Good day, everyone. Thank you for joining Alibaba Group's March Quarter and Full Fiscal Year 2026 Earnings Call.

On the call with me 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. As a reminder, this call is being webcast live.

A replay of the call will be available on our website later today. On this call, we may make forward-looking statements and discuss certain non-GAAP financial measures.

The forward-looking statements reflect management's current expectations that are subject to risks and uncertainties. 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. With that, let me turn the call over to Eddie.

各位投资人朋友，

Welcome to Alibaba Group's fiscal year 2026 fourth quarter earnings call. Over the past quarter, Alibaba's high-intensity investment in our two strategic priorities of AI plus cloud and consumption is rapidly translating into tangible business results, with group revenue growing 11% year-over-year.

This quarter, Cloud Intelligence Group's external revenue growth accelerated to 40%, and AI-related product revenue achieved triple-digit growth for the 11th consecutive quarter. China e-commerce CMR grew 8% year-over-year on a like-for-like basis, and the quick commerce market achieved significant unit economics improvement while maintaining market share.

We are at a pivotal inflection point in the evolution from conversational chatbots to autonomous AI agents, which is directly driving explosive growth across our across three core workload categories: training, inference, and agent orchestration. Against this backdrop, Alibaba's AI has moved beyond the initial investment phase and progressed commercialization at scale.

Next, let me walk you through four areas in detail: AI commercialization, cloud infrastructure, the AI application ecosystem, and our consumption business. First, the AI and cloud commercialization inflection point has arrived.

This quarter, Cloud Intelligence Group's annualized AI-related product revenue has surpassed 35.8 billion RMB, continuing to maintain triple-digit growth. AI-related product revenue now accounts for 30% of Cloud Intelligence Group's external revenue.

We expect that in about one year, AI-related product revenue will cross the 50% threshold, becoming the primary engine driving the cloud business's revenue growth. As a result, Cloud Intelligence Group's external revenue growth is expected to continue accelerating beyond its current 40% rate over the coming quarters.

Given the certainty of long-term AI demand and our full-stack technology advantages, we expect this trajectory to sustain strong growth over the medium to long term. This reflects AI's role in driving a comprehensive upgrade of Alibaba Cloud's entire business, as its growth engine fully pivots from traditional compute and storage to models, AI compute, and agent services.

We're also seeing exponential growth in AI model and application services revenue, a new revenue engine driven jointly by foundation model services and AI-native software. Over the past 3 months, token consumption volumes on our model services platform grew substantially quarter-over-quarter as enterprise customers accelerated their shift from simple tasks to production scale and complex workloads, driving continued growth in demand for model and application services on the Model Studio platform.

We expect model and application services annualized recurring revenue, ARR, inclusive of the Model Studio platform, to surpass 10 billion RMB in the June quarter and 30 billion RMB by year-end. The high margin profile of this revenue stream is becoming increasingly apparent, making it a source of healthy, high-quality growth.

Second, our AI infrastructure underpins our full technology stack and constitutes a durable moat. T-Head's proprietary GPU chips have achieved scaled mass production, with over 60% of compute capacity already serving external customers across Internet, financial services, and autonomous driving verticals.

As the only AI cloud provider in China capable of delivering self-developed AI chips at scale, we've secured autonomy over our compute supply chain while providing customers with highly competitive AI inference and training services. In an environment of compute scarcity, this structural advantage is favorable to our revenue growth and gross margin improvement.

At the same time, our cloud products are accelerating their AI-oriented upgrade. The surge in agent workloads has significantly elevated demand for traditional cloud products built around CPU, storage, and containers, and we're upgrading these into infrastructure solutions optimized for the agent era.

Third, at the application layer, we've built a complete closed loop spanning AI-native software to a full agent ecosystem. Alibaba Token Hub, ATH, continues to launch new products, connecting consumer and enterprise environments with breakthrough progress in AI-native software and coding agents.

The Qwen model continues to iterate across reasoning, coding, and agentic capabilities. On the enterprise side, we've launched a range of products spanning intelligent workplace tools, AI coding, and business operations management, helping enterprises unlock greater productivity.

