Good day, ladies and gentlemen. Thank you for standing by, and welcome to Alibaba Group's December Quarter 2025 Results Conference Call. At this time, all participants are on listen-only mode. After management's prepared remarks, there will be a Q&A session. I would now like to turn the call over to Lydia Liu, Head of Investor Relations of Alibaba Group. Please go ahead. Thank you. Good day, everyone, and welcome to Alibaba Group's December quarter 2025 earnings conference call. Joining us today are Joe Tsai, Chairman, Eddie Wu, Chief Executive Officer, Toby Xu, Chief Financial Officer, Jiang Fan, Chief Executive Officer of Alibaba E-commerce Business Group. I would like to remind you that this call is also being webcast on our corporate website. A replay of the call will be available on our website later today. Now, I will quickly cover the Safe Harbor. Today's discussions may contain forward-looking statements based on current expectations and assumptions that are subject to risks and uncertainties. Actual results may differ materially. Please refer to the Safe Harbor statements that appear in our press release and investor presentation provided today. Please note that certain financial measures are expressed on a non-GAAP basis. Our GAAP results and reconciliations of GAAP to non-GAAP measures is included in today's earnings press release and investor presentation. Our comments will be on year-over-year comparisons unless we state otherwise. Now I will turn the call over to Eddie. Oh. Thank you and welcome to this quarter's earnings call. Over the past quarter, we maintained strong investment momentum in our two strategic priorities, AI + Cloud and AI + Consumption. Cloud Intelligence Group revenue growth accelerated to 36%, while our Quick Commerce business continued to expand in scale with ongoing improvement in unit economics. With the dawn of the AI agent era, the addressable market for AI infrastructure providers like Alibaba is set to grow exponentially. AI models and their capabilities are rapidly being embedded into mainstream work environments across all industries, with token consumption surging across sectors. Cloud and software budgets for enterprise IT services have traditionally represented only around 5% of corporate revenue. As model-driven agents begin to handle mainstream work tasks across industries, our total addressable market will expand by several multiples. From AI infrastructure to the application layer, Alibaba has built a complete full stack AI capability set to support the exponential growth in AI demand. Faced with an industry transformation and strategic opportunity of this magnitude, Alibaba Group is itself entering a new phase of entrepreneurial reinvention and critical investment oriented toward the future. Next, let me share Alibaba's AI strategic roadmap. We have complete full stack AI capabilities. Chips and cloud computing form the AI infrastructure layer, while the AI application layer is anchored by Alibaba Token Hub and comprises foundation models, MaaS, and both enterprise and consumer applications. Together, these give us end-to-end coverage across the full stack from AI infrastructure to applications. Given the enormous and sustained growth momentum of the AI market, combined with Alibaba's full stack positioning across the AI value chain, the business goal of Alibaba's AI strategy is very clear. Over the next five years, our goal is to surpass $100 billion in combined cloud and AI external revenue, including MaaS. Regarding our infrastructure, driven by sustained strong AI demand, Cloud Intelligence Group's revenue from external customers accelerated to 35% this quarter, with AI-related product revenue delivering triple-digit year-over-year growth for the 10th consecutive quarter. Cloud Intelligence Group's market share has grown for three consecutive quarters, rising to 36%, with our lead continuing to widen. Alibaba Cloud's cumulative external revenue through February for fiscal year 2026 officially surpassed RMB 100 billion. Over the past three months, token consumption on the Model Studio platform has grown by 6x. We expect MaaS to become Cloud Intelligence Group's largest revenue product. T-Head's proprietary GPU chips have achieved scaled mass production. As of February 2026, T-Head had cumulatively shipped 470,000 AI chips. In real-world business deployments through Alibaba Cloud, more than 60% of T-Head chips serve external customers, and we've completed scaled adoption for external customer AI workloads. T-Head now supports the AI workloads of over 400 enterprise customers across industries, including internet, financial services and autonomous driving. We're confident that T-Head's compute supply capacity will continue to expand, contributing high quality compute to our cloud infrastructure and MaaS platform, strengthening the overall competitiveness of our cloud services. Regarding our application layer. Centered on the core mission of creating, delivering and applying tokens, we established the new Alibaba Token