中金研究 根据Sensor Tower，25年11月ChatGPT移动端MAU突破8.7亿，月活市占率63%，Gemini则依赖Google庞大生态追赶；国内字节豆包日活达到亿级。建议 关注中外参与者竞争格局、Agent化、商业化的发展趋势。 点击小程序查看报告原文 Abstract 摘要 Chatbot已经成为AI时代"Killer App"。 互联网核心变革来自生产关系，普通用户能低门槛成为生产者，互联网"Killer App"例如社交、UGC内容平台源于 此；AI大模型核心变革来自生产力，其能高效理解用户需求和产出内容，而Chatbot应运而生，目前Chatbot的用户月均活跃天数、日均使用时长、留存率 逐渐接近社交平台，在工作、学习与娱乐场景的渗透率不断提升。 ChatGPT海外领先，国内豆包一家独大。 ChatGPT遵循"模型即产品"逻辑，其模型能力迭代是驱动用户持续增长重要原因，推动用户场景从"效率工具"泛 化至"生活方式"。而豆包初始定位部分借鉴Character.ai（移动端原生且更加聚焦情绪价值），依赖于字节用户生态获客，并通过多模态模型的突破以及成 本下探，持续加强自身优势，始于EQ（情绪 ...

追踪锦秋基金与被投企业的每一个光点与动态， 为创业者传递一线行业风向。 以下文章来源于十字路口Crossing ，作者Koji 十字路口Crossing . AI 正在给各行各业带来改变，我们在「十字路口」关注变革与机会，寻找、访谈和凝聚 AI 时代的「积极行动者」，和他们一起，探索和拥抱，新变化， 新的可能性。「十字路口」是乔布斯形容苹果公司站在科技与人文的十字路口，伟大的产品往往诞生在这里。 「Jinqiu Spotlight」 2026 会是 AI + 视频的「大年」，很多新的独角兽都将诞生在这里。「十字路口」播客在 2026 年邀请的第 一位 AI 创业者嘉宾，就是「OiiOii」的创始人闹闹。她所在的领域是 AI 视频，并且她的产品一经内测就获得 了大量的关注和好评。 锦秋基金是 OiiOii 所在公司 Hogi 的天使轮投资方。 我们也同样相信，AI 正在让创作这件事，从"会不会"变 成"想不想"。个体的想象力将不再受限于团队规模所限制。 以下是「十字路口」与闹闹的对话。看这 位曾在微信和字节跳动核心业务线战斗过的产品人，如何抓住AI时代的新 机会。 播客采访：Koji 整理编辑：十字路口 闹闹的 ...

智通财经APP获悉，国泰海通证券发布研报称，维持计算机板块"增持"评级。工信部等四部门印发《汽 车行业数字化转型实施方案》重点攻关智能机器人、智能检测设备等关键装备；AI领域，月之暗面获 大额融资、Meta高价收购Manus，验证Agent商业化前景；数字人民币制度框架升级并推动跨境应用、 金融科技等领域协同发展。 国泰海通证券主要观点如下： 工业和信息化部等四部门近日联合印发《汽车行业数字化转型实施方案》，重点攻关智能机器人、智能 检测设备等关键装备。 方案将加强关键技术自主攻关作为核心任务，旨在提升产业链供应链的韧性与安全水平。方案提到的攻 关重点覆盖仿真设计、研发测试及车用操作系统等基础软件，智能机器人、智能检测设备等关键装备， 以及信息物理系统(CPS)等集成核心技术，并明确鼓励整车及零部件企业优先应用上述自主可控技术产 品。为加速突破，政策支持重点企业联合高校、科研院所组建创新联合体，开展协同技术攻关。同时， 通过加强数据共享和平台共建，构建高效的"研发-验证-迭代"协同创新闭环，以缩短技术产业化周期。 国内大模型公司月之暗面(Kimi)近期完成5亿美元C轮融资，投后估值达43亿美元，公司现金储备已 ...

