海力士与三星电子在HBM市场的领先地位进一步强化其盈利能力，同时带动上游设备、材 料、封装厂商及下游AI服务器、云计算与终端设备的配套增长。 上证科创板综合指数紧扣科技创新主线，围绕国家战略性新兴产业发展方向，行 ...

Core Insights - The storage chip industry is entering a "super cycle" driven by the unprecedented demand for AI computing power, particularly for large models and high bandwidth requirements, leading to a fundamental restructuring of the industry logic and cycle characteristics [2][3][17] - The humanoid robot industry is accelerating its industrialization process, with significant developments from companies like Tesla, XPeng, and Leju Intelligent, showcasing advancements in AI and robotics integration [2][3][41] Storage Chip Industry Trends - The storage chip sector is experiencing a structural prosperity period, with rapid advancements in high bandwidth memory (HBM) and high bandwidth flash (HBF) technologies, leading to a supply-demand imbalance and rising prices [3][16] - Major players like SK Hynix and Samsung Electronics are strengthening their profitability in the HBM market, which is driving growth in upstream equipment, materials, and packaging manufacturers, as well as downstream AI servers and cloud computing [3][19] - The current cycle is characterized by a shift from traditional inventory management to a demand-driven model, with AI's insatiable need for computing power redefining the value of memory [17][19] Humanoid Robot Industry Trends - The humanoid robot industry can be divided into three main segments: "brain," "body," and "system integration," with the core value concentrated in the midstream components [3][59] - Companies like Tesla are planning large-scale production of humanoid robots, with Tesla's Optimus expected to have a market capacity of billions of units, indicating a significant shift towards AI-driven manufacturing platforms [41][44] - XPeng's new humanoid robot, IRON, showcases advanced features and aims for mass production by the end of 2026, highlighting the competitive landscape in the humanoid robotics sector [50][52] Investment Recommendations - The report suggests focusing on sectors with marginal improvements, including AI applications, AI hardware, power equipment, non-ferrous metals, and innovative pharmaceuticals in the short term [4] - In the medium to long term, it emphasizes the importance of technological cycles, supply-demand dynamics, and the progress of intelligent infrastructure and AI ecosystems [5]

Investment Rating - The storage industry is expected to enter a "prosperity cycle" with a recommendation to focus on specific companies such as Demingli, Jiangbolong, and Zhaoyi Innovation [4][72][74]. Core Insights - The demand for storage is driven by AI, with a significant shift from HDD to SSD/DRAM due to the increasing data volume and the need for faster access [2][18][72]. - The supply side is innovating with CBA and HBF technologies to overcome the limitations of traditional memory, enhancing storage density and performance [3][40][52]. - The semiconductor equipment market is projected to benefit from increased capital expenditure by storage manufacturers, with NAND equipment market size expected to reach $13.7 billion in 2025 [4][61][72]. Summary by Sections Storage Cycle - The storage industry exhibits clear cyclical characteristics, with the current cycle driven by AI demand and supply optimization from major manufacturers [9][12]. Demand Side - The transition from cold data to warm data is accelerating the replacement of HDDs with SSDs, as AI applications require more frequent data access [2.2][28]. - The data generated by AI applications is expected to grow exponentially, with projections indicating a shift from megabytes to exabytes and zettabytes [2.1][21]. Supply Side - CBA technology is crucial for achieving high density and performance in storage solutions, with applications in next-generation DRAM and NAND technologies [3.1][40]. - HBF technology offers significant advantages in capacity and energy efficiency, positioning it as a key solution for AI applications [3.2][52]. Semiconductor Equipment - The semiconductor equipment market is anticipated to grow significantly, with NAND equipment sales projected to increase by 42.5% in 2025 [4.1][61]. - Innovations in etching and deposition equipment are essential for advancing storage density and performance [4.2][68]. Investment Recommendations - The report suggests focusing on companies that are well-positioned to benefit from the storage industry's growth, including Demingli, Jiangbolong, and Zhaoyi Innovation [4][72][74].

Core Insights - The storage industry is entering the "post-HBM era" as the AI inference market rapidly grows, with major players like Samsung and SK Hynix advancing their sixth-generation HBM while new technologies like HBF are emerging to compete in AI storage [1][2] Group 1: HBF Technology Development - Major storage manufacturers, including Samsung, SK Hynix, and SanDisk, are investing in the research and development of HBF technology, with SK Hynix recently launching the "AIN series" that includes HBF products [1][2] - HBF, or High Bandwidth Flash, is a product made by stacking NAND flash memory, offering approximately 10 times the capacity of DRAM, which is crucial for supporting next-generation AI applications [2][3] - SanDisk first proposed the HBF concept in February, positioning it as an innovative product that combines 3D NAND capacity with HBM bandwidth, with plans to release initial HBF memory samples by the second half of 2026 [2][3] Group 2: Market Demand and Growth Projections - The HBF market is projected to reach $12 billion by 2030, representing about 10% of the HBM market size of approximately $117 billion, indicating a complementary relationship that could accelerate growth [2] - The demand for storage is expected to surge to hundreds of exabytes due to the rise of AI inference applications, with capacity becoming a bottleneck for computational power [4] - The storage industry is currently experiencing a "super cycle," driven by the increasing need for real-time access and high-speed processing of massive data, prompting HDD and SSD suppliers to expand their offerings of high-capacity storage products [4]