Hub business group, ATH. It comprises Tongyi Lab, the MaaS business line, the Qwen business unit, the Wukong business unit, and the AI innovation business unit. It is the organizational foundation for executing Alibaba's AI strategy and the hub for efficient coordination across our AI businesses. During Chinese New Year, we launched our latest generation large model, Qwen3.5-Plus, which delivered outstanding performance across comprehensive benchmarks in reasoning, coding, and agentic capabilities. Qwen3.5-Plus demonstrated significant improvements in inference efficiency through foundational architectural innovation. Building on Qwen3.5, we will soon release the next generation of models optimized for coding and agentic use cases. On the consumer application side, powered by the strength of our models, Qwen's consumer-facing monthly active users have surpassed 300 million. During Chinese New Year, we deepened integration across Alibaba's ecosystem, connecting Qwen App with Taobao instant commerce, Alipay, Fliggy, Damai and Amap, giving it unique capabilities relevant to everyday life and becoming China's first all-in-one personal AI assistant for life, work and learning. We've also recently launched Wukong, our enterprise AI agent platform. Wukong is the world's first AI native enterprise-grade agent platform, enabling AI powered upgrades to enterprise workflows while remaining compatible with each organization's data permissions and management processes. It serves as the unified interface for Alibaba's AI capabilities in enterprise work environments and the B2B capabilities of businesses across Alibaba's full ecosystem will be progressively integrated to support Wukong in becoming the best AI work assistant. On Alibaba's other strategic priority, the consumption segment, we continued to advance our strategic initiatives. This quarter, our Quick Commerce business further expanded and scaled with continued share growth, high customer retention and sequential improvement in both unit economics and average order value. At the same time, Quick Commerce and E-commerce demonstrated clear synergies, driving Taobao app monthly active consumers to double-digit year-over-year growth. That concludes my remarks. I'll now hand over to Toby to share the financial update. Thank you. Thank you, Eddie. Our strategic priorities are clear. We remain focused on AI + Cloud and AI + Consumption businesses. We are seeing great momentum with gains in technology, customer adoption, market share, and user engagement. On AI + Cloud, we have the full stack AI capabilities with all three core elements, model, cloud infrastructure, and chips, and leadership in each with Qwen, Alibaba Cloud and T-Head. We also operate the most comprehensive consumer ecosystem in China that can monetize through AI. The launch of Qwen App was a major milestone, and it can bring our consumer applications together. On consumption, our Quick Commerce business continued to gain GMV market share in December quarter, while unit economics and AOV also continued to improve. Now let's look at the financial results. On a consolidated basis, total revenue was RMB 284.8 billion. Excluding revenue from Sun Art and Intime, revenue on a like-for-like basis would have grown by 9%. Total Adjusted EBITDA decreased by 57%, primarily due to our strategic investments in technology-related innovation initiatives in the consumption front, including Quick Commerce business, partly offset by the improved operating results in cloud business and enhanced operating efficiencies across various businesses. Our GAAP net income was RMB 15.6 billion, a decrease of 66%. Operating cash flow was an inflow of RMB 36 billion. Free cash flow was RMB 11.3 billion, a decrease of RMB 27.7 billion from the same quarter last year. We are reinvesting our cash flow to be a leader in AI and Quick Commerce. As of December thirty-first, 2025, we held $42.5 billion in net cash. Excluding debt with maturities beyond five years, our net position stands beyond $60 billion. This balance sheet strength gives us confidence to reinvest for long-term growth. Now let's look at our consumption businesses. Revenue from China E-commerce group was RMB 159.3 billion, an increase of 6%. Customer management revenue increased by 1%. The slowdown in revenue growth was primarily due to weaker transaction activities and phase out of the impact of software service fee implementation. The Taobao app achieved a double-digit increase in MAC during the quarter, driven by the growing mind share and increasing scale of our Quick Commerce business. Revenue from our Quick Commerce business increased 56% to RMB 20.8 billion. During the quarter, we executed our plan to further grow the scale of our Quick Commerce business, improve user experience, improve UE and increase AOV month-over-month during the quarter. Alibaba China E-commerce Group Adjusted EBITDA was RMB 34.6 billion, a decrease of 43%, primarily due to the investment in Quick Commerce, user experiences and technology. Going forward, this