Investment Rating - The investment rating for the industry report is "Outperform the Market" (maintained) [1] Core Insights - MiniMax is a global large model company that has served over 200 countries and regions, with more than 200 million individual users and over 100,000 enterprise clients. The company's overseas revenue accounts for 73%, with significant contributions from Singapore and the United States [2][4] - The company has a strong focus on AI applications, particularly in video and audio, positioning itself in the first tier globally. MiniMax has launched the first MoE (Mixture of Experts) large model in China and is prioritizing multimodal integration in its strategy [2][3] - MiniMax's revenue has seen significant growth, with a 175% year-on-year increase in revenue for the first nine months of 2025, driven primarily by its AI video and open platform products [2][20] Summary by Sections Company Overview - MiniMax was established at the end of 2021 and has rapidly expanded its services globally, leveraging technology innovation, efficient operations, and a global strategy [6][14] - The company has a diverse product portfolio, including AI video generation (Hailuo AI), AI companionship (Talkie), and an open platform for API services, which contribute significantly to its revenue [15][20] Financial Performance - In 2024, MiniMax's revenue was $30.52 million, and in the first nine months of 2025, it reached $53.44 million, marking a 175% increase year-on-year. The revenue contributions from the open platform, Hailuo AI, and Talkie are 29%, 33%, and 35%, respectively [20] - The gross margin turned positive in 2024, and by the first nine months of 2025, it reached 23%, with a significant reduction in net losses from $244.24 million in 2024 to $186.28 million in 2025 [20][17] Market Position - MiniMax ranks as the fourth largest pure-play large model technology company globally, with a market share of 0.3% based on 2024 revenue. The company is the only Chinese startup in the top ten [42][46] - The global large model market is projected to grow significantly, with expectations of reaching $220 billion by 2025, indicating a strong potential for MiniMax's growth in this sector [41] Product and Technology - MiniMax's AI products, particularly in video and audio, are recognized for their high performance and cost-effectiveness. The Hailuo AI video generation platform is noted for its dual-mode capabilities, enhancing its application across various scenarios [56][57] - The Speech-02 model is highlighted for its low latency and high-quality audio generation, ranking second globally in the voice model category [59][60]

今日（1.5），沪指加速上涨超1%重返4000点，算力板块再度强势，云计算ETF汇添富（159273）大幅收涨超3%，全天成交额超3000万元，环比放量33%。 云计算ETF汇添富（159273）标的指数权重股多数收红：金山办公涨超6%，中际旭创、阿里巴巴-W、中科曙光涨超2%，浪潮信息、恒生电子涨近2%，腾 讯控股微涨。 | 序号 | 代码 | 名称 | 估算权重 ▼ | 涨跌幅 | 历了不容负 | | --- | --- | --- | --- | --- | --- | | 1 | 300308 | 中标准创 | 11.14% | 2.21% | 186.59亿 | | 2 | 300502 | 新易感 | 11.02% | -0.99% | 153.60亿 | | 3 | 0700 | 腾讯控股 | 10.09% | 0.24% | 124.50亿 | | 4 | 9988 | 阿里巴巴-W | 9.52% | 2.55% | 156.82亿 | | ਦ | 603019 | 中科脂光 | 6.88% | 2.52% | 52.34Z | | 6 | 688111 | 金山办公 | 3.97% | 6 ...