Core Viewpoint - SK Hynix has unveiled its AI product strategy, including the next-generation NAND storage called "HBF" (High Bandwidth Flash), aimed at maximizing performance through vertical stacking of NAND flash technology [1][2]. Group 1: AI Product Strategy - The company introduced the "AIN (AI-NAND) Family" product lineup to meet the rapidly growing demand for NAND storage products capable of efficiently processing massive amounts of data in the AI inference market [1][2]. - The AIN series focuses on optimizing performance, bandwidth, and density to enhance data processing speed and storage capacity [1][2]. Group 2: AIN Product Details - AIN P (Performance) is designed for large-scale AI inference environments, significantly improving processing speed and energy efficiency by minimizing bottlenecks between AI computation and storage. Samples are expected by the end of 2026 [2]. - AIN D (Density) targets low-power, low-cost storage for large data volumes, aiming to increase QLC-based TB-level SSD capacities to PB-level while maintaining SSD speed and HDD cost-effectiveness [2]. - AIN B (Bandwidth) utilizes vertical stacking of NAND to expand bandwidth, representing the company's HBF technology [2]. Group 3: Collaboration and Ecosystem Development - SK Hynix initiated research on AIN B to address memory capacity shortages, focusing on combining high-capacity, low-cost NAND with HBM stacking structures. The company is exploring collaborative deployment of AIN B with HBM for various applications [3]. - To promote the AIN B ecosystem, SK Hynix signed a memorandum of understanding with SanDisk in August and hosted the "HBF Night" event during the OCP summit, inviting representatives from major global tech companies [3]. Group 4: Future Outlook - The president of SK Hynix emphasized the company's commitment to becoming a core player in the AI memory market by continuing to collaborate with customers and partners in the next-generation NAND storage sector [4]. - SK Hynix is advancing its HBM production capabilities with the M15X factory, which is set to focus on mass production of next-generation HBM products, ensuring no supply shortages by the end of next year [5].

Core Viewpoint - The global storage chip market is experiencing a significant upturn driven by AI demand, with major companies like Samsung, Micron, and SK Hynix announcing price increases for DRAM and NAND products, indicating a potential "super cycle" in the industry [1][3][11]. Market Dynamics - Major players in the storage chip industry have collectively raised prices, with DRAM products increasing by 15%-30% and NAND prices up by 5%-10% [1][11]. - The DDR4 memory has seen a cumulative price increase of over 200% in the past six months, reflecting strong market demand [1][12]. - The AI-driven demand is causing a structural shift in the storage market, with predictions that the global storage market could reach $300 billion by 2027 [1][6]. Supply and Demand Changes - The current cycle differs from previous ones as it is primarily driven by enterprise-level AI capital expenditures rather than consumer demand [3][5]. - AI data centers are creating unprecedented demand for storage capacity, with AI servers requiring DRAM capacities that are eight times higher than traditional servers [8][9]. - The demand for high-performance storage is pushing prices up, with HBM prices exceeding $5,000 per unit, significantly higher than traditional DRAM [9][12]. Technological Innovations - The storage industry is undergoing a "three-dimensional revolution," focusing on bandwidth competition in HBM, increased stacking layers in 3D NAND, and the emergence of High Bandwidth Flash (HBF) technology [16][28][31]. - HBM technology is evolving rapidly, with the introduction of HBM4 standards that significantly enhance performance and efficiency [17][18]. - The competition in 3D NAND is centered around increasing the number of stacking layers, which directly impacts storage density and capacity [20][23]. Strategic Shifts - Major companies are shifting their production focus from traditional NAND to high-margin products like HBM and DDR5, leading to a supply-demand imbalance in lower-end products [11][13]. - The strategic pivot towards high-value products is evident as companies like Samsung and SK Hynix prioritize HBM and advanced DRAM production over traditional NAND [25][27]. - The rise of domestic manufacturers in the high-end storage sector is also noted, as they seek to innovate and reduce reliance on foreign technology [19][36]. Market Outlook - Analysts predict a "structural super cycle" in the storage market, driven by AI demand and the need for high-performance storage solutions [32][34]. - The global storage revenue is expected to reach $200 billion by 2025, with AI-related applications being a significant growth driver [34]. - Geopolitical factors and supply chain risks are highlighted as potential uncertainties that could impact the market dynamics and recovery pace [35][36].

