公众号记得加星标⭐️，第一时间看推送不会错过。 在这些追赶者中，英特尔的转型动作最为激进，也最具系统性。作为曾经的半导体霸主，英特尔在制 程技术上的落后一度让外界质疑其代工业务的前景。但从2024年底到2025年，英特尔展现出的战略 调整清晰而坚决：不是放弃先进制程竞争，而是通过技术突破、客户争取和生态整合，试图在特定领 域重新建立竞争力。 先进制程：14A与High-NA EUV的技术豪赌 英特尔晶圆代工的核心筹码是其14A制程节点。这一节点被定位为对外部客户极具竞争力的选择，预 计在功耗效率和芯片密度方面实现显著提升。更关键的是，14A将成为全球首个在关键层采用高数值 孔径（High-NA）EUV光刻技术的制造节点。 英 特 尔 已 安 装 ASML 的 Twinscan EXE:5200B ， 这 是 业 界 首 款 采 用 0.55 数 值 孔 径 投 影 光 学 系 统 的 High-NA光刻设备。该设备能够以8nm的分辨率打印芯片，在50 mJ/cm²的剂量下每小时可处理175 片晶圆，并实现0.7纳米的套刻精度。相比之下，台积电和三星虽然也在测试High-NA设备的研发版 本，但尚未将其用于商业 ...

截至2025年12月11日 11点15分，上证科创板半导体材料设备主题指数上涨0.50%，成分股华海清科 上涨5.19%，新益昌上涨4.74%，龙图光罩上涨3.45%，中科飞测上涨2.37%，天岳先进上涨1.93%。科创 半导体ETF（588170）上涨0.49%。 消息面上，半导体设备厂商透露，台积电与日月光集团、Amkor与联电等都在加速扩充先进封装 CoWoS产能，从订单分布观察，2026-2027年GPU、ASIC客户需求均超出预期。 半导体材料ETF（562590）及其联接基金（A类：020356、C类：020357），指数中半导体设备 （61%）、半导体材料（21%）占比靠前，充分聚焦半导体上游。 每日经济新闻 （责任编辑：张晓波 ） 【免责声明】本文仅代表作者本人观点，与和讯网无关。和讯网站对文中陈述、观点判断保持中立，不对所包含内容 的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考，并请自行承担全部责任。邮箱： news_center@staff.hexun.com 东吴证券指出，晶圆制造资本开支迈入新台阶，先进制程与封装加速突围。展望2026年，国内Fab 厂将迎来存储与先进 ...

Core Insights - The article emphasizes the strategic importance of SiC (Silicon Carbide) as a potential interposer material for advanced packaging solutions by Nvidia and TSMC, with a planned introduction by 2027, indicating a shift towards addressing thermal management challenges in AI computing [3][4]. - The competition in AI computing is shifting focus from transistor density to packaging and thermal management capabilities, highlighting the critical role of heat dissipation in chip performance [3][4]. - SiC is positioned as the optimal solution for CoWoS (Chip on Wafer on Substrate) interposers, balancing performance and feasibility, while traditional materials like diamond and glass fall short in practicality [3][4]. - The adoption of SiC in CoWoS could create a significant new market, particularly benefiting the mainland Chinese SiC industry due to aggressive investments in substrate capacity and cost advantages [3][4]. Group 1: SiC as Interposer Material - Nvidia and TSMC are considering SiC for future advanced packaging, with plans to implement it by 2027 [4]. - SiC is expected to address the thermal management issues associated with CoWoS packaging, which is crucial for the performance of AI chips [3][4]. - The transition to SiC interposers is seen as a strategic move to maintain competitive advantages in the semiconductor industry [3][4]. Group 2: Thermal Management Challenges - The article highlights the increasing power requirements of Nvidia's GPUs, necessitating improved cooling solutions to manage heat dissipation effectively [23][25]. - The CoWoS packaging technology is critical for high-performance computing, and any limitations in thermal management could hinder chip performance and reliability [25][37]. - SiC's high thermal conductivity (490 W/m·K) significantly outperforms silicon (130 W/m·K) and glass, making it a superior choice for managing heat in advanced packaging [105][106]. Group 3: Market Implications - The potential shift to SiC interposers could unlock a substantial new market, moving SiC from a niche power electronics market to a broader AI and data center infrastructure market [15][111]. - The mainland Chinese SiC industry is poised to benefit from this transition, leveraging its investments and production capabilities to capture a share of the global semiconductor supply chain [3][4][113]. - The expected growth in CoWoS capacity, projected at a compound annual growth rate of 35%, underscores the increasing demand for advanced packaging solutions [112].

