报道引述消息人士的话称，在特定商业领域，H200或在近期获得中国市场。另据路透社援引两名消息 人士报道，由于销售前景的不确定性，英伟达现在要求中国客户预付全款，且下单后不能取消、退款或 重新配置。 【环球时报记者 倪浩 环球时报特约记者 文简】在美国政府去年12月放行英伟达H200对华出口后，业界 纷纷猜测其对华交付的时机和未来销售前景。彭博社8日引述消息人士的话称，最快本季度或可以向中 国出口H200。 彭博社报道称，中国是全球最大的半导体市场，英伟达芯片若能进入，无疑将是一次"重大胜利"。英伟 达首席执行官黄仁勋曾表示，光是人工智能（AI）芯片领域，在中国未来几年就可能产生500亿美元的 营收。报道还提到，在英伟达芯片遭美国限制出口、美国芯片缺席中国市场期间，中国本土竞争对手蓬 勃发展，并计划在2026年大幅增产。 美国《华尔街日报》报道称，在全球AI竞赛如火如荼之际，美国总统特朗普于去年12月8日宣布允许英 伟达将其较高阶的H200芯片出口至中国"经批准的客户"。"《金融时报》随后传出北京正在审慎评估让 此芯片卖到中国市场的可能性，或至少先调查其'安全性'。"报道称，这反映出中方对芯片领域长期依 赖导致 ...

1月2日，壁仞科技在港交所上市，成为港股"国产GPU第一股"，同时也是港股2026年上市的第一只股票。这家由前商汤总裁张文2019年创立的GPU企业，正 式填上了中国算力版图的关键一环。 当日，壁仞科技盘初快速拉升涨幅一度超过100%，市值超940亿港元。壁仞科技发行价为19.6港元，发行2.85亿股，募资总额为55.83亿港元。 壁仞科技在国产AI芯片版图中占据着重要的一席，其在通用GPU领域拥有多项技术专利，技术先进性可比肩国际巨头。截至2025年12月15日，壁仞科技在 全球多个国家和地区累计申请专利1500余项，位列中国通用GPU公司第一，获得专利授权600余项，位列中国通用GPU公司前列；发明专利授权率达100%， 位列国内企业发明专利授权率榜首。 但是从业绩来看，2022年—2024年及2025年上半年，公司收入分别为49.9万元、6203万元、3.37亿元、0.59亿元，年内亏损分别为14.74亿元、17.44亿元、 15.38亿元、16.01亿元。 由此计算，壁仞科技三年半以来产生亏损达63.57亿元。公司解释称，较大幅度亏损主要系若干前股东的赎回权相关的"赎回负债账面值变动"，该变动为非 现 ...

打开手机刷AI生成视频，新能源电站靠算力调度发电，甚至家里的智能家电都要靠芯片"思考"——现在不管是日常日子还是产业升级，都离不开"算力"这个 硬支撑。而提到算力核心的GPU芯片，以前大家首先想到的都是英伟达这类国际巨头，总觉得国产芯片还差着一截。 可2025年底，一匹"国产黑马"横空出世，直接打破了这个格局——它就是被称为"中国版英伟达"的摩尔线程。12月5日刚登陆科创板，短短几天股价就像坐 了火箭，从114.28元的发行价一路飙升，最高涨到940元以上，即便后续有所回落，截至12月17日总市值仍达3360亿元 。 更让人振奋的是，凭借在能源算力领域的硬核实力，它成功登顶全球能源科技龙头，让"中国芯"在全球高端算力赛道有了话语权。 市值暴涨的背后，是摩尔线程拿得出手的技术硬实力。2025年12月20日，在首届MUSA开发者大会上，公司亮出了全栈技术底牌——新一代GPU架构"花 港"，直接刷新了国产GPU的性能上限 。这款架构在计算密度上提升了50%，效能最高能提升10倍，还完整支持从FP4到FP64的全精度计算，不管是AI训 练、图形渲染还是科学计算，都能轻松hold住 。 更厉害的是它的"夸娥"万卡智算集 ...

郑纬民认为，算力自主有三个要求：一是芯片设计能力要自主；二是制造与供应链风险要可控；三是系 统与集群交付能力要强。算法自强则指的是，针对GPU能做大模型适配，能做大模型训练，能让模型优 化。 中新网12月22日电(记者 吴家驹)"真正决定主权AI成败的，在于是否有足够多的开发者，愿意长期在这 套栈上写代码。"近日，摩尔线程首届MUSA开发者大会上，中国工程院院士、清华大学计算机系教授 郑纬民如是表示。 郑纬民表示，过去很长一段时间，做芯片是全球化分工的，有人做架构设计，有人做设备制造，有人做 代工，有人做封装。如今，"主权AI"已成为每个国家必须回答的现实问题，是提升未来国家竞争力的关 键。 在他看来，"主权AI"其核心在于实现"算力自主、算法自强、生态自立"的完整体系。 他表示，在某种程度上，生态自立比算力自主和算法自强更重要。因为生态自立，意味着芯片要从"能 跑"到"愿意用"，而不是能跑一个软件就可以。"真正决定主权AI成败的，在于是否有足够多的开发者， 愿意长期在这套栈上写代码。" 同时，郑纬民表示，当前中国芯片行业面临着内卷与碎片化问题，例如：不同的厂家提供不同的接口， 要做不同的适配。开发者是生态建 ...