Core Viewpoint - The rapid development of AI has made storage a critical component in the AI infrastructure, alongside computing power. The demand for storage is surging due to the increasing data volume and inference scenarios driven by large models and generative AI. Three storage technologies—HBM, HBF, and GDDR7—are redefining the future landscape of AI infrastructure [1]. Group 1: HBM (High Bandwidth Memory) - HBM has evolved from a high-performance AI chip component to a strategic point in the storage industry, significantly impacting AI chip performance limits. In less than three years, HBM has achieved over twofold capacity and approximately 2.5 times bandwidth increase [3]. - SK Hynix is leading the HBM market, currently in the final testing phase for the sixth generation (HBM4) and has announced readiness for mass production. In contrast, Samsung is facing challenges in HBM4 supply to Nvidia, with a two-month delay in testing [3][5]. - A notable trend is the customization of HBM, driven by cloud giants developing their AI chips. SK Hynix is shifting towards a fully customized HBM approach, collaborating closely with major clients [4]. Group 2: HBF (High Bandwidth Flash) - HBF aims to address the limitations of traditional storage by combining the capacity of NAND flash with the bandwidth of HBM. Sandisk is leading the development of HBF technology, which is expected to meet the growing storage demands of AI applications [8][9]. - HBF is seen as complementary to HBM, suitable for specific applications requiring large block storage units. It is particularly advantageous in scenarios demanding high capacity but with relatively relaxed bandwidth requirements [10][11]. Group 3: GDDR7 - Nvidia's introduction of the Rubin CPX GPU, utilizing GDDR7 instead of HBM4, reflects a new approach to AI inference architecture. This design optimizes resource allocation by separating the inference process into two stages, effectively utilizing GDDR7 for context building [13]. - The demand for GDDR7 is increasing, with Samsung successfully meeting Nvidia's orders. This flexibility positions Samsung favorably in the graphics DRAM market [14]. - GDDR7's cost-effectiveness may drive the widespread adoption of AI inference infrastructure, potentially increasing overall market demand for high-end HBM due to the proliferation of applications [15]. Group 4: Industry Trends and Future Outlook - The collaborative evolution of storage technologies is crucial for the AI industry's growth. HBM remains essential for high-end training and inference, while HBF and GDDR7 cater to diverse market needs [23]. - The ongoing innovation in storage technology will accelerate as AI applications expand across various sectors, providing tailored solutions for both performance-driven and cost-sensitive users [23].

Core Viewpoint - The article discusses the explosive growth potential in the memory market, driven by AI and data center demands, highlighting a "super cycle" in memory pricing and production, particularly for DRAM, HBM, and NAND [2][11][23]. Market Trends - The storage market is experiencing upward trends, with significant price increases in DDR and NAND due to supply chain disruptions and rising demand from AI applications [2][8]. - Recent reports indicate that Micron has raised its server shipment growth forecast for 2025 to approximately 10%, driven by increased demand for AI agents and traditional server workloads [9]. - TrendForce predicts a 5-10% average price increase for NAND Flash products in Q4 due to supply shortages and rising demand from cloud service providers [10]. Price and Profitability Drivers - Key drivers of the current memory super cycle include: 1. Explosive demand for AI and data centers, with traditional server capital expenditures expected to grow by 20-30% by 2026, leading to a 50% increase in DDR4/DDR5 memory demand [14]. 2. Profit margins for DRAM are projected to rise from 40-50% to nearly 70% by 2026, while NAND margins are expected to improve from breakeven to 30-40% [14]. Demand Surge Factors - The recent surge in storage demand is attributed to the transition of AI applications from an "accumulation phase" to a "high penetration phase," significantly increasing user interaction and data generation [19]. - The upgrade in AI technology logic has also amplified the need for DRAM and NAND, with token consumption increasing dramatically due to more complex interactions and multi-modal data processing [20]. - Companies are restructuring their AI infrastructure to implement a tiered storage system, which is driving immediate demand for DRAM and NAND products [21]. Future Outlook - The AI-driven super cycle is expected to last at least until 2027, with potential downturns anticipated in 2028 [23]. - Ongoing negotiations between DRAM manufacturers and NVIDIA regarding HBM pricing are likely to favor DRAM manufacturers, potentially leading to higher growth predictions for the HBM market [25]. Technological Developments - NVIDIA's introduction of the CPX solution is expected to create differentiated demand across storage products, potentially increasing GDDR7 demand while impacting HBM4 negatively in the short term [27]. - NVIDIA is also developing HBF (High Bandwidth Flash) as a cost-effective alternative to HBM, indicating a strategic shift in memory resource allocation [28].