On the consumer side, the Qwen app fully integrated Taobao and Tmall's commerce service capabilities on May the 7th. With this, Qwen app is now deeply embedded across the ecosystem, spanning Taobao, Alipay, Amap, and Fliggy, making it China's first all-in-one personal assistant to seamlessly bridge everyday life, productivity, and learning.

Fourth, across our consumption business and at the group level, we're prioritizing long-term value. Beyond AI, our consumption strategy continues to progress steadily, with CMR growth rebounding significantly.

This quarter, CMR grew 8% year-over-year on a like-for-like basis as we continue to improve user experience and merchant operating efficiency. The quick commerce business achieved significant unit economics improvement while maintaining stable market share market scale.

In summary, the return on our investments in AI plus cloud and consumption are increasingly clear. AI plus cloud revenue growth is accelerating with improving margins, model and application services ARR continues to grow at pace, and operating efficiency across our consumption business continues to improve.

Facing the historical opportunity that AI represents, Alibaba is at a pivotal juncture where our technology investments are beginning to pay off commercially. We'll maintain our strategic resolve and leverage our full-stack AI capabilities to support long-term growth.

That concludes my prepared remarks. Next, I'll hand over to Toby to walk you through our financial results.

Thank you.

Thank you, Eddie. Our strategic priorities remain laser-focused on AI plus cloud and consumption businesses.

Multiple growth catalysts, including technological advancements and business innovation, are aligning to create strong tailwinds. On AI plus cloud, our full-stack capabilities span models, cloud infrastructure, and applications, with established leadership in every layer.

The strong growth of our AI plus cloud businesses and the clear path to monetization of our MaaS platform give us confidence to make significant investments to extend our leadership. On consumption, we achieved a strong CMR growth on a like-for-like basis during the quarter, and our quick commerce business continued to improve UE and AOV quarter-over-quarter.

Now let's look at the financial results for this quarter. On consolidated basis, total revenue was RMB243.4 billion.

Excluding revenue from Suning and Intime, revenue on a like-for-like basis would have grown by 11%. Total adjusted EBITA decreased 84%, primarily due to our strategic investments in technology businesses, quick commerce, and user experience, partly offset by the improved operating results supported by continued growth in consumer management service and cloud business, and enhanced operating efficiencies across various businesses.

Our GAAP net income was RMB23.5 billion, an increase of 96%, primarily attributable to the year-over-year increase in net gain from mark-to-market changes of our equity investments and disposal losses of Suning and Intime in the same quarter last year, partly offset by the decrease in adjusted EBITA. Operating cash flow was an inflow of RMB9.4 billion.

Free cash flow was an outflow of RMB17.3 billion. We are reinvesting our operating cash flow to enhance our competitive advantage in AI.

As of March 31st, 2026, we held approximately US$38 billion in net cash. Excluding debt with maturities beyond 5 years, our net cash position stands at approximately US$59 billion.

This balance sheet strength gives us confidence to invest for growth. Now let's look at our consumption businesses.

Revenue from China E-commerce Group was RMB122 billion, an increase of 6%. Customer management revenue increased by 1%.

To help merchants grow their businesses and increase willingness to spend on our platform, we upgraded our business development program for select merchants during the quarter, under which the level of platform subsidies for these merchants is directly tied to their marketing spend on our platform. For accounting purpose, such subsidies, previously recorded as sales and marketing expenses, are now recorded as a contra-revenue item to CMR.

Accordingly, CMR grew 1% year-over-year during the quarter. Excluding the contra-revenue impact from the program, on a like-for-like basis, CMR would have grown 8% year-over-year.

Revenue from our quick commerce business increased 57% to RMB20 billion. The quick commerce business further improved UE and increased AOV quarter-over-quarter, primarily driven by order mix optimization.