Investment Rating - The report suggests a positive investment outlook for the SiC industry, indicating significant growth potential due to the anticipated adoption of SiC in advanced packaging technologies by major companies like NVIDIA and TSMC [6]. Core Insights - The report emphasizes the critical need for improved thermal management solutions in AI computing chips, particularly in the context of CoWoS packaging, which is currently facing challenges due to rising power demands [3][40]. - SiC is identified as a promising alternative material for CoWoS interposers, offering superior thermal conductivity and structural integrity compared to traditional silicon and glass materials [4][86]. - The potential for the Chinese mainland SiC industry to benefit significantly from the shift towards SiC interposers is highlighted, given its advantages in investment scale, production costs, and downstream support [5][6]. Summary by Sections 1. NVIDIA and TSMC's Consideration of SiC - NVIDIA plans to adopt 12-inch SiC substrates in its next-generation GPU packaging by 2027, indicating a strategic shift towards advanced materials for better performance [2][9]. 2. Need for CoWoS Thermal Management - The report discusses the increasing power requirements of AI chips, with NVIDIA's H100 GPU exceeding 700W, necessitating enhanced cooling solutions to manage heat effectively [15][22]. 3. SiC as a Preferred Interposer Material - SiC's thermal conductivity is 2-3 times that of silicon, making it an ideal candidate for interposers in CoWoS packaging, which is crucial for high-performance computing applications [4][86]. 4. Benefits for China's SiC Industry - If CoWoS adopts SiC interposers, the demand could exceed 230,000 12-inch SiC substrates by 2030, presenting a substantial opportunity for the Chinese SiC supply chain [5][6]. 5. Overview of SiC Substrate and Equipment Companies - Key beneficiaries of the SiC market growth include companies like Jingcheng Machinery, Jing Sheng Co., Tianyue Advanced, and others, which are positioned to capitalize on the anticipated demand for SiC substrates and related equipment [6]. 6. Investment Recommendations - The report recommends investing in companies involved in SiC substrate production and equipment manufacturing, as they are expected to benefit from the industry's transition towards SiC technology [6].

Core Insights - The global advanced packaging market is projected to reach $56.9 billion in 2025, with a year-on-year growth of 9.6%, and is expected to grow to $78.6 billion by 2028, reflecting a compound annual growth rate (CAGR) of 10.05% from 2022 to 2028 [3]. Industry Transformation - The logic of semiconductor packaging has shifted from merely providing protective casings to creating economic value, indicating a significant change in the industry dynamics [1][2]. - Advanced packaging is becoming a strategic focal point in the semiconductor supply chain, driven by the demand for AI and high-performance computing [2]. Market Dynamics - The demand for advanced packaging is largely fueled by AI applications, which have significantly increased the need for computing chips [2]. - The advanced packaging sales are expected to surpass traditional packaging for the first time in 2025, with consumer electronics and automotive electronics accounting for 85% of this market [2]. Innovation Directions - The industry is witnessing a surge in new technologies and materials, such as Chiplet technology, CoWoS packaging, and advanced substrates like silicon carbide and glass substrates [4]. - Key challenges in advanced packaging include efficient thermal management, heterogeneous integration of Chiplets, and the need for finer line widths and larger package sizes [5]. Equipment and Material Trends - The global advanced packaging equipment market is expected to reach $30 billion by 2030, with significant investments in hybrid bonding equipment and TSV etching machines [5]. - Glass substrates are emerging as a superior packaging material due to their better electrical and thermal performance, although they face challenges in production and reliability [5]. Strategic Development - The industry requires a collaborative ecosystem that integrates large, medium, and small enterprises to achieve high-quality development and innovation breakthroughs [6]. - There is a need for China to enhance its international influence by developing local standards and actively participating in global standard-setting to secure competitive advantages [6].