12月20日上午，刚刚登陆科创板的GPU新秀摩尔线程，召开了首届MUSA开发者大会（MDC 2025）。 会上，摩尔线程公布了新一代GPU架构"花港"，AI训推一体芯片"华山"，用于游戏和图形渲染等场景的 芯片"庐山"，以及"夸娥"万卡训练集群等产品。 现场，中国工程院院士、清华大学计算机系教授郑纬民发表主题演讲。他指出，发展"主权AI"是提升未 来国家竞争力的关键，其核心在于实现"算力自主、算法自强、生态自立"的完整体系。 霸狂女 为什么 "万卡甚至十万卡系统"是必选项 算力基石 模型时代的基本单位是集群总算力，不是单卡性能 预训练超大规模模型、服务国民级推理需求，需要 持续可用的万卡级训练集群 分布在全国的推理集群与第力网络 num SSICAL Partist 从主权 Al 角度 国产万卡/十万卡系统 = 本土大模型与行业模型的 "母机"与基座 图 郑纬民认为，国产计算显卡与国外主流产品的性能差距正在持续缩小，虽然构建国产万卡乃至十万卡级 别的超大规模智算系统存在难度，但这是必须完成的产业基础设施任务。他特别指出，开发者是生态建 设的关键，国产芯片平台必须构建起友好、易用的开发环境，以有效服务开发者社群 ...

Core Insights - The article highlights the significant advancements made by Moore Threads in the GPU sector, particularly through the introduction of the new "Huagang" architecture and the "Kua'e" ten-thousand card intelligent computing cluster, which supports trillion-parameter model training [2][3]. Architecture Innovations - The "Huagang" architecture showcases a 50% increase in computing density and up to 10 times improvement in efficiency, fully supporting precision calculations from FP4 to FP64. It integrates the self-developed MTLink high-speed interconnect technology, facilitating cluster expansion beyond 100,000 cards [3][5]. - Two chips have been planned based on the "Huagang" architecture: "Huashan" for AI training and inference integration, and "Lushan" aimed at high-performance graphics rendering, with performance improvements of 64 times for AI computation, 16 times for geometric processing, and 50 times for ray tracing [5]. Cluster Capabilities - The "Kua'e" ten-thousand card intelligent computing cluster has publicly disclosed key engineering efficiency metrics, achieving a model compute utilization (MFU) of 60% for dense models and 40% for mixture of experts (MOE) models, with a linear scaling efficiency of 95% and effective training time exceeding 90% [6]. Ecosystem Development - Moore Threads announced the iteration of its unified software architecture MUSA to version 5.0, with plans to gradually open-source core components, including computation acceleration libraries and system management frameworks [8]. - The "Moore Academy" platform has attracted nearly 200,000 learners and collaborates with over 200 universities nationwide, reflecting a comprehensive approach to ecosystem building through technology open-sourcing, developer tool provision, and early talent cultivation [9]. Technological Integration and Exploration - The release indicates a trend towards the deep integration of graphics, AI, and high-performance computing, with hardware-level ray tracing acceleration and the introduction of the AI generative rendering technology MTAGR 1.0 [10]. - The company is also exploring cutting-edge fields such as embodied intelligence and AI for science, showcasing its ambition to redefine the value of GPUs as a general computing platform [10]. Industry Context - The comprehensive technology showcase reflects the current stage of domestic high-end computing power development, transitioning from single-chip innovations to tackling large-scale system engineering and building a thriving application ecosystem [11]. - The efficiency disclosure of the ten-thousand card cluster signifies that domestic computing infrastructure is beginning to undergo rigorous testing in large-scale, high-load scenarios, while the architecture iteration and integration of graphics and AI demonstrate the company's intent to define the next generation of computing architecture [11].

