每经记者｜朱成祥 每经编辑｜程鹏 魏文艺 8月25日晚间，芯原股份（688521.SH）披露股东询价转让定价情况，向机构投资者询价后，初步确定的转让价格为105.21元/股。截至8月25日收盘，芯原 股份报157.90元/股，即询价转让定价为当日收盘价约66.63%，不足七成。 出让方拟转让股份的总数占芯原股份总股本的比例为5.00%，拟参与芯原股份首发前股东询价转让的股东为VeriSilicon Limited、共青城时兴投资合伙企业 （有限合伙）、嘉兴海橙创业投资合伙企业（有限合伙）、济南国开科创产业股权投资合伙企业（有限合伙）、共青城文兴投资合伙企业（有限合伙）、 富策控股有限公司。 公告显示，本次询价转让拟转让股份已获全额认购，初步确定受让方为37家机构投资者，拟受让股份总数为2628.57万股。以105.21元的转让价计算，此次 交易总价超过27亿元。 值得一提的是，从去年9月24日到今年8月25日这近一年时间，芯原股份股价累计涨幅超过500%。 图片来源：芯原股份公告 《每日经济新闻》记者注意到，从业务结构看，半导体IP（知识产权）厂商营收结构中，以常年版税为主，而芯原股份一次性授权费用占比较高。 ...

芯原股份 20250822 摘要 新元股份 2025 年上半年 IP 授权业务收入 2.8 亿元，同比增长 8.2%， 二季度单季收入环比接近翻倍，达 1.87 亿元，同比增长 16.97%。数 字 IP 贡献占比约 75%，模拟和射频 IP 收入显著提高。 2025 年上半年芯片设计收入 2.32 亿元，其中 52%与 AI 算力相关，14 纳米以下先进制程项目占比 63%，涵盖数据中心、智慧驾驶等领域。执 行中的芯片设计项目接近 100 个。 2025 年上半年量产业务收入 4.08 亿元，同比增长 20%，单季度环比 增长接近 80%，同比增长 11.65%。目前有 112 个量产项目，45 个项 目等待量产。 公司全球化运营保持稳定，境外销售收入占比约 40%，研发人员主要驻 扎国内，实现双循环发展模式。非芯片公司客户群体收入占比达 35.66%。 2025 年二季度 ISIC 业务新签订单超过 7 亿元，环比增长超过 700%， 同比增长超过 350%，量产新签订单接近 4 亿元。上半年消费电子行业 收入同比增长 70%，受端侧 AI 需求推动。 Q&A 新元股份在 2025 年上半年取得了哪些主要 ...

下半年港股牛途继续， AI 浪潮持续演绎下，港股科技板块向上空间更大。国泰海通海外策略团队联合海 外科技团队，分析下半年港股科技板块的看好逻辑，并深度研究全球科技根目录公司，核心覆盖港美股半 导体及互联网板块，追寻产业边际与价值共振投资机会。 一、研究报告 （点击标题查看报告） ①今年港股明显跑赢 A 股，背后反映宏观偏弱背景下港股稀缺性资产更具吸引力，类似 2012-14 年移 动互联浪潮下港股比 A 股率先崛起。②互联网、新消费、创新药、红利等板块的稀缺资产在港股更集 中，与当前 AI 应用、新消费等产业趋势相关度更高，即港股资产的稀缺性所在。③随着外部扰动减缓， 国内政策发力驱动基本面修复、南下提供边际资金增量，下半年港股望进一步向上，结构上恒生科技更 优。 年初以来港股明显跑赢 A 股，结构上医药、科技、消费等行业更显著，借鉴历史看本轮港股占优源于部 分港股资产更具稀缺性。 今年初以来，港股相较 A 股走势表现更为亮眼，年初以来恒生指数累计上涨 19% ，跑赢沪深 300 指数 21 个百分点，结构上医药、科技、材料、日常消费等行业跑赢的幅度更大， 具体来看行情可以划分为一季度科技重估行情下恒生科技明 ...