Core Insights - The AI semiconductor industry is expected to experience significant growth in 2026, with a shift in investment logic from upstream to downstream infrastructure [2][10] - The bottleneck in AI development has transitioned from chip manufacturing and packaging to downstream components such as data center space, power supply, and cooling systems [2][5] Upstream Capacity No Longer the Sole Bottleneck - Chip manufacturing and packaging have significantly expanded, alleviating previous supply concerns [4] - TSMC reported stronger-than-expected AI demand and a quick ramp-up in CoWoS capacity, indicating flexibility in the supply chain [4] - Despite ongoing tightness in advanced node wafer front-end capacity, AI semiconductors are prioritized over other applications like cryptocurrency ASICs [4] Bottleneck Shift - The current constraints are now focused on data center space, power availability, and supporting infrastructure, which have longer construction cycles than chip manufacturing [6] - The deployment of large-scale GPU clusters presents challenges in power consumption and heat dissipation, leading to a shift towards liquid cooling and high-voltage direct current (HVDC) solutions [6] Storage and Memory - AI workloads demand high-speed data storage and access, with companies like Meta opting for QLC NAND flash for cost efficiency [8] - The global demand for HBM (High Bandwidth Memory) is projected to surge, with NVIDIA expected to consume 54% of the total HBM by 2026 [8] Racks and Networking - OCP has introduced standardized blueprints for "AI Open Data Centers" and "AI Open Cluster Designs" to facilitate large-scale deployments [9] - Companies like Alibaba are focusing on pluggable optics for their cost-effectiveness and flexibility, while new technologies like CPO/NPO are gaining attention [9] Demand Forecast Indicates Explosive Growth for Downstream Components - Global cloud service capital expenditure is expected to grow by 31% in 2026, reaching $582 billion, significantly exceeding market expectations [11] - AI server capital expenditure could see approximately 70% year-over-year growth if its share in overall capital spending increases [11] AI Chip Demand Breakdown - NVIDIA is projected to dominate the CoWoS capacity consumption with a 59% share, followed by Broadcom, AMD, and AWS [12] - In AI computing wafer consumption, NVIDIA leads with a 55% share, followed by Google, AMD, and AWS [12] Investment Focus Shift - The signals from the OCP conference and industry data indicate a new direction for AI hardware investment, emphasizing the importance of downstream infrastructure [13] - Investors are encouraged to broaden their focus from individual chip companies to the entire data center ecosystem, identifying key players in power, cooling, storage, memory, and networking [13]

Group 1 - Morgan Stanley upgraded SMIC's rating, raising the target price from HKD 40 to HKD 80, anticipating an expansion in leading edge capacity and resolution of equipment bottlenecks [2] - Chinese mobile announced plans to deploy 100,000 local GPU networks by 2028, leading to an updated revenue forecast for China's AI GPU market, projected to reach RMB 113 billion in 2026 and RMB 180 billion in 2027, with a compound annual growth rate of 62% [2] - The report indicates that while NVIDIA's market share in China is nearly zero, there are still opportunities for local suppliers to fill the gap, particularly in AI high-performance computing and other semiconductor demands [2] Group 2 - The bottleneck in the semiconductor market is not expected to be TSMC's capacity but rather specific memory or server rack components, with TSMC reporting stronger-than-expected AI demand [3] - AI cluster sizes are moving towards over 100,000 GPUs, driving new standards in Ethernet design and liquid cooling for AI racks [3] - The semiconductor supply chain is projected to expand significantly by 2026, with a focus on CPO and NAND module manufacturers [4] Group 3 - Global CoWoS consumption is expected to reach 1,154k wafers in 2026, with NVIDIA holding a 59% market share, and HBM consumption projected at 2.6 billion GB [5] - AI capital expenditures remain strong, with cloud capex expected to reach USD 582 billion in 2026, reflecting a 31% annual growth [5] - AI GPU and ASIC rental prices have seen slight declines, but demand for AI inference in China remains robust, indicating a positive outlook for the AI supply chain [5]

Core Insights - The core argument of the article is that the bottleneck in AI development has shifted from chip manufacturing and packaging to downstream infrastructure, including data center power supply, liquid cooling, high bandwidth memory (HBM), server racks, and optical modules [2][4][9]. Upstream Capacity Expansion - Chip manufacturing and packaging have significantly expanded, alleviating previous concerns about supply shortages [5][6]. - TSMC has reported strong AI demand and is working to close the supply-demand gap, with a lead time of only six months for expanding CoWoS capacity [6][9]. - The report predicts that global CoWoS demand will reach 1.154 million wafers by 2026, a 70% year-on-year increase, indicating a robust supply response [6][12]. Downstream Infrastructure Challenges - As chip supply is no longer the main issue, the focus has shifted to the availability of data center space, power, and supporting infrastructure, which have longer construction cycles than chip manufacturing [9][12]. - The deployment of large-scale GPU clusters presents significant challenges in power consumption and heat dissipation, leading to a preference for liquid cooling solutions and high-voltage direct current (HVDC) power supply systems [9][12]. - The demand for HBM is expected to explode, with global consumption projected to reach 26 billion GB by 2026, with NVIDIA alone accounting for 54% of this demand [9][12]. Investment Opportunities - The shift in focus towards downstream infrastructure opens new investment opportunities beyond traditional chip manufacturers, emphasizing the importance of companies that excel in power, cooling, storage, memory, and networking [12][13]. - Global cloud service capital expenditure is expected to grow by 31% to $582 billion by 2026, significantly higher than the market's general expectation of 16% [12]. - AI server capital expenditure could see approximately 70% year-on-year growth if AI servers' share of capital expenditure increases [12][13].