Adjusted EBITDA will continue to fluctuate quarter-over-quarter due to intense competition and significant investment in user experience. Revenue from AIDC grew 4% this quarter. AIDC's adjusted EBITDA loss narrowed significantly year-over-year, driven by a combination of logistics optimization and investment efficiency enhancement. The UE of the AliExpress's Choice business also improved on a sequential basis. Next, let's look at the business updates and results of Cloud Intelligence Group. Our cloud business delivered another quarter of accelerating growth. Revenue from external customers grew 35%, up from 29% last quarter. AI-related products continued to lead this momentum. We delivered our 10th consecutive quarter of triple-digit growth in AI revenue. Its share of external cloud revenue continued to increase. This is a clear reflection of the scale and acceleration in our AI business. Adjusted EBITDA margin remained relatively stable at 9%. We will continue to invest in customer growth and technology innovation to increase adoption of AI cloud infrastructure and strengthen our market leadership. All Other segment revenue decreased by 25% to RMB 67.3 billion, mainly due to the disposal of Sun Art and Intime businesses, as well as the decrease in revenue from Cainiao, partly offset by the increase in revenue from Freshippo and Alibaba Health. All Others Adjusted EBITDA was a loss of RMB 9.8 billion, primarily due to the increased investment in technology businesses including Qwen models and the consumer facing Qwen, partly offset by the improved results of Cainiao, Hema, Ele.me and other businesses. Qwen Model has become one of the most widely adopted open source model families globally, surpassing 1 billion cumulative downloads on Hugging Face by the end of this January. The consumer facing Qwen has surpassed 300 million MAU across platforms, which reinforces user engagement and expands long-term monetization potential. We have been increasing investments on these technology fronts, including the Spring Festival campaign. Building on the strong momentum and results achieved, as Eddie mentioned earlier, we will continue to invest substantially in Qwen models and Qwen App. Our unallocated Adjusted EBITDA was a loss of RMB 2.7 billion compared to a loss of RMB 0.2 billion in the same quarter last year, which reflected costs associated with talent retention incentive from the one-off replacement awards plan of Ele.me. Thank you. We will now open for Q&A. Hi everyone. You're welcome to ask questions in Chinese or English. A third party translator will provide consecutive interpretation. In the case of any discrepancy, our management statement in the original language will prevail. If you are unable to hear the Chinese translation, bilingual transcripts of this call will be available on our website within one week after the end of the meeting. Operator, please go ahead with the first question. Thank you. Thank you. If you would like to ask a question, you can press star then one on your phone and wait for your name to be announced. If you are on a speakerphone, please pick up your handset to ask your question. To give more people the opportunity to ask questions, please keep yourself to no more than one question at a time. First question today comes from Robin Zhu at Bernstein. Please go ahead. Thank you. Thanks management for taking my question. Could you give us some specific examples of how Token Hub will change how the different cloud and AI businesses work together going forward, from an organizational standpoint? You know, strategically, what changes or goals are you hoping to achieve with this new structure that, you know, improves on the previous arrangement going forward? You know, if management could share a hierarchy of priorities in cloud and AI, is it market share and revenue growth such as the target you just announced, versus having, you know, the best first party model capabilities versus consumer side traction with customers using agentic AI or anything else? Thank you. 好，感谢管理层接受我的提问。首先是不是可以请你们介绍一下，现在有了Token Hub之后，从组织设计的角度来讲，不同的云和AI相关的业务，协作的方式会产生什么样的新的变化？另外从战略的角度来讲，就是有了这样一个新的结构之后，会带来什么样的改变，或是有助于实现什么样的新的目标是更加优于之前的安排。另外想请教管理层是不是可以给我们阐述一下你们在云和AI方面的这个优先级，比如说第一大优先级是市场份额和这个收入增长呢，如你们刚才所宣布的这个目标，还是说第一大优先级是要拥有最好的这个模型能力，还是说要发展更多的消费者消费端的这个使用，或者是AI智能体等等，那么呢，就排一个优先的一个顺序。谢谢。 非常感谢你的提问。我觉得我们成立ATH事业群的目的和现在的这个时代，或者说这个技术变革的背景有关系。因为从2025年的下半年到2026年的前面这两三个月，我们已经看到了，就是AI已经进入到agent驱动的这个时代。而agent驱动的这个时代和我们前面的，就是说前面早期的AI这个阶段最大的区别在于模型与应用之间的紧密配合，对于怎么样做好模型以及发展应用至关重要。因为在AI的早期，其实预训练的很多数据来自于一些静态的数据。那当我们现在开始进入到agent的时代之后，其实我们大量的来自于怎么去提升模型的能力，或者说帮我们的应用做得更好的能力，来自于模型和应用的紧密结合，以及在客户的使用场景当中的紧密的数据联调。所以从这个角度上来说，我们觉得在我们的如果看AI的五个层面的话，第一个应用层，第二个是模型层，然后在下面是AI基础设施类似云计算，再到下面的芯片层的话，我们觉得在这个agent的时代，模型和应用的紧密配合是一个更关键的事情。 