Core Insights - The processor market is expected to grow significantly, driven by the increasing demand for generative AI applications, with market size projected to rise from $288 billion in 2024 to $554 billion by 2030 [1] - The GPU market is anticipated to surpass the APU market for the first time in 2024, reflecting the high computational power demand, particularly in server applications [1] - The competition in the GPU market is intensifying due to the development of AI ASIC chips by major players like Google and AWS, aimed at reducing capital expenditure [1][12] - The data center processor market is rapidly expanding, projected to reach $147 billion in 2024 and $372 billion by 2030, primarily driven by generative AI applications [9] Market Dynamics - The processor market is highly concentrated, with Intel holding 66% of the CPU market and Nvidia over 90% of the GPU market, while the APU and AI ASIC & DPU markets are more fragmented [3] - New entrants in the processor market, particularly from China, are emerging, with companies like Xiaomi and NIO achieving success in specific segments [3][4] - The trend towards advanced technology nodes is evident across all segments, with a significant reduction in the number of foundries capable of producing cutting-edge nodes [7] Technological Advancements - The transition to smaller technology nodes is crucial, with CPUs expected to adopt 3nm processes by 2024, while GPUs and AI ASICs are still on 4nm processes [15] - The demand for AI applications has led to an 8-fold increase in computing performance since 2020, with Nvidia's upcoming Rubin Ultra expected to achieve 100 PetaFLOP inference speeds by 2027 [15] - The integration of HBM memory in AI solutions is critical, although several AI ASIC startups are exploring SRAM-based processors for enhanced performance [15] Strategic Developments - Governments are investing in dedicated AI data centers to ensure national computing capabilities, while the U.S. government is implementing strict export controls affecting China's access to advanced AI chips [18] - In response, China is accelerating its semiconductor industry development, with companies like Huawei focusing on CPU and AI ASIC advancements [18] - Strategic computing is becoming central to AI infrastructure, with significant investments and mergers occurring in the AI chip sector, highlighting the increasing value of silicon expertise [19]

Group 1 - The Computer ETF (159998) is experiencing a tight market with a turnover of 4.45% and a transaction volume of 150 million yuan, while the CSI Computer Theme Index (930651) has decreased by 0.01% [2] - The Computer ETF has seen significant capital inflow, with a total subscription of 130 million shares, marking a substantial increase in its scale to 3.351 billion yuan, a record high since its inception [2] - In the past week, the Computer ETF has risen by 2.69%, with a notable increase of 43.2 million shares, leading its peers in performance metrics [2] Group 2 - The Computer ETF has recorded a net capital inflow of 51.2472 million yuan, accumulating a total of 36.3008 million yuan over the last five trading days [3] - The global PC market showed a significant recovery in Q2 2025, with a year-on-year growth of 7.4%, indicating a return to positive growth after several quarters of decline [3] - The AI ASIC chip market is projected to reach a size of 14.8 billion USD in 2024 and is expected to grow to 83.8 billion USD by 2030, with a CAGR of 33.5% [3] Group 3 - The CSI Computer Theme Index includes companies involved in information technology services, application software, system software, and computer hardware, reflecting the overall performance of computer-themed listed companies [4] - As of June 30, 2025, the top ten weighted stocks in the CSI Computer Theme Index account for 46.92% of the index, including companies like iFlytek, Inspur, and Hikvision [4]