Alibaba China E-commerce Group adjusted EBITA was RMB24 billion, a decrease of 40%, primarily due to the investment in quick commerce, user experience, and technology, while there's positive contribution from customer management service. Excluding loss from our quick commerce business, our Alibaba China E-commerce Group EBITA would have been stable year-over-year and will fluctuate quarter-over-quarter due to significant investment in merchant retention and user experience.

Revenue from AIDC grew 6% this quarter. AIDC's adjusted EBITA loss narrowed significantly year-over-year, approaching break-even, driven by a combination of logistics optimization and operating efficiency.

The unit economics of AliExpress' Choice business continued to improve substantially 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 accelerated to grow 40%.

AI-related products continued to lead this momentum. We delivered our 11th consecutive quarter of triple-digit growth in AI revenue.

Its share of external cloud revenue continued to increase, now account for 30%. This quarter's AI revenue is RMB9 billion, and the annual revenue run rate is RMB36 billion or US$5.3 billion.

This is a clear reflection of the scale and acceleration in our AI business. The adjusted EBITA margin remained relatively stable at 9.1%.

All other segment revenue decreased by 21% to RMB65.5 billion, mainly due to the disposal of Suning and Intime businesses, as well as the decrease in revenue from Cainiao, partly offset by the increase in revenue from Freshippo and Amap. All others adjusted EBITA was a loss of RMB21.2 billion, primarily due to the increase in investment in technology businesses, including foundation models and the consumer-facing Qwen app.

As we close this fiscal year, we remain committed to delivering consistent shareholder returns. Our board of directors has approved an annual dividend of US$1.05 per ADS.

We will continue to invest decisively in AI and consumption businesses, where we see significant long-term growth potential and our competitive advantages are compounding. We believe these investments to deliver growth and returns over time, ultimately creating greater value for our shareholders.

Thank you. We will now open for Q&A.

Hi, everyone. You are welcome to ask questions in Chinese or English.

A third-party translator will provide consecutive interpretation. In the case of any discrepancy, our management's statement in the original language will prevail.

大家好，欢迎提问。我们有第三方工作人员提供实时中英文交替传译。如有任何异议，请以管理层原始语言所作的陈述为准。 Operator, please start Q&A session.

Thank you.

Thank you Joe, Eddie, Toby, Fan, and Lydia. Thanks for sharing the very sizable AI, MaaS, and applications ARR scale and the target for the first time.

I just want to ask, how much of that ARR is driven by our in-house models like Qwen versus third-party models? Given the recent token price hikes, what would be the implications to MaaS and also our cloud margins as a result?

Thank you.

感谢Joe、Eddie、Toby、江凡和Lidia，也感谢你们刚才分享在AI MaaS这方面实现的很大的一个规模，还有应用方面的规模。那我想要问一下你刚才讲到这个ARR，其中这个增长多大程度上是我们内部自研模型像千问这样带动的，而多少是第三方模型。然后另外考虑到最近token这个价格是提高了的，那么对MaaS以及云的利润率会有什么影响？谢谢。 好，谢谢您的问题啊。在我们现在的现在我们，因为这个季度我们刚刚公布了一个最新的一个数字，也就是我们的模型及应用模型及应用服务收入，这个收入的主要的业务现在就现在而言，主要的业务构成其实分成两个部分，就是我们的百炼的MaaS的API服务，以及我们的AI原生软件的订阅制的这些这些收入。那么在现在这两部分的收入里面绝大部分都是还是来自于百炼的MaaS的API服务。但同时阿里云的百炼其实又是一个相对开放的一个平台。在我们这个平台上我们hosting自研的模型，也会hosting三方的开源模型，包括三方的闭源模型。那就现在我们的收入规模上来说，绝大部分还是我们的自研模型，包括我们的千问、基模，以及包括我们的语音模型，包括我们的视频模型。

Thank you for that question. This quarter marks the first time that we announced the latest figure for model and application service revenue.

That really comprises mainly two things. On the one hand, it includes revenue from API calls on MaaS on our Bailian platform, and it also includes revenues from our AI software subscriptions.