Great, thank you very much for your question. I think that the goal and purpose of the establishment of the ATH business group is very much connected to the era that we're now in as of the end of 2025 and going into the first few months of 2026 in terms of the development of AI. You know we're now in the agent-driven era of AI development. This is different from the earlier period of AI development in the agentic AI era. We need to achieve a very close integration of model with application. In the earlier AI era, a lot of model training data was static data, but in the agentic era, we need to enhance the integration between models and applications, and achieve tight integration. A lot of the data is now coming from the customer side. If you look at the different layers involved in AI deployment from application, model, the AI infrastructure, through to chips, I think what's most different and most important about the agentic AI era is the need to achieve this tight integration between the application and model. That's the critical priority. 好，然后我再来解释一下我们这个ATH内部的几个业务之间的一个关联吧。就是从我们的从现在行业看到的未来的发展趋势来说，我们也觉得已经看得非常清楚，就是说未来的AI agent在应用层会有一个这个生态会创新，会非常，会那个非常多，然后这个在应用层的各类的应用也会非常的丰富。那么在这个应用层呢，我们呢自己的布局，我们觉得我们会有一个自己的Qwen App作为我们在这个应用层的一个To C的个人助理，那我们希望把我们的Wukong打造成为一个在中国企业面向To B的一个个人助理。但同时我们，我们觉得在AI应用层会有非常多的各种行业应用，或者垂直应用，或者说各类不同场景的AI agent的应用，再去支持各个行业的发展。所以我们在，在这个，在这个应用层之外，我们还需要有一个我们强大的一个MaaS业务。其实MaaS业务是贯穿就是在模型和应用层之间的一个渠道，而MaaS业务将会在支持我们自己的内部的应用之外，我们还需要通过一个强大的MaaS业务来支持外面更多的丰富多彩的，丰富多彩的这类AI的这些行业应用。那我们觉得这个市场价值，市场空间也会，也会非常大。所以从这个角度上而言，我们觉得AI应用层是未来的模型，模型AI token的一个最大的，最大的一个分销渠道，而最强的一个模型能力会吸引更多的应用来使用我们的模型，而一个更加高效的，更加高效或者更能力更强的一个MaaS产品，将会把这两者之间衔接得更好。这是我们在这个事业群当中设计的一个业务逻辑。 Next, let me address the interconnection and synergies among the different businesses in relation to ATH. If you look at the trends of where this industry is going, and we think we see these trends very clearly, the AI agents will be tightly integrated together with the application layer. There will be a multitude of highly diverse applications. In the B2C space, we're strongly developing the Qwen app as a personal assistant for individuals. In the B2B space, we're positioning Wukong as a B2B assistant. In the AI application layer, there will be a multitude of different industry and vertically specialized applications to serve different industry use cases. All of this needs to be supported by a very robust model as a service MaaS layer. MaaS supports, of course, our own internal applications, as well as a multitude of external and industry specific use cases that leverage AI. In this context, we see massive value that we can provide and a huge total addressable market, or TAM. Going forward, we see the AI application layer as the main channel through which tokens will be distributed. The stronger the model capabilities that you can offer at the MaaS layer, the more attractive and compelling all of these different offerings will be to customers. That is the business logic that we have laid out within this new business unit. From the perspective of both the model and the application layers, our top priority absolutely is to develop the most intelligent models. I really need to emphasize that only when you have the most powerful models can you truly drive the deployment of AI applications across all kinds of different industries. Only with the strongest models can you attract applications from across diverse industries to adopt our MaaS offering. However, in order to build the most robust models, you need to have very close collaboration with various industries and with our own to 2C and to 2B applications to connect with our MaaS to applications across all kinds of different industries and use cases. We need to get more users to leverage and make use of our models in order to gradually be able to leverage the data flywheel effect. Only in that way can we continuously enhance the capabilities of our models. That's one of the reasons why we have established the ATH business unit at this time. To summarize, I would say our top priority is definitely to enhance model capabilities. However, to enhance model capabilities requires concerted efforts across the entire model pipeline as well as on the application and infrastructure sides in order to achieve sustained improvements over the long term. Next question, please. Thank you. Your next question comes from Joyce Ju at Bank of America. Please go ahead. Good evening, management. Congrats on the solid progress you've made in cloud and AI, and thanks for taking my question. My question is. We see CMR growth slowing notably in the December quarter, given the macro pressures. We have seen China's online retail sales only up 2% year-over-year in the fourth quarter 2025. More recently, NBS data point to a re-acceleration in January and February. Could you share your latest view on the CMR trends heading into the March quarter and whether you have started to see any improvement in consumer sentiment? Thanks. 没听清百分之多少。那么最近我们还是看到一月和二月这个在线零售的增速是重新加速的，那是不是可以请你们介绍一下，进入到三月份季度，你们对于CMR趋势的最新的看法，然后消费者端你们是不是开始看到有什么的改善？谢谢。 我来回答一下这个问题。刚才你也提到，十二月季度，因为宏观消费疲软、暖冬以及今年春节比较晚等因素，使得我们十二月季度增长受到了比较大的挑战。同时因为大促季延长，我们在消费者权益投资较往年也有所增加，所以我们十二月季度的CMR跟电商利润都有放缓。那么我们也看到，今年一季度以来，我们看到消费复苏还是非常明显的。那么同时在我们即时零售战略的共同拉动下，我们的食物电商成交跟CMR增速都有显著回升，那我们电商的利润也有显著的改善。 