Group 1: AI ASIC Market Insights - The AI ASIC market is experiencing rapid growth, with significant price and power consumption advantages over GPUs. The average price of GPUs is projected to be $8001 in 2024, while AI ASICs are expected to average $5236, highlighting a clear price advantage for AI ASICs [1][14][17] - The market size for AI ASICs is expected to grow from $14.8 billion in 2024 to $83.8 billion by 2030, with a CAGR of 33.5% from 2024 to 2030. In comparison, the GPU market is projected to grow from $70.1 billion to $326.3 billion during the same period, with a CAGR of 29.2% [1][20][18] - AI ASICs are anticipated to capture a larger market share in the training and inference sectors, with their growth rates outpacing those of GPUs [1][20] Group 2: Google TPU Development Trends - The development of Google's TPU has revealed three major trends: increasing specialization, enhanced computational power, and improved energy efficiency. The TPU v5 series includes TPU v5e for cost-effective training and inference, and TPU v5p focused on large model training [2][26][81] - The TPU architecture has evolved to support more complex tasks, with TPU v4 and v5 series demonstrating significant improvements in performance and energy efficiency, with TPU v5e achieving a 2.5 times increase in cost-effectiveness for inference tasks [2][57][76] - The latest TPU v7 (Ironwood) has shown a peak performance increase of 10 times compared to TPU v5p, with significant enhancements in HBM capacity and inter-chip bandwidth [2][76][78] Group 3: Stablecoin Regulatory Developments - The introduction of the Stablecoin Ordinance in Hong Kong aims to enhance transparency and reduce redemption risks in the stablecoin industry, providing a clear regulatory framework for compliant institutions [3][84] - Stablecoins are expected to improve cross-border payment efficiency, offering advantages over traditional systems by bypassing the inefficiencies of SWIFT [3][84] - The regulatory framework is anticipated to activate digital financial innovation, paving the way for the integration of stablecoins in various financial applications, including RWA (Real World Assets) [3][84]

Group 1: AI ASIC Market Insights - The AI ASIC market is experiencing rapid growth, with significant price and power consumption advantages over GPUs. The average price of GPUs is projected to be $8001 in 2024, while AI ASICs are expected to average $5236, highlighting a clear price advantage for AI ASICs [1][14] - The market size for AI ASICs is expected to grow from $14.8 billion in 2024 to $83.8 billion by 2030, with a compound annual growth rate (CAGR) of 33.5% from 2024 to 2030 [1][20] - AI ASICs are anticipated to capture a larger market share in the training and inference sectors, with their growth rates outpacing those of GPUs [1][20] Group 2: Google TPU Development Trends - The development of Google's TPU has revealed three major trends: increasing specialization, enhanced computational power, and improved energy efficiency. The TPU v5 series includes TPU v5e for cost-effective training and inference, and TPU v5p focused on large model training [2][81] - The TPU architecture has evolved to support higher performance and efficiency, with TPU v6 achieving near-linear scalability and significant improvements in training and inference speeds compared to previous generations [2][62] - The latest TPU v7, Ironwood, boasts a peak performance of 4614 TFLOPS and a significant increase in energy efficiency, being twice as efficient as the previous generation [2][76] Group 3: Stablecoin Regulatory Developments - The introduction of the Stablecoin Ordinance in Hong Kong aims to enhance transparency and reduce redemption risks in the stablecoin industry, providing a clear regulatory framework for compliant institutions [3][84] - Stablecoins are expected to improve cross-border payment efficiency, offering advantages over traditional systems by bypassing the inefficiencies of SWIFT [3][84] - The regulatory framework is anticipated to activate digital financial innovations and facilitate the global circulation of real-world assets (RWA) [3][84]