近日，Manus 被 Meta 以惊人溢价收编，彻底撕碎了"应用无壁垒"的伪命题。在此之前，Agent 类产品 常被嘲笑为"套模工具"，因不掌握底层模型而被资本冷落。但 Manus 证明了在 AI 时代，底层算法是公 用水电，而能调动水电完成复杂工程交付的"调度力"，才是最值钱的护城河。 如果说 Manus 是通用场景下的"万能助理"，迈富时则是商业深水区的"特种兵"。它不再仅仅提供 CRM 工具，而是通过 Marketingforce 平台 构建了一个庞大的 Agent 矩阵。它的核心竞争力在于"懂行"：它利 用 Agent 调度模型，直接接管了企业的获客、营销与转化流程。对于客户而言，迈富时的价值不再是账 号订阅费，而是 "可量化的增长结果"。这种从 SaaS 向"结果驱动型 Agent"的商业模式升级，使其估值 逻辑彻底脱离了传统软件股，向高溢价的 AI 生产力服务商靠拢。 2. 金山办公 (688111.SH) —— 掌握"高频入口"的 Agent 霸主 角度切换： 场景即正义，WPS 正在成为 Agent 的"操作系统"。 Manus 的高光时刻，让金山办公的 WPS AI Agent 想象空间被无 ...

复盘美股科技巨头过去三年股价走势，AI叙事不断递进 2023年OpenAI领先全球开启AI加速度，微软受益于OpenAI独家合作，估值抬升明显。2024年市场低估 模型进步空间，叙事转向推理侧，认为应用公司最优，Meta坐拥社交垄断生态(潜在Agent入口)和广告 场景，股价为除英伟达以外PE唯一抬升的巨头。(24年2月，英伟达业绩会估计数据中心收入约40%来自 推理。)同年云厂商由于大幅增加资本开支但供给受限，云收入传导有延迟，三大CSP估值略有所回 落。2025年模型差距与OpenAI明显收敛，谷歌后来居上，生态优势为市场追逐。26年该行认为Scaling Law将持续，模型厂商打开差异化应用市场，模型推理侧需求或进入放量拐点。模型和算力或为最优投 资方向。 2025年四家巨头Capex同比增长50%以上，26年该行测算Capex将持续实现30%以上增速 国信证券发布研报称，模型架构持续演化，多模态与长文本为Agent爆发奠定基础。当前大模型厂商商 业化路径分化，推理侧需求有望于2026年放量，并驱动SaaS市场格局重塑，编程、Agent等应用场景率 先实现商业化突破。 国信证券主要观点如下： 2025年 ...

Core Insights - The article discusses the significant changes in AI technologies, particularly focusing on large models, agents, and AI-native development paradigms, and how these have transformed various industries in 2025 [2] Group 1: Industry Landscape - OpenAI remains a leading player in the AI space, maintaining its position with general large model capabilities, although the release of GPT-5 did not meet high expectations [4] - Google made a strong comeback in 2025, with technologies like Gemini 3 and Nano Banana gaining user traction through effective distribution across search, office, and cloud products [4] - Anthropic has emerged as a stable player, surpassing OpenAI in API business scale and growth through deep partnerships with cloud providers like AWS [5] - Domestic company DeepSeek has become a notable star in 2025, with the release of R1 and an open-source approach that invigorated the AI ecosystem [5] - The industry is shifting focus from "scaling" to "sustainability," as companies face challenges like low production ratios and high loss pressures [5] Group 2: Company Capabilities - Companies that succeed are those addressing high-frequency demand scenarios, such as AI social media and music, which naturally fit large model applications [7] - Companies that have fundamentally restructured their cost structures through AI, significantly reducing marginal costs, are also positioned for success [7] - Companies lagging behind include those that focus solely on algorithms without integrating product development, leading to stagnation in commercialization [9] Group 3: Technological Evolution - The evolution of large models has shifted from merely increasing size to enhancing usability, with improvements in complex instruction understanding and multi-step reasoning [14] - The cost-effectiveness of models has improved significantly, with a nearly tenfold increase in performance per cost within a year [15] - The industry consensus is moving from "how strong is the model" to "how verifiable and reusable are the processes" [8] Group 4: Agent Development - Agents are recognized as the next core battleground in AI, with a shift from merely answering questions to executing tasks [36] - The introduction of standardized protocols like MCP has enabled agents to collaborate more effectively, moving from isolated operations to organized systems [38][39] - The competition is not just about the models but also about the surrounding infrastructure and operational capabilities necessary for agents to function effectively [40] Group 5: Future Directions - The future of agents lies in their ability to operate in open environments, handling uncertainties and making decisions based on incomplete information [45] - The industry is expected to see a shift from selling agent capabilities to providing automated services that deliver measurable business value [43] - The integration of agents into existing business processes is anticipated to redefine their role from mere tools to essential components of operational workflows [43]