Thank you for your question. Indeed, in the December quarter, weak macro consumption, warm winter, the later timing of the Chinese New Year, challenged the growth for the December quarter. Due to the extended promotional season, our investments in consumer benefits increased compared to previous years. As a result, the CMR and EBITDA trend softened. Going into the March quarter with the improving consumer sentiment that we've observed and momentum from our Quick Commerce strategy, our physical goods GMV and CMR trend have significantly recovered from the December quarter and EBITDA is expected to improve accordingly. All right, let's move on to the next question. Thank you. Your next question comes from Gary Yu at Morgan Stanley. Please go ahead. Hi, thank you management for the opportunity. My question is related to Quick Commerce. I understand that, you know, in the past couple of months, we have achieved certain milestones in terms of GMV market share and also UE improvement. How should we look at the priority going forward? Are we aiming for, you know, share, or hoping to take this opportunity to improve unit economics, reduce loss, and how should we look at the synergy between Quick Commerce and traditional E-commerce, and how should we see these synergy to translate into CMR better growth going forward? Thank you. 好，感谢管理层接受我的提问。我的问题是关于即时零售这一方面。我知道过去几个月，公司已经在市场份额，还有UE改善这些方面取得了一些阶段性的成果。那么面对未来，我们的优先级会是什么？是市场份额，还是希望利用这个机会来进一步的优化UE和收窄亏损。另外，我们应该如何看待即时零售和传统电商之间的协同，并且这些协同将来会如何转化为CMR更快的一个增速？谢谢。 我来回答这个问题。我们继续看到在市场份额提升的同时，我们通过物流效率提升、商业化能力的改善，还有我们订单结构的优化，那他们进一步驱动了UE的明显的，就是我们的UE还是在持续的优化中。那么我们认为，未来几个季度我们的UE会进一步的好转。 Certainly. Well, while growing our market share, we have continued to significantly improve UE, driven by improvement in fulfillment, logistics efficiency, by improvement in monetization, as well as by order mix optimization. Driven by those factors, we expect to further optimize UE in the coming quarters. 我们也看到，过去一年闪购对平台整体的拉动明显，包括闪购在内的电商大盘年度活跃买家增长了1.5亿。食物电商的年度活跃买家增长了1亿，那么淘宝食物电商年度活跃买家增长超过了过去三年的总和。那新的用户相比成熟用户短期的客单价跟购买频次相对较低，但我们希望在未来持续提升这部分的ARPU值跟购买频次，这也是未来平台几年增长的新引擎。那么同时我们也看到闪购对相关品类拉动明显，特别是对食品、生鲜、健康等相关品类拉动明显，那同时也推动了盒马、超市等即时零售业务的加速发展。 In terms of the positive impact that Quick Commerce is bringing to our conventional E-commerce business and to our entire ecosystem, we saw a very significant increase in AACs on the platform in the past year. Our AAC number increased 150 million in 2025, including 100 million conventional E-commerce physical goods AACs, which is more than the previous three years combined. Now new consumers ARPU and purchase frequency are lower than that of existing users, so we aim to continually increase their ARPU and purchase frequency, which will serve as a new growth engine for our platform in the coming years. Quick Commerce is clearly driving sales in various categories such as food and fresh produce and healthcare, and is contributing to Freshippo and Tmall Supermarket's accelerated growth. 关于未来的发展预期，首先我们维持FY28即时零售整体交易规模过万亿的目标。在此规模基础上，我相信我们可以实现规模化的正向现金流。同时我们预计FY29即时零售业务板块将实现整体盈利。 In terms of the outlook, we maintain our target of achieving over RMB 1 trillion in Quick Commerce GMV by FY 2028. We expect to generate positive cash flow when the GMV target is achieved, and we expect the Quick Commerce business to be profitable in FY 2029. 闪购跟即时零售已从新客获取、促进用户活跃、满足用户多元化的消费场景、拉动成交跟商业化，以及物流基建等多方面，成为淘宝、天猫电商板块的基石性业务，对于淘天在AI时代的长期发展起到至关重要的战略作用。未来两年，我们会以实现整体规模过万亿的目标，继续坚定投入，同时实现市场地位领先。 Quick Commerce has become a cornerstone of our E-commerce business, playing a strategically vital role in the AI era by driving customer acquisition, enhancing user engagement, fulfilling diverse consumer demands, increasing transactions, and improving monetization and supporting logistics infrastructure. We are committed to investing in Quick Commerce in the next two years towards achieving the RMB 1 trillion GMV target as a market leader. Operator, let's move on to the next question. Thank you. Your next question comes from Alicia Yap at Citigroup. Please go ahead. Hi. Good evening, management. Thanks for taking my question. I have a question regarding your chip business T-Head, Pingtouge. There have been reports that Alibaba plans to spin off the T-Head unit as a separate listing. Can management provide any information of this? If so, what is the expected time frame for this to occur? In the meantime, can you share more operating metrics? In addition to the 470,000 chips that you mentioned you ship to external customers, how do we reconcile that number, the shipments to the revenue size? Also, what is the expected growth rate for your chip business in the coming year? I think you mentioned currently 60% of this is from external customers. Maybe can you also share with us, are these chips, you know, for external customers mainly used for inferencing? For internal, is it used for model training and also inferencing? Lastly, how do Pingtouge's chips or T-Head's chips compare to other domestic chips? If management can share some details, it will be great. Thank you. 感谢管理层接受我的提问。我想问一些关于芯片业务，就是平头哥方面的问题。最近有报道说阿里打算将平头哥分拆上市，管理层是否可以对此提供一些信息？