以下文章来源于智能涌现 ，作者邓咏仪 智能涌现 . 直击AI新时代下涌现的产业革命。36氪旗下账号。 2025年，月之暗面从"烧钱换规模"的斗争中暂时脱身，还在海外开发者蹚出一条新路，这是杨植麟在公开信中写下"短期暂不考虑上市"的 底气。 文 ｜ 邓咏仪 编辑 ｜ 苏建勋 来源｜ 智能涌现（ID：AIEmergence） 封面来源 ｜ AI生成 1 2月 末的AI圈异常热闹：智谱、MiniMax的"港股AI第一股"之争刚落幕，2025年最后一天，月之暗面（Kimi）默默甩出最后一 炸：完成5亿美金的新一轮融资。 据了解，本轮融资由IDG领投，阿里、腾讯等 月之暗面老股东超额认购，公司投后估值达43亿美元。据"智能涌现"了解，月之暗 面这一轮超额认购的老股东，还包括高榕创投和今日资本。 超额认购，意味着老股东对被投项目持续看好。 所谓超额认购（Super Pro Rata），通俗来说，这是一种让早期投资者在后续融 资中"加仓"，并扩大持股比例的特殊权利。 举个例子，机构A在投前占月之暗面股比5%，而在引入新股东后，机构A想维持5%的份额，需要继续下注（Pro Rata），那如果 想要获得5%以外的更多份额，就要 ...

Core Insights - Kimi has successfully completed a $500 million Series C funding round, achieving a post-money valuation of $4.3 billion, following the acquisition of Manus [1][2] - The company has reported a significant increase in paid users, with a month-over-month growth of over 170% from September to November 2025, and a fourfold increase in overseas API revenue during the same period [2][9] - Kimi's advancements in technology, particularly with the release of the K2 Thinking model, have driven rapid commercialization and product development [3][9] Funding and Financials - The Series C funding round saw participation from major investors including Alibaba, Tencent, and existing shareholders, with cash reserves exceeding 10 billion RMB [2][9] - Kimi's B/C funding rounds have raised more than most IPOs and directed offerings, indicating a strategic preference for private funding over immediate public listing [5][9] - The funds from the recent financing will be allocated towards expanding GPU resources and accelerating the development of the K3 model, as well as employee incentive programs [10] Technological Advancements - Kimi has launched the K2 and K2 Thinking models, marking significant breakthroughs in complex reasoning and long-chain thinking capabilities, with the K2 model being the first in China to reach a trillion parameters [3][8] - The K2 Thinking model allows for continuous self-reasoning and tool invocation, enabling the model to perform complex tasks autonomously, which is a shift from traditional models that primarily generate text [3][7] - Future developments will focus on the K3 model, which aims to enhance computational efficiency and generalization capabilities, potentially increasing equivalent FLOPs by an order of magnitude [6][11] Strategic Goals - Kimi aims to surpass leading companies like Anthropic and establish itself as a world leader in AGI, with a focus on innovative and unique model capabilities [6][11] - The company plans to integrate model training with product development to enhance user experience and meet real-world application needs, rather than solely focusing on benchmark scores [7][11] - Kimi's vision for 2026 includes a commitment to exploring uncharted technological territories and delivering unique contributions to human civilization through its innovations [11]

出走新加坡的Manus被高价收购的消息刷爆了创投圈，相比之下，今天月之暗面的5亿美金融资的消息，却显得平静许多。同处于AI领域，国内创投态度 为何会出现这样的反差？到底什么样的企业才应该被追捧？ AI领域的热度在这几天达到了一个新的高度。Manus被Meta高价收购，智谱和MiniMax即将上市之际，另一家大模型企业月之暗面宣布了新一轮融资消 息。 12月31日，月之暗面创始人、CEO杨植麟在内部全员信中宣布，公司已完成5亿美元C轮融资，当前账面现金储备超100亿元人民币。据悉，本轮融资由 IDG领投，阿里、腾讯等老股东超额认购，投后公司估值达43亿美元。 全员信同时披露了公司亮眼的业务表现：受K2 Thinking大模型带动，Kimi全球付费用户数月增速达170%，海外大模型API收入增长4倍。具体来看，Kimi 产品自5月起高频推出Agent功能，陆续发布Researcher、OK Computer、PPT、Kimi Code等新品，功能持续完善；依托K2模型的领先表现，C端商业化实 现指数级增长，9-11月海外及国内付费用户数平均月环比增长超170%，同期海外API收入亦增长4倍。 关于上市规划，杨植麟 ...