随着AI大模型快速发展，从基础设施到上层应用的演进正成为新一轮科技竞争的关键。 一种行业观点认为，基座大模型的数量未来将持续收敛至个位数左右，但围绕千行百业将衍生出诸多更 为丰富的垂域模型与应用，那也将是本轮AI浪潮真正引发技术变革的关键所在。 其中，物理AI成为一种重要关注窗口，正加速推进具身智能、自动驾驶等领域演进，有望深刻改变未 来社会的运行方式。但技术路线仍存分歧，法律、合规与伦理等软性基础尚在夯实。而进入"Agent元 年"，让AI技术真正触及实体经济的"深水区"，仍有挑战需要克服。 中兴通讯首席发展官崔丽接受21世纪经济报道记者专访时，深入分析了物理AI的技术路线走向。据她 观察，一些具体行业已经在真正借力AI，率先完成价值闭环。 物理AI之辩 2025年初，Sora的横空出世因其高度还原物理世界的视频生成能力，引发关于"世界模型"的广泛讨论， 也让物理AI的两条核心路线——世界模型与 VLA（视觉语言模型）的竞争浮出水面。 崔丽对记者分析道，Sora等模型的爆发，标志着AI正从单纯的"预测者"向"模拟者"进化，是从"数据驱 动"到"模型仿真驱动"到"物理对齐"到"通用模拟"的范式转移，也是AI落 ...

Core Insights - The article emphasizes the transformative impact of AI on the cloud market, highlighting that AI is becoming a core growth driver for cloud vendors as more industries recognize its potential to optimize business efficiency and create value [3][4][6] - Cloud vendors are shifting from being infrastructure providers to AI capability providers, with the development of Agents seen as a method to unlock the value of Tokens [6][11] - There is a growing demand for reliable and low-barrier Agent development platforms to help enterprises transition from concept validation to large-scale application [3][4][6] Group 1: Market Growth and Opportunities - AI-driven growth has created new business opportunities for cloud vendors, with Alibaba Cloud's AI-related revenue experiencing triple-digit year-on-year growth for nine consecutive months [1] - AWS anticipates that future Token revenue from MaaS platforms will be comparable to its EC2 computing product revenue [1] - Google Cloud's annual revenue exceeds $50 billion, largely driven by AI [1][3] Group 2: Agent Development and Implementation - The article discusses the need for a comprehensive framework for Agent development, which includes tools for model customization, Agent development, operation, and security governance [3][4][7] - Companies like Firefly Engine and AWS are actively providing solutions to lower the barriers for Agent development, emphasizing ease of use and security [7][9] - The development of Agents is expected to lead to significant efficiency improvements, as evidenced by case studies where projects were completed in a fraction of the time previously required [4][6] Group 3: Challenges in Agent Adoption - Despite the optimistic outlook, many enterprises face significant obstacles when moving from concept validation to production, with 93% of customers encountering major challenges [6] - The challenges stem from data and engineering aspects, where the requirements for large-scale applications differ significantly from those in the concept validation phase [6][11] Group 4: Strategic Shifts Among Cloud Vendors - Cloud vendors are increasingly focusing on developing foundational models that are tailored for Agent development, with companies like Tencent and Baidu making organizational adjustments to enhance their model capabilities [11][13] - The shift towards MaaS business models is becoming a core metric for cloud vendors, with Firefly Engine viewing AI Token usage as a key performance indicator [13] - Alibaba Cloud aims to position itself as a leading player in the AI era, with a focus on comprehensive AI cloud solutions [13]