另外是不是可以提供一些平头哥的业绩数字？比如说刚才讲了，就除了你们交付的47万个芯片之外，这个收入是多少？那么芯片业务比如说未来一年的预期的增长率是多少？然后刚才你们好像讲到了，其中有50%是来自…… 60%，60%是来自外部客户的？ 需求，那是不是也可以展开介绍一下这些芯片，就提供给外部客户的芯片主要是用于推理吗？那如果是内部使用的话，是用于模型的训练，还是用在其他的方面？另外平头哥的这个芯片相比较其他的国产芯片，是怎么样的一个比较，能不能展开介绍一些细节？谢谢。 好，谢谢，谢谢。非常感谢你这个问题。平头哥是阿里巴巴全站AI布局的重要一环，我也想趁此机会详细介绍一下。在当前的国内的AI芯片生态中，我们觉得平头哥的技术能力和产品能力都处于第一梯队。我们的产品覆盖从训练、微调到推理的完整AI工作流。我们的平头哥的AI芯片已经通过阿里云在训练场景、百炼的推理场景深度大规模地使用。同时在阿里云的公共云和混合云产品中，我们也有60%以上的平头哥的芯片在被外部的商业化客户使用。 外部的商业化客户涵盖互联网、金融、智能驾驶和智能制造多个行业。这些外部的商业化客户在用平头哥的芯片当中，在用他们的训练和推理场景都有使用。而且我们在平头哥的软件栈上具备与CUDA生态系统的一个良好的适配性，所以我们的客户在迁移他的系统，迁移他系统的项目过程当中，花的时间非常少。那另外一点，我觉得平头哥对于阿里巴巴而言，一个重要性除了是因为我们希望在国产芯片相对来说，比国外的芯片在各方面的制造制程啊，各方面的这个芯片的性能方面，与国外的芯片有一定落后的情况下，我们希望在与阿里巴巴的云的基础设施，以及通义千问的模型有更深度的协同设计，以提升更好的性价比。所以这个是我们做平头哥芯片的一个与外面的这些芯片公司不太一样的一个点。所以更多的是希望可以创造我们更高的一个AI能力的一个性价比，也可以成为我们今后百炼平台能够降低我们百炼平台推理成本的一个重要产品。那然后还有一个，除了在整体提升我们的整体的AI效率、降低成本之外，我觉得还有一个在现在中国的这个AI行业，一个特殊情况下，我觉得有一个对我们的一个重大价值，就是整个AI算力的供应保障。因为在现在我觉得未来三到五年，全球的AI算力都会处于一个非常紧缺的三到五年，尤其是在中国市场更会紧缺。那作为在中国市场唯一具备自研芯片能力的云计算公司，那平头哥对于阿里集团来说也会是至关重要。能够提供更多的AI算力的供给，将会帮助我们的云和AI业务，包括我们的MaaS业务获得一个更高的增长动能。 Okay. Thank you very much for this question. I'd like to take the opportunity to expand on this a bit because T-Head is a very important component of Alibaba's company-wide AI strategy. In the context of China's domestic AI chip ecosystem, we firmly believe that T-Head is ranked in the top tier of the domestic AI chip ecosystem in terms of the technology capabilities and product capabilities. Our products cover the entire AI workflow from model training and fine tuning through to inference. Our T-Head AI chips are already in extensive, large-scale use via Alibaba Cloud, both for training workloads and for Bailian inferencing use cases. At the same time, over 60% of T-Head chips are being used by external commercial customers across Alibaba Cloud's public and hybrid cloud offerings. The external commercial clients span multiple industries, including internet finance, autonomous driving, and intelligent manufacturing. These external commercial customers are utilizing T-Head chips in both their training and inferencing workloads. Moreover, on the T-Head software stack, we have excellent compatibility with the Linux ecosystem, so customers can migrate their systems easily without spending a lot of time on the migration. Another point I would make is that in my view, T-Head's significance to Alibaba lies not only in our aspiration to close the gap between domestically produced chips and foreign counterparts, foreign produced chips in terms of manufacturing processes and overall performance across various dimensions. Given that our chips still lag behind foreign counterparts in performance in various respects, we aspire to engage in more profound co-design with Alibaba's cloud infrastructure and the Qwen model to provide improved cost effectiveness. This is one key differentiator in how we approach chip design at T-Head that sets us apart from other chip companies. Our primary goal is to create AI capabilities that offer superior value for money. This will make it a key product for the Bailian platform, allowing us to reduce inference costs going forward. Beyond generally improving our AI efficiency and reducing costs, there's another factor at play, namely the unique circumstances currently facing the AI industry in China. In that context, one significant benefit for us is the guaranteed supply of AI computing power. Because I believe that over the next three to five years, global AI computing power will be in extremely short supply, especially in the Chinese market. As the only cloud computing company in the Chinese market with proprietary chip development capabilities, T-Head is of paramount importance therefore to the Alibaba Group. Increasing the supply of AI computing power will help our cloud and AI businesses, including our MaaS business, to achieve stronger growth momentum. 好，我再最后稍微分享一下我们未来的一些预期吧。就平头哥，我们在前面两年历史上已经成功地商业化应用，推出的芯片规模超过了47万片，那年化营收规模也达到了百亿级别。那在未来，在今年26、27年，今年26以及明年的27年，我们预计平头哥可以生产的高质量的AI芯片的规模还会持续扩大，为我们整个集团的AI业务提供充足的算力保障，也能够为整体的AI业务提供一个非常强大的增长动能，同时对未来的提升的盈利水平也会…… 未来提升盈利水平也会非常有帮助。那总的来说，平头哥的价值对阿里巴巴不仅是成本优化，而且更是供应保障吧。在算力稀缺的时代，我觉得对阿里巴巴的AI战略来说至关重要。所以平头哥有一些可能我们在未来并不排除去做IPO，但是现在还没有一个明确的时间表。 At T-Head, over the past two years, we've successfully commercialized and launched chips with total volume exceeding 470,000 units, with annual revenue reaching the RMB 10 billion level. Looking ahead to 2027, well through 2026, this year through 2027, next year, we expect T-Head's production capacity for high-quality AI chips to continue to expand. This will provide robust computing power support for our group's AI business and serve as a powerful growth driver for our overall AI initiatives. We also believe that future improvements in profitability will be achieved, further enhancing profit levels, which will also be very beneficial. Overall, T-Head's value to Alibaba goes beyond cost optimization. It primarily serves to ensure supply chain resilience. In an era of scarce computing power, I see this as crucial to Alibaba's AI strategy. It is possible and we don't rule out the idea of T-Head considering an IPO in the future, although we currently do not have any definitive timeline. Next question, please. Thank you. The next question comes from Yuan Liao at CITIC Securities. Please go ahead. 