At present, most of the revenue is coming from the first of those two pieces. This is an open platform, we are providing access both to our proprietary models as well as third-party models, including open-source models and closed models.

For the time being, most of that revenue is coming from our own proprietary models, including Qwen as well as base models, as well as our voice and video generating models.

您说的第二个问题其实也是比较关键的一个问题。因为最近最近这一个季度或最近这几个月来发生了一个非常大的，整个行业发生了一个非常大的改变。就是因为整个的AI在从对话式的chatbot转向agent的运行。agent运行需要帮助客户完成非常复杂的推理任务。那在这个就导致于客户的对于模型的推理的这个需求持续直线的直线上升。那在这个过程当中，由于可以帮助客户完成更复杂的工作任务，所以整个API token的价格也客户的接受度其实虽然价格进行了上调，但是客户的接受度其实还是还是非常高，而且需求也是非常持续的大。而且在这个需求就现在来看，我们实际是我们的供应其实还没有办法完全的满足这些客户的需求，排队的客户还有很多。所以就就现在这个情况下，我们觉得首先MaaS业务它也本身的一个对比IaaS业务来说相对毛利就会天然就会高一些。然后然后还有一些还有几个比较重要的一些点吧。第一个点就是说整个推理的技术技术的这个发展还在持续的发展。在这个所以每个季度我们都会看到在推理技术上的一些优化带来的成果，可以使我们在单服务器单卡的token产能上面产生一些持续的持续的增量效果。同时由于模型的能力也在持续的加强，而且模型的价格在未来的一年一两年内我们看到持续的应该还是会是一个价格提升的一个过程。所以从从这个角度来看，我觉得我们未来这几季度因为MaaS业务的这个飞速增长，会对我们的毛利率产生一些非常非常积极的非常积极的影响。

Your second question was also a really important one, because in the past quarter, over the past few months, we've seen a very large shift in the market where AI is shifting from functioning as a conversational chatbot to providing agentic capabilities. These agents are increasingly capable of solving for very complex problems, meaning that they need to do a lot more inferencing than in the past.

Precisely because these agents can help to solve very complex tasks, customers' acceptance for higher prices—and we have increased per-token prices—is good, and the demand continues to be high and growing. In fact, our ability to supply this demand is not able to keep up with all the growth and demand, and we actually have a lot of customers still waiting to access the service.

Inherently, MaaS will have higher gross margin than IaaS. That's important to know.

I can also add a few important points on top of that. First is that the development of reasoning or inferencing technology still continues to advance.

Every quarter, we're seeing new results in terms of optimization in reasoning, in inferencing, with continuous incremental effects in terms of the token capacity of a single server and a single card. At the same time, as the capabilities of models continue to strengthen and price of the models continues to increase in the next year or two, we see that this should be a process of continued price improvement.

I think from this point of view, the rapid growth in this business over the next few quarters will result in very positive impact on our overall gross profit margin. 谢谢，Eddie.

Hi, good evening management. Thanks for taking my questions and congrats on the very strong progress on the AI.

I have a question regarding the return on invested capital on the AI investment. While our AI investments have driven impressive 40% cloud growth, they have also created significant drag on the group free cash flow as well as our EBITA.

How should investor assess the return on these investments? What's the management framework for balancing the aggressive AI spending versus earning stability?

Thank you.

好，非常感谢管理层接受我的问题，也祝贺你们在AI领域取得的非常好的这个业绩。我的问题呢是关于AI领域我们这个资本投资的回报率这一方面。我们看到这种投资使我们得以实现40%的云业务的增长，这个非常好。但同时呢，对于集团的这个自由现金流以及EBITA带来了一定的这个拖累效果。那么我想知道集团如何评价这个投资的回报率？然后你们采用什么样的管理框架来平衡，就是一方面是AI投入，另一方面是公司的这个营收能力怎么平衡？ 好，Kenneth，谢谢你的问题啊。我想我先来这个回答第一部分，因为我觉得大家可能现在特别是这个季度看到我们的这个自由现金流是一个负数，所以大家可能会比较关心我们是怎么来控我们的这个自由现金流的。我想首先大家可以看得到这样自由现金流的负数最关键的还是我们在过去一年的在AI方面的投入。那因为我们看到了这样一个历史的一个机遇，我们是十分坚定的在这个方面进行这样的一个投入，所以这是最主要造成的这个整体的一个自由现金流为负的这样一个情况。

Thanks, Kenneth, for that question. This is Toby, and I'm going to start by answering that first question, because I think it's important and of interest to everybody.