摘要：对于超百亿现金储备的用途，杨植麟在内部信中明确表示，将"更加激进地扩增显卡，加速K3模型的训练和研发。" 来源：凤凰网科技 凤凰网科技 出品 作者｜董雨晴 12月31日，凤凰网科技获悉，在2025年的最后一天，月之暗面CEO杨植麟对内做了一个简单的沟通。 他通过内部信告知，月之暗面近期完成了5亿美元C轮融资且大幅超募，当前现金持有量超过100亿元。"相比于二级市场，我们判断还可以从一级市场募集 更大量资金，事实上，我们B/C轮融资金额就超过绝大部分IPO募资及上市公司的定向增发。" 另据《晚点LatePost》报道，Kimi的此次融资IDG领投了1.5亿美元，阿里、腾讯、王慧文等老股东均超额认购，投后估值43亿美元，约合300亿人民币。其 中，王慧文已经累计投资月之暗面 7000 万美元。 "他们前后只用了不到两个月，属于超额融资。" 一位接近月之暗面的人士称。 Kimi原本想在今年保持低调，但外部环境已发生诸多变化——曾经拿来比较的其他头部AI公司都在冲击上市。最快下个月，2026年开年，智谱与Minimax都 将登陆港股。 作为对比，以每股116.20港元发行价计算，扣除相关费用后，智谱本次IPO募 ...

每经记者｜李宇彤 每经编辑｜段炼 陈俊杰 大模型行业的生存竞赛，已悄然进入新阶段。 12月31日，《每日经济新闻》记者获悉，月之暗面（Moonshot AI）"90后"创始人杨植麟发布内部信，其透露："公司近期完成了5亿美元C轮融资且大幅超 募，当前现金持有量超过100亿元。" 图片来源：视觉中国（资料图） 2025年底，行业正驶入快车道，上市潮起之际，月之暗面却明确表示不急于叩响资本市场大门。杨植麟在信中称："相比于二级市场，我们判断还可以从 一级市场募集更大量资金。事实上，我们B/C轮融资金额就超过绝大部分IPO募资及上市公司的定向增发。所以我们短期不着急上市，也不以上市为目 的。" 就在2025年12月中旬，大模型独角兽智谱AI与MiniMax已相继通过港交所聆讯。两家企业近两日先后开始招股，预计分别于2026年1月8日、1月9日登陆香 港交易所。 对月之暗面旗下的Kimi来说，2025年是技术持续演进的一年。杨植麟在内部信开头即祝贺团队取得"SOTA成绩"（业界顶尖水准）。他写道，K2和K2 Thinking的发布标志着公司在AGI道路上走出重要一步，并列举了"中国首个万亿参数基座模型""第一个开源的 ...

Core Insights - The Kimi K2 Thinking model reportedly cost only $4.6 million to train, which is lower than the $5.6 million for DeepSeek V3, raising questions about the valuation of closed-source giants in Silicon Valley [13][14]. - The Kimi K2 model is causing a migration trend in Silicon Valley as it offers superior performance at a lower cost compared to existing models [5][6]. - The Kimi K2 model utilizes innovative engineering techniques, including a self-developed MuonClip optimizer, which allows for stable gradient training without human intervention [18]. Training Cost and Performance - The training cost of Kimi K2 is claimed to be $4.6 million, significantly lower than other models, prompting reflection within the industry [13][14]. - Investors and companies are migrating to Kimi K2 due to its strong performance and cost-effectiveness, with reports of it being five times faster and 50% more accurate than closed-source models [8][6]. Technical Innovations - Kimi K2 has optimized its architecture by increasing the number of experts in the MoE layer from 256 to 384 while reducing the number of active parameters during inference from approximately 37 billion to 32 billion [16]. - The model employs Quantization-Aware Training (QAT) to achieve native INT4 precision inference, which enhances speed and reduces resource consumption by about 2 times [21]. Community Engagement and Future Developments - The team behind Kimi K2 engaged with the developer community through a three-hour AMA session, discussing future architectures and the potential for a next-generation K3 model [22][24]. - The team revealed that the unique writing style of Kimi K2 results from a combination of pre-training and post-training processes, and they are exploring longer context windows for future models [26][27].