管理层晚上好。感谢接受我的提问。我的问题是关于你们提到的阿里巴巴集团AI战略的商业目标。未来五年的收入要突破1,000亿美元，那管理层能否给出这一目标的更多的细节？比如说，未来五年是到2031年，那这对应大概多少CAGR的一个增长。那同时呢，我们能否拆解一下这个增长的一个驱动，我们应该怎么去理解？基于我们规模化的营收的一个增长，那我们什么时候可以看到阿里云的margin有一个提升的趋势？谢谢。 Thank you for taking my question, management. My question is about the business objectives for your AI strategy that you just mentioned. Revenue for the next five years is expected to exceed RMB 100 billion. Could you provide more details on this target? For example, if the next five years is through to 2031, what kind of CAGR would that correspond to in this five-year period? Could you also break out what will be driving that growth and how we should understand those drivers? Given this scalable growth in revenue, when can we expect to see sustained improvement in Alibaba Cloud's margins? Thank you. 好，非常感谢你的问题。我觉得对于未来五年的AI与云相关的业务的营收突破一千亿美元，从我们现在的市场增长的容量，以及我们现在的基础和我们的产品基础上来说，我们的目标和路径都是可见性还是比较强的。 Thank you for your question. Yes, we certainly believe that within five years, revenues from our AI and cloud related business will exceed $100 billion. We think that is very clear. If you look at the market growth that we're seeing today and the strength of our product portfolio, and the roadmap to get there. 我觉得最大的，最大的增长动能还是来自于AI，来自于AI大模型的能力的突破。我们看到在2026年，在这一... 二零二六年的这两个月，这几个月，我们已经看到了非常明显的一些趋势，就是我们看到大模型开始具备了完成To B的复杂工作流的能力。当我们看到越来越多的公司内部在启用大模型产生的agent，在帮他完成端到端的工作任务的时候，其实我们整个的原来AI和云面向的这个IT预算的这个市场，其实发生了一个根本性的改变，也就是大量的企业在用token消耗的时候，他并不把token当成是他的IT预算，而是把它当成了整个公司的生产或者研发成本，是它的生产资料的一部分。所以这是我们看到一个对未来的AI增长有一个长期性的最根本的…… 我们看到一个最根本的一个内在因素吧。 I think that the major driver underlying all this really is continued breakthroughs in the capabilities of large AI models. We've certainly seen a very clear trend over the past couple of months, the first two months of 2026, whereby large models have now gained the capability to execute complex B2B workflows. More and more enterprises are deploying agents powered by large models to handle end-to-end business tasks. That marks a fundamental transformation in the way that the market looks at IT budgets. IT budgets traditionally allocated to AI and cloud services. The shift really is that many enterprises now, when consuming tokens, don't treat token consumption as part of their IT budget any longer. Instead, they see tokens as part of their overall operational or R&D costs. Tokens are a key component of their production inputs, not just a part of their IT budget. This is the most fundamental long-term factor that we see driving future AI growth. 我们觉得最大的三个——最大的增长动能来自于三个方面。第一方面也就是以大模型驱动的MaaS业务做一个核心的增长引擎，而MaaS业务的增长，MaaS业务的应用方，包括我们自己的应用，以及我们自己应用的客户，以及行业当中非常丰富多样的各类AI应用、应用场景，包括AI应用软件。那我们觉得这个有MaaS业务推动的增长，可能是对于未来AI和云的营收是一个核心关键的因素。然后第二点，对于AI云计算而言，还有一个非常重要的增量场景，也就是我们认为在未来基于公共的MaaS业务，我们会有一个很大的市场，但又在相当多的中大型企业，它还会有一个企业级的内部推理和训练市场，这个市场长期会基于存在，它并不是一个——它会因为每个企业会根据它自己的业务的形式，以及它这个应用场景的安全性，或者它应用场景的一个特殊性。有一些应用场景会选择使用公共的MaaS API服务，有很多的应用场景还会基于它企业内私有化部署的应用场景，而这些应用场景也是我们阿里云AI基础设施一个非常大的增量场景。 I believe that the largest drivers of growth will come from three areas. First is the MaaS driven business, which really is the core growth engine. The growth of our MaaS business will be supported by a variety of different use cases, including our own applications, as well as a diverse array of AI application scenarios from across our customer base and across various different industries, including AI application software. We believe that the growth driven by MaaS initiatives will be a key driver of future revenue for both AI and cloud services. Secondly, for AI and cloud computing, there's another very important growth opportunity. Of course, we believe that public MaaS will be a substantial market in the future, but in a considerable number of larger medium and large-sized enterprises, there'll be a demand for enterprise-level internal inference and training, a new marketplace. That market will continue to exist in the long term. It's not one that will disappear simply because each enterprise makes decisions based on its own business model and the security requirements of its specific use case or the particularity of an application scenario. For some application scenarios, enterprises will opt to use public MaaS API services, while many others will be based on privately deployed solutions within the enterprise. Those kinds of application scenarios represent a large incremental growth opportunity for Alibaba Cloud's AI infrastructure. Third, there's another important driver, important opportunity that I think tends to get ignored a lot of the time. I'm talking about CPU centric cloud computing, the traditional cloud computing, which still has significant room for expansion in this AI enabled era. Traditional cloud computing is designed for IT engineers, which in China may number a few million, say perhaps no more than 10 million, potentially