The question is the reason for the negative free cash flow and how we are managing that. Starting there, the answer is that the negative free cash flow is primarily due to the very significant investments we've been making in AI over the past year.

We've been extremely resolute in making those investments precisely because we've seen the historic opportunity of AI.

往未来再看两年的话，我想我们的这样一个投入还是会继续的十分的坚定。因为这样一个窗口期可能对我们来讲就是几年的时间，所以在投入的角度我们会继续很坚定。同时回来再看从我们经营现金流的角度其实并没有这个有大的一个变化。这里我想谈两个方面啊。第一个方面，从我们消费业务的角度，淘宝天猫作为我们最重要的一个经营现金流的产生的这样一个业务，这个整个经营现金流的产生还是十分稳定的。而未来两年，随着整体的我们闪购的这个相对的这个亏损的大幅的收窄，整体的消费业务会加上我们还有一个AIDC的整体的从一个亏损往盈利的方向走，整体的消费业务的在未来两年来看，整体的经营现金流会是十分的一个正向的一个发展，所以这是第一个我想说的。

We've been very resolute in making those investments over the past year. Looking forward to the next 2 years, we intend to be equally resolute in continuing these investments, again, because we see this as a critical window of opportunity that will be open for that period, for the next couple of years.

Additionally, there's really been no big change in the way that we look at cash flow. The major contributor of operating cash flow for the group is Taobao and Tmall, and that cash flow is very stable.

Looking ahead over the next 2 years, in terms of quick commerce, the losses will narrow very substantially at the same time AIDC will develop from making a loss to being profitable. We see these developments over the next 2 years as being highly positive for our net cash flow.

第二点，另外一个很重要的点是这个我们在云的这样基础设施的投资，刚才那个Eddie也提到了，会让我们的整个的云的收入AI云的收入继续加速，同时整个的毛利率的改善。所有这些会进一步提升我们在云这个板块的经营现金流，回来同样可以这个支撑我们对这个云的基础设施的投入。第三点我也想说，我刚才提到了我们自己的整个的balance sheet还是十分strong的。我们目前的净现金差不多380亿美金，如果我们拿掉这个5年以上到期的债务的话，我们现在净现金大概有差不多590亿美金。所以这样一个十分坚实的这样一个资产负债表，也可以很好的支持我们的对这样一个这个云的基础设施的投入。最后我还想说是，我们还有很强的资本市场的融融资能力，可以通过不同的形式的市场融资去应对战略发展的需要。所以我这里我想先回应一下您刚才提到的关于现金流包括我们怎么样这个准备好更充足的现金流这个问题。然后接下来看看那个Eddie是不是有一些补充。

Another important point to be added is that our ongoing investments in cloud infrastructure will increase the revenues that we can achieve from our AI and cloud offerings. At the same time, we will increase gross margins in those very same offerings.

In those ways, we expect that we can achieve higher net cash flow from our cloud and AI business, and that cash flow can in turn be used to support the development of the relevant infrastructure. An additional point is that we have a very strong balance sheet.

As of March 31st, 2026, we held approximately US$38 billion in net cash, and if you exclude debt with maturities beyond 5 years, our net cash position stands at approximately US$58 billion. That balance sheet strength also gives us confidence to reinvest for growth.

Beyond that, I would also add that we have a very strong capacity for pursuing financing in capital markets, and we have the capability to raise capital from the markets as we need to support our development. I wanted to open with that in response to your question on cash flows, and I'll pause there to see if Eddie has anything to add.

