关于那个神秘的「Pony Alpha」模型的传言，已经在互联网发酵了一周。 有人说它是 Claude 5 的马甲，也有人说它是某大厂的秘密武器。就在刚刚，靴子落地，谜底揭晓：这个代号「Pony Alpha」的新模型，正是智谱 AI 的春 节大招——GLM-5。 智谱公众号截图 而且，它直接开源了。 如果说 2025 年是 AI 学会写代码的一年，那么 2026 年开年，正如特斯拉前 AI 总监 Andrej Karpathy 所预言，我们或许即将进入「智能体工程」（Agentic Engineering）时代。 只不过，比起 GPT-5.3-Codex、Claude Opus 4.6，头一个把这件事做成开源基础设施的，是国产模型 GLM-5。 附体验地址： 骗过硅谷的 Pony Alpha，竟然是智谱 GLM-5 的马甲 现在的 AI 写个贪吃蛇或者俄罗斯方块，早就不是什么新鲜事了。要测，就得测点刁钻的。 我们给 GLM-5 抛出了一个极其具体的物理模拟需求： 创建一个交互式的 HTML、CSS 和 JavaScript 卫星系统模拟程序，该程序应模拟卫星向地面接收器发送信号的过程。模拟程序应显示一颗卫星绕地 ...

Core Viewpoint - The stock of Zhiyun (02513) has seen a significant increase of over 26%, currently trading at 388 HKD with a transaction volume of 925 million HKD, following the release of its new flagship model GLM-5 [1] Group 1: Product Launch - Zhiyun officially launched its next-generation flagship model GLM-5 on February 11, achieving state-of-the-art (SOTA) performance in coding and agent capabilities, closely matching the user experience of Claude Opus 4.5 in real programming scenarios [1] - The GLM-5 model is now available on Zhiyun's development platforms, including BigModel.cn, Z.ai, and Zhiyun Qingyan (App/web version), for user experience [1] - Due to computational power limitations, GLM-5 is currently only available in the Max user package, with plans for gradual expansion of access [1] Group 2: Technical Adaptation - The GLM-5 has completed deep reasoning adaptation and operator-level optimization with major domestic chip platforms such as Huawei Ascend, Moore Threads, Cambricon, Kunlun Core, Muxi, Suiruan, and Haiguang, enabling stable operation with high throughput and low latency on domestic computing clusters [1] - This adaptation signifies not just an engineering achievement but also relates to the autonomy and controllability of the AI computing supply chain, providing the conditions for large-scale delivery of open-source Agentic Engineering-level productivity tools [1]

Group 1 - The core viewpoint of the article highlights the performance of the Chip ETF Huatai Fu (516920), which opened with a slight increase of 0.27% at 1.132 yuan [1] - The major holdings of the Chip ETF include companies such as Cambricon, which rose by 0.10%, SMIC by 0.47%, and Haiguang Information by 1.96% [1] - The ETF's performance benchmark is the CSI Chip Industry Index return, managed by Huatai Fu Fund Management Co., Ltd., with a return of 12.94% since its inception on July 27, 2021, and a recent one-month return of -0.72% [1]

Core Viewpoint - The stock of Zhiyu (02513) has seen a significant increase, with a rise of over 26%, currently trading at 388 HKD and a transaction volume of 925 million HKD, following the release of its new flagship model GLM-5 [1] Group 1: Product Launch - Zhiyu officially launched its next-generation flagship model GLM-5 on February 11, achieving state-of-the-art (SOTA) performance in coding and agent capabilities, closely approaching the user experience of Claude Opus 4.5 in real programming scenarios [1] - The GLM-5 model is now available on Zhiyu's development platforms BigModel.cn, Z.ai, and Zhiyu Qingyan (App/web version) for user experience [1] - Currently, due to computational power limitations, GLM-5 is only included in the Max user package, with plans to gradually expand access [1] Group 2: Technical Adaptation - The newly released GLM-5 has completed deep reasoning adaptation and operator-level optimization with major domestic chip platforms such as Huawei Ascend, Moore Threads, Cambricon, Kunlun Core, Muxi, Suiruan, and Haiguang, enabling stable operation with high throughput and low latency on domestic computing clusters [1] - This adaptation signifies more than just engineering compatibility; it is crucial for the autonomy and controllability of the AI computing power supply chain, providing the conditions for large-scale delivery of open-source Agentic Engineering-level productivity tools [1]