traditional IT engineers. Those have been the traditional cloud computing customers. However, in the future, there could be billions of agents that are created by large AI models and their operating environments. The operating environments of these agents will also require substantial support from traditional CPU-centric cloud computing. They need these traditional CPUs as well as databases, storage, and large amounts of memory to support their long-term problem-solving and sustained operations. The challenge lies in transforming the traditional cloud computing market, shifting from a cloud platform designed for human users, those IT engineers, to one that's optimized for agent-based invocation. I believe there's tremendous room for growth there. A key challenge for us this year is transforming traditional cloud computing into a platform that is better suited for agentic use. That's a key focus of Alibaba Cloud's upgrade. As the revenue from this business continues to grow, our AI business will undergo transformation and upgrading, shifting from selling resources to selling intelligence, selling intelligent capabilities. I think that represents a massive upgrade to the business model. At the same time, by integrating our proprietary T-Head chips, we are achieving and will achieve cost reduction and efficiency gains. We believe that as our AI and cloud business continues to grow in revenue scale, cloud profitability should become increasingly visible and we see it is on a steady path of improvement. However, the process of continued improvement is not a linear one. It's possible that there could be a scale effect breakthrough, the achievement of an economy of scale, or the scaling up of our T-Head chips, and there could be a massive leap forward. I think that's you know, a function of the product as a whole and those kinds of economies of scale. It will not unfold in a linear fashion. You asked about the CAGR, the compound annual growth rate from 2026 through to 2031. You know, I think you can plug that into your calculator and figure out what it would be, assuming it were to be linear, but I don't think that it will be linear. Our R&D investment and growth in the market will not be linear. Some of the investments we're making today may not yield significant growth until one or even two years from now. However, regarding that overall five-year goal, we are highly confident in our ability to achieve it. Thank you. Operator, let's take the last question. Thank you. The last question comes from Alex Yao at JP Morgan. Please go ahead. Thank you. I'd like to shift the topic a little bit and ask a question about E-commerce. You'd previously said that we were in a three-year investment cycle for E-commerce. I'm wondering if that is now being adjusted or being driven by the new opportunities that have arisen in Instant Commerce and in Agentic Commerce. If we're still thinking of it in terms of the original three-year plan, which would put us now in the middle really of that three-year period, where I guess we would start to be reaping the returns on a stable basis from those investments. If you could speak to us about the overall direction of E-commerce in the context of that three-year investment cycle that you'd told us before, and also share with us how you're thinking about being positioned and your strategies on this E-commerce track. Thank you. Thank you. As I just mentioned, we are making a very significant investment in the instant retail business this year, the Quick Commerce business this year. At this point in time, we're seeing a highly definitive opportunity in this space. Again, as I just mentioned, we will continue to invest heavily over the next two years in order to achieve our goal of surpassing RMB 1 trillion in Quick Commerce sales. We also believe that in two years' time, our investments in Quick Commerce will generate positive economic returns for our E-commerce business as a whole. Thank you. I'd like to add to that by bringing in the dimension of AI, 'cause Eddie's talked a lot about AI. I believe that AI will also have a very significant impact on E-commerce. However, three years is too long a time to talk about when it comes to AI because AI today is evolving at a pace that's measured in weeks or in months. That's precisely why we're making significant investments on the AI front. We are leveraging AI to roll out new experiences for consumers and for merchants as well as upgrading merchants' business models with AI. We believe that AI will allow us to make huge upgrades in E-commerce across different parts of the E-commerce business. It's beneficial for our B2B business where we're seeing tremendous opportunities for its deployment, and we will actively seize on all of these new opportunities. Okay. That wraps up the Q&A session of today's earnings call. Thank you very much for joining us today, and we look forward to speaking with you soon. Thank you. That concludes the call for today. Thank you for participating. You may now disconnect your lines.