Group 1: Economic and Fiscal Implications - The "Big and Beautiful" Act signed by Trump includes tax cuts and significant spending measures, projecting a $4 trillion tax reduction and a $1.5 trillion spending cut over the next decade [1] - The Act is expected to increase the U.S. deficit by approximately $3.4 trillion over the next ten years, raising concerns about fiscal deficits and debt [1][2] - The Act is anticipated to create a super loose fiscal stimulus environment, potentially benefiting the economy and stock market liquidity, while negatively impacting U.S. debt and the dollar [1][2] Group 2: Market Reactions and Predictions - The Act is likely to push up U.S. Treasury yields and weaken the dollar, with increased demand for gold as a safe haven [2] - Analysts suggest that the Act may lead to a stronger recovery for the U.S. economy, although the extent remains uncertain [2] - The S&P 500 index is projected to reach 6850 points within 12 months, despite concerns over tariffs and geopolitical tensions [3] Group 3: Sector-Specific Impacts - The Act provides significant tax incentives and funding support for sectors such as chip manufacturers, energy companies, defense contractors, and real estate developers, while cutting subsidies for electric vehicles and renewable energy projects [1] - Traditional energy and military sectors are expected to benefit, while the renewable energy sector may face challenges [2] - The German stock market has shown strong performance, with military procurement plans potentially benefiting key defense manufacturers [5][6] Group 4: Oil Market Dynamics - OPEC+ has agreed to increase production by 548,000 barrels per day, exceeding market expectations, which may lead to a global oversupply risk and downward pressure on oil prices [7][8] - The strategy shift from limiting supply to increasing production aims to reclaim market share lost to U.S. shale oil [8] Group 5: AI Chip Supply Chain Growth - The global ASIC supply chain is entering a growth cycle driven by the widespread adoption of AI ASIC chips by cloud service providers like Google and Amazon [9] - Companies such as MPI, Aspeed, and Alchip are expected to benefit significantly from this trend, with MPI planning to double its production capacity [9][10]

Core Viewpoint - Marvell Technology (MRVL.US) has seen a significant stock price increase due to positive evaluations from top Wall Street analysts regarding its customized AI ASIC chip activities and potential market announcements [1][3] Group 1: Market Opportunities - Analysts from Evercore ISI predict that the new AI ASIC chip designs could ramp up quickly between 2026 and 2027, indicating strong future demand [1] - Marvell expects each customized AI chip design win to generate billions in lifecycle revenue within 1.5 to 2 years, while each XPU Attach win could contribute hundreds of millions within 2 to 4 years [2] - The total addressable market (TAM) for customized data center chips has been raised to $94 billion, a 26% increase from last year's AI activities [3] Group 2: Financial Projections - Marvell has raised its financial targets, with analysts noting that the potential earnings per share could reach $8 by 2028, exceeding Wall Street estimates by 60% [4] - The company aims to capture at least 20% of the TAM, with over 50% of its data center revenue expected to come from AI ASIC-related demands [3][5] Group 3: Competitive Landscape - Broadcom (AVGO.US) is identified as the long-term beneficiary of Marvell's AI activities, holding a dominant market share of approximately 60% in the AI ASIC sector, while Marvell holds 13% to 15% [6][7] - The AI ASIC market is expected to grow significantly, with major tech companies like Google, Microsoft, and Amazon investing heavily in AI ASIC chips, indicating a shift in market dynamics away from GPU dominance [7]

Core Viewpoint - The AI ASIC industry is experiencing significant growth opportunities due to its advantages over general-purpose chips like GPUs and CPUs in terms of computing power, efficiency, and cost per unit of computing power, which are driving demand growth [1][2]. Group 1: Market Dynamics - The ASIC market is catalyzed by its ability to adapt to various business scenarios and customer needs, providing flexibility in business layout [1]. - Major overseas CSP companies are launching self-developed chips, with Google releasing its latest TPU chip, Trillium, which has more than doubled its computing power compared to the previous generation [2]. - AWS has introduced the Trainium series, with the latest Trainium2 chip's performance being four times that of its predecessor, showcasing advancements in AI chip technology [2]. Group 2: Company Performance - Leading AI ASIC design companies like Broadcom and Marvell are benefiting from the surge in AI demand, with Broadcom projecting a 220% year-on-year increase in AI business revenue to $12.2 billion for fiscal year 2024 [3]. - Broadcom anticipates that its AI business revenue will reach between $60 billion to $90 billion by 2027, indicating strong market confidence [3]. - Marvell expects its AI business revenue to grow from $550 million to $2.5 billion between fiscal years 2024 and 2026, reflecting accelerated growth [3].