Group 1 - The core point of the article highlights the performance of the Chip ETF (159995), which opened with a gain of 0.68% at 1.913 yuan on February 12 [1] - The major holdings of the Chip ETF include companies such as SMIC, Haiguang Information, and Cambrian, with respective opening gains of 0.47%, 1.96%, and 0.10% [1] - The performance benchmark for the Chip ETF is the National Securities Semiconductor Chip Index return, managed by Huaxia Fund Management Co., with a return of 89.97% since its inception on January 20, 2020, and a near-term return of -0.05% over the past month [1]

科创人工智能ETF华宝（589520）及其联接基金（024560）重点布局国产AI产业链，成份股囊括国产 GPU龙头（如寒武纪），国产ASIC龙头（如芯原股份）、AI应用龙头（如金山办公），半导体行业权 重占比近一半，具备较强进攻性；软件行业权重占比超三成，有望受益于AI应用补涨行情。同时，该 ETF是融资融券标的，是一键布局国产算力的高效工具。 （文章来源：每日经济新闻） 国联民生证券表示，持续看好AI投资机会，从四维度验证行业高景气：①科技巨头资本开支增长； ②AI助手Clawdbot验证AI从对话工具向执行者转型，边缘AI产品前景广阔；③算力基础设施供需紧张 持续，推动上游通胀，云厂涨价、H100租赁价格上行，存储板块或延续涨价态势；④AI已进入应用落 地、需求加速与产业链景气共振阶段，全面看多AI产业趋势。 当AI发展正从算力建设转向应用落地，一键布局"算力+AI应用"的创业板人工智能ETF（159363）及场 外联接（023407），更直接受益于AI技术商业化爆发的增长红利。从赛道看，创业板人工智能约六成 仓位布局算力（光模块龙头+IDC龙头），约四成仓位布局AI应用，不止是"算力"核心，也是真正的 ...

Group 1 - The core viewpoint highlights the strong performance of AI-related ETFs, particularly the创业板人工智能ETF华宝 (159363) and科创人工智能ETF华宝 (589520), which are benefiting from the commercialization of AI technology [1][2] - The创业板人工智能ETF has approximately 60% of its portfolio allocated to computing power and 40% to AI applications, indicating a balanced approach to both sectors [2] - The科创人工智能ETF focuses on the domestic AI industry chain, with significant holdings in domestic GPU and ASIC leaders, as well as AI application leaders, showcasing its aggressive investment strategy [2] Group 2 - Citic Securities notes structural highlights in AI applications, particularly in AI fintech, AI healthcare, and AI data sectors, with overall profitability expected to improve significantly [1] - Guotai Junan Securities expresses optimism about AI investment opportunities, supported by four dimensions: increased capital expenditure by tech giants, the transition of AI assistants to executors, ongoing supply-demand tension in computing infrastructure, and the acceleration of AI application demand [1] - The AI sector is entering a phase of application landing and demand acceleration, indicating a positive outlook for the overall AI industry trend [1]