Core Insights - The core argument of the article is that the bottleneck in AI development has shifted from chip manufacturing and packaging to downstream infrastructure, including data center power, liquid cooling, HBM memory, racks, and optical modules [4][9][19] Group 1: Shifts in Industry Focus - The focus of the market has transitioned from TSMC's CoWoS packaging and advanced processes to downstream supply chain challenges [4][5] - Chip manufacturing and packaging have significantly expanded, alleviating previous supply concerns [5][6] - The demand for AI semiconductors is expected to grow robustly, with the global CoWoS demand projected to reach 1.154 million wafers by 2026, a 70% year-on-year increase [7][14] Group 2: Downstream Infrastructure Challenges - The new bottlenecks are centered around data center space, power supply, and supporting infrastructure, which have longer construction cycles than chip manufacturing [9][10] - The OCP conference highlighted the need for redesigning data centers to accommodate large-scale AI clusters, emphasizing power and cooling requirements [10][18] - The demand for HBM is expected to surge, with global consumption projected to reach 26 billion GB by 2026, where NVIDIA alone is expected to consume 54% [18] Group 3: Investment Opportunities - Investment opportunities are shifting from upstream wafer foundries and packaging to a broader downstream supply chain [4][19] - Companies with robust power and space resources in data centers will have a competitive edge in the AI computing race [4][19] - The report suggests that investors should broaden their focus from individual chip companies to the entire data center ecosystem, identifying key players in power, cooling, storage, memory, and networking [19]

Core Insights - TSMC's Q3 2025 financial report showcases a significant revenue of $33.1 billion, exceeding market expectations by $1.6 billion and reflecting a year-on-year growth of 41% [2][3] - The company has revised its 2025 revenue growth forecast from 30% to nearly 35%, targeting $121.6 billion, which is $1 billion above market expectations [2][3] - TSMC's net profit reached $15.1 billion, marking a 39% year-on-year increase, equating to a daily net profit of $168 million [2][3] Revenue and Profitability - TSMC's quarterly revenue of $33.1 billion surpassed market expectations of $31.5 billion, with a quarter-on-quarter increase of 10.1% and a year-on-year increase of 41% [4] - The adjusted EPS reached $2.92, a 39% increase year-on-year, exceeding expectations by $0.33, with a net profit margin of 45.7% [4] Gross Margin - The gross margin reached 59.5%, up 1.7 percentage points year-on-year and 0.9 percentage points quarter-on-quarter, exceeding the expected 58.9% [6] - Key drivers include a surge in 3nm and 5nm process shipments and effective internal cost control [6] Process and Platform Structure - Advanced processes contributed 74% of wafer revenue, with 5nm accounting for 37% and 3nm for 23% [8] - The high-performance computing (HPC) segment, primarily driven by AI servers, accounted for 57% of revenue, indicating strong demand resilience [10] Implicit Highlights - The average selling price (ASP) of wafers reached $7,040, a 15% year-on-year increase, reflecting the value added by advanced processes [11] - Free cash flow was NT$139.38 billion (approximately $4.56 billion), a 12% year-on-year increase, providing ample resources for future expansion and R&D [11] AI Demand - TSMC's CEO stated that AI demand is stronger than three months ago, indicating an early stage of a long-term trend supported by three main drivers: cloud, enterprise, and sovereign AI [13] - The number of AI tokens is growing exponentially, necessitating stronger computing power, with TSMC's AI revenue growth forecast of nearly 35% for 2025 being lower than token growth due to technological iterations [14] Technology Roadmap - TSMC's N2 family of technologies is set to drive growth over the next decade, with N2 production starting in Q4 2025 and expected to contribute 5% of wafer revenue by 2026 [17][18] - N2P and A16 technologies are also in the pipeline, targeting high-end AI training and HPC applications, respectively [19][20] Global Expansion - TSMC is advancing its global production capabilities, with significant projects in Arizona, Japan, Germany, and Taiwan to support AI demand [21][22][24][26] - The company aims to achieve over 1 million 12-inch equivalent wafers in Arizona by 2027, leveraging government subsidies to reduce costs [22] Capital Expenditure - TSMC has narrowed its 2025 capital expenditure (CapEx) forecast to $40-42 billion, with 70% allocated to advanced processes [26] - The company expects a return of $1.5-$2 for every $1 spent on CapEx over the next 3-5 years, indicating a strong growth outlook [27] Non-AI Market and Competition - The smartphone market is recovering, with a 19% quarter-on-quarter increase, while automotive electronics are also gaining momentum [29] - TSMC's "Foundry 2.0" strategy aims to build a competitive moat by offering comprehensive solutions, including advanced packaging services [31] Future Signals - To validate TSMC's $65 billion revenue target for 2030, key indicators to monitor include Q4 2025 revenue performance, N2 process ramp-up speed, and overseas factory margin dilution [33] Conclusion - TSMC's Q3 2025 performance exemplifies the benefits of AI-driven advanced processes, solidifying its position as a cornerstone of the global semiconductor industry [35]