Core Insights - The year 2025 is a pivotal moment for the domestic GPU industry in China, marked by a wave of IPOs from companies like Moore Threads and Muxi Technology, which highlights the urgency for funding to sustain operations and growth [2][4] - The rapid listing of these companies is driven by a need for capital to navigate the lengthy R&D phase and to ensure survival in a competitive landscape [2][4] - The challenges facing domestic GPU manufacturers extend beyond product design to include supply chain vulnerabilities and the dominance of the CUDA ecosystem, which poses significant barriers to entry [9][10] Financial Performance - Moore Threads reported cumulative revenue of 609 million yuan over the past three years (2022-2024) with a net loss of 5.005 billion yuan, while Muxi Technology had cumulative revenue of 1.117 billion yuan and a net loss of 3.29 billion yuan during the same period [4] - The financial data reflects a common trend in the GPU industry, characterized by high R&D investments and significant operational losses [4] Market Dynamics - The investment strategy in the GPU sector is described as a "wolf pack tactic," where several leading companies are encouraged to go public to secure funding, with the expectation that only a few will emerge as winners [6][7] - The current market environment is shifting from a focus on fundraising to a competitive emphasis on engineering capabilities and market delivery, as companies strive to meet the demands of large clients [14] Supply Chain and Ecosystem Challenges - The reliance on external manufacturing capabilities is identified as a critical issue, with domestic manufacturers struggling to achieve scale in production and yield control [10] - The entrenched CUDA ecosystem, developed over nearly two decades, presents a formidable challenge for domestic GPU companies, making it difficult to attract customers who face high costs in switching ecosystems [10][11] Strategic Responses - Some domestic GPU manufacturers are adopting a pragmatic approach by promoting heterogeneous mixed training, which involves using a mix of different brands within a computing cluster to enhance compatibility and robustness [11][12] - The focus is shifting towards collaboration with existing ecosystems rather than outright replacement, which is seen as a more realistic strategy for overcoming barriers [12] Future Outlook - The industry is transitioning from a narrative-driven phase to one focused on tangible results and performance metrics, with a heightened emphasis on engineering reliability and stability [14] - The explosion of AI inference demand presents new opportunities for growth, with companies exploring supernode solutions to enhance performance [15] - The competitive landscape is expected to undergo significant changes within the next year, with only a few companies likely to survive the intense competition [15]

Group 1 - The semiconductor sector experienced a rise and subsequent pullback, with the Sci-Tech Semiconductor ETF (588170) and Semiconductor Materials ETF (562590) gaining 3.04% and 3.67% respectively in the afternoon session [1] - According to data from China Merchants Securities, as of September 5, 2025, Moer Thread is negotiating expected orders worth approximately 2.004 billion yuan, with over 1.7 billion yuan in AI computing projects [1] - The current order scale for Muxi stands at 1.43 billion yuan, indicating a ramp-up in domestic AI computing capabilities [1] Group 2 - Galaxy Securities highlighted that the demand for high-performance computing chips is being driven by both cloud-based large model training and edge AI application deployment [1] - Domestic manufacturers like Huawei Ascend and Muxi are enhancing market confidence in autonomous computing capabilities through technological iterations [1] - The semiconductor sector is undergoing a structural market trend, with equipment and materials benefiting from domestic innovation and technological upgrades [1] Group 3 - The Sci-Tech Semiconductor ETF (588170) and its linked funds track the Shanghai Stock Exchange Sci-Tech Board Semiconductor Materials and Equipment Theme Index, focusing on semiconductor equipment (61%) and materials (23%) [2] - The semiconductor equipment and materials industry is a key area for domestic substitution, characterized by low domestic replacement rates and high ceilings for domestic substitution [2] - The Semiconductor Materials ETF (562590) also emphasizes the upstream semiconductor sector, with significant allocations to semiconductor equipment (61%) and materials (21%) [2]

Group 1 - The semiconductor industry index has seen a strong increase of 2.05%, with notable gains in component stocks such as Jingrui Electric Materials up 15.17% and Aisen Co. up 7.36% [3] - The semiconductor industry ETF (159582) rose by 2.21%, reaching a latest price of 2.27 yuan, and has accumulated an 8.30% increase over the past week [3] - The trading activity in the semiconductor industry ETF was robust, with a turnover rate of 14.1% and a transaction volume of 58.68 million yuan [3] Group 2 - A significant breakthrough in the domestic chip sector was reported, where a team from Peking University utilized cryo-electron microscopy to observe the microscopic behavior of photoresist in developing solutions, potentially reducing wafer defects by over 99% [3] - The domestic AI computing power market is entering a growth phase, with expected orders of approximately 2.004 billion yuan for Moer Thread and 1.43 billion yuan in hand orders for Muxi [3] Group 3 - The demand for high-performance computing chips is being driven by cloud-based large model training and edge AI applications, with domestic manufacturers like Huawei Ascend and Muxi enhancing market confidence in autonomous computing power [4] - The semiconductor industry ETF has experienced a net outflow of 6.5534 million yuan recently, but has attracted a total of 40.9866 million yuan over the past ten trading days [4] - The top ten weighted stocks in the semiconductor industry index account for 78.18% of the index, including companies like Zhongwei Company and North Huachuang [4]

Group 1 - The capital market is entering a practical phase of an industrial revolution driven by policies, technological advancements, and capital investments [1] - New AI regulations have clarified the operational landscape for AI companies, reducing uncertainty and allowing for increased investment in AI applications [2] - Major tech exhibitions in September showcased significant advancements in technology, leading to a reevaluation of the value of domestic alternatives and computing power autonomy [3] Group 2 - The introduction of new vehicles by Huawei has disrupted the automotive market, transforming cars into intelligent terminals and boosting related stocks [4] - The expectation of interest rate cuts by the Federal Reserve is providing a favorable environment for tech growth stocks, attracting foreign investment back to emerging markets [5] - The current technological and policy-driven cycle is characterized by tangible advancements and a clear investment direction, encouraging deeper understanding of underlying technological changes [7]