国产大模型竞争加速，消息面上，智谱推出GLM-5，定位为最新一代旗舰级对话、编程与智能体模 型，主攻复杂系统工程与长程Agent任务。内部评估显示，GLM-5在编程开发场景中平均性能较上一代 提升超20%，真实编程体验逼近Claude Opus 4.5水平。在BrowseComp、MCP-Atlas和τ2-Bench等三项 Agent评测中均取得开源领域最优表现。 截至2026年2月12日 09:40，中证人工智能主题指数(930713)上涨0.87%，成分股晶晨股份上涨12.95%， 协创数据上涨7.61%，光环新网上涨4.55%，深信服上涨3.80%，复旦微电上涨3.21%。AI人工智能 ETF(512930)上涨0.80%，最新价报2.26元。 AI人工智能ETF紧密跟踪中证人工智能主题指数，中证人工智能主题指数选取50只业务涉及为人工智能 提供基础资源、技术以及应用支持的上市公司证券作为指数样本，以反映人工智能主题上市公司证券的 整体表现。 数据显示，截至2026年1月30日，中证人工智能主题指数(930713)前十大权重股分别为中际旭创、新易 盛、寒武纪、澜起科技、科大讯飞、中科曙光、海康威视、豪威 ...

Core Insights - Zhipu AI has launched and open-sourced GLM-5, with multiple domestic chip manufacturers completing Day-0 adaptation for the model, ensuring compatibility and stable operation from the first day of release [1][2] Group 1: GLM-5 Launch and Adaptation - Zhipu AI's GLM-5 has been adapted by major domestic chip platforms including Huawei Ascend, Moore Threads, Cambricon, Kunlun, Muxi, Suiruan, and Haiguang, achieving high throughput and low latency on domestic computing clusters [2] - Haiguang's DCU team collaborated closely with Zhipu AI to optimize the underlying operators and hardware acceleration, enabling GLM-5 to run stably on Haiguang DCU with high throughput and low latency [1] - Moore Threads completed full-process adaptation and verification on its flagship AI training and inference GPU MTT S5000, leveraging its MUSA architecture to enhance model inference performance while reducing memory usage [1] Group 2: Model Performance and Features - GLM-5 has expanded its parameter scale from 355 billion (activated 32 billion) to 744 billion (activated 40 billion) and increased pre-training data from 23 terabytes to 28.5 terabytes, significantly enhancing its general intelligence capabilities [2] - The model incorporates a new "Slime" asynchronous reinforcement learning framework, supporting larger model scales and more complex tasks, and utilizes DeepSeek Sparse Attention to maintain long text performance while reducing deployment costs and improving token efficiency [2] - A month prior, Zhipu AI released the GLM-Image model, which employs a hybrid architecture of autoregressive and diffusion decoders, marking a significant exploration in cognitive generative technology [2]

Core Viewpoint - The Shanghai 180 ETF Index Fund has shown significant growth in both scale and performance, with notable increases in net value and share volume, indicating strong investor interest and market confidence [1][3]. Performance Summary - As of February 11, 2026, the Shanghai 180 Index rose by 0.19%, with constituent stocks like China Jushi and Huayou Cobalt experiencing gains of 9.99% and 5.45% respectively [1]. - The Shanghai 180 ETF Index Fund has achieved a 14.74% increase in net value over the past six months, with a maximum monthly return of 9.13% since inception [1]. - The fund has a historical one-year profit probability of 100%, with an average monthly return of 3.08% and a monthly profit percentage of 75% [1]. Liquidity and Scale - The Shanghai 180 ETF Index Fund recorded a turnover rate of 0.43% with a trading volume of 24.91 million yuan on February 11, 2026, and an average daily trading volume of 70.58 million yuan over the past week [1]. - The fund's scale has increased by 32.33 million yuan over the past year, ranking second among comparable funds [1]. Share Growth - The number of shares for the Shanghai 180 ETF Index Fund has grown by 21 million shares in the past year, also ranking second among comparable funds [1]. Risk and Fee Structure - The fund's management fee is 0.15% and the custody fee is 0.05%, which are among the lowest in comparable funds [3]. - The maximum drawdown for the fund this year is 4.28%, with a tracking error of 0.019% over the past three months, indicating high tracking precision [3]. Top Holdings - As of January 30, 2026, the top ten weighted stocks in the Shanghai 180 Index account for 24.85% of the index, with major companies including Zijin Mining and Kweichow Moutai [3].