好，您说的关于AI AI方面的这个投资的以及未来的这个ROI这方面的情况，我觉得可以也借此这个机会分享一些我们度一个看法吧。就是从从现在整个AI的业务的发展趋势来看，我觉得AI更像一个制造业，也就是说当我们要获得更多的收入的时候，我们其实要必须要去建立两个核心的工厂。这两个核心工厂的规模会影响着我们未来有多大的一个收入规模。这两个核心工厂，一个我们可以称为叫做AI的训练工厂，一个叫做AI的推理工厂。那这两个工厂背后其实是一个AI的数据中心的建设，而数据中心的这个建设我相信一定会消耗比较大的集团的自由现金流。但是这些刚性的数据中心的这个这些基础设施的建设，我们在回报的路径上是非常清晰的，就是当我们这些数据中心我们在to B的to to B的这个商业化这个路径上是非常清晰的。无论是云的IaaS的这种商业化的服务，还是通过我们的MaaS平台，以及通过我们的AI原生软件去创造更多的模型之上的这这样的一个营收，我们几乎现在在我们的服务器内几乎没有一张卡是空的。也就是现在我觉得在未来3到5年内的这个需求的情况下，我们大量的投入的AI数据中心的建设，这个投资回报是非常确定的。

Thank you. You asked about our investments in AI and the ROI on those investments going forward.

On top of what Toby's already said, I'd like to add a few notes regarding where we're heading. I think the best analogy is manufacturing.

In other words, in order to be able to manufacture more and sell more in the future and achieve more revenue, what we're doing today is investing capital to build two factories, if you like. The first we can call the AI training factory, the second we can call the inferencing factory.

Both of those factories need to be powered by our AI data centers, and that requires the investment of cash flow today. However, looking to the future, the pathway to achieving solid return on investment in those factories, in those areas, is very clear on the to-B side, by monetizing our to-B offerings, including our cloud-based IaaS as well as MaaS, of course, and our AI-native apps.

I can tell you that today there isn't a single card on our servers that is idle. We see the ROI on this investment in the next 3- to 5-year period as being extremely clear.

Next question, please.

Hi, good evening. Thanks management for taking my question.

My question is on quick commerce. We have talked about the improvement in UE in the prepared remarks.

I just want to get some more color about the drivers behind in terms of AOV, subsidies ratio, fulfillment ratio, etc. On top of that, I remember last time we talked about the outlook for quick commerce over the next couple of years.

Is there any update or changes in terms of how we think about the landscape or the UE in the next few years? Thank you.

好，感谢管理层。我的问题是关于即时零售这一方面。那么刚才在准备好的发言当中，你们已经介绍了UE得到了显著的改善。我想了解一下背后的驱动因素，包括这个是笔单价还是补贴比率还是履约等等各方面的一个贡献。另外的话，上一季度的业绩发布会上，你们介绍了未来两年的这样一个即时零售的展望，那么想知道从那个时候到现在，你们这种展望有什么样新的变化？你们看待市场格局的方式有什么样的变化，包括这个UE方面和补贴等方面。 好，我来回答这个问题。对，首先经过一年的投入，我们看到即时零售业务飞速发展，我们的市场份额取得了根本性的变化。那么对比这个3月份季度，去年3月份季度同期，就大规模的投入之前，今年我们的订单规模跟市场份额都取得了显著的提升。那么1到3月份整体订单规模是去年同期的2.7倍，那么其中非餐饮零售部分是去年的3倍。那么4月份以来，我们在保持订单规模的同时，我们继续通过物流效率的提升，订单结构的优化，尤其是这个AOV的这个进一步上涨，那么它推动了我们的UE显著的优化。那么我们有信心在新财年结束前实现UE转正。

Thank you. First, as a result of our strong investments in quick commerce, we've achieved very rapid growth in quick commerce over the past year, marking a very fundamental shift in our market position.

Compared to the same quarter last year, which was, of course, prior to all this large-scale investment, both our order volume and our market share have increased significantly. Overall order volume was 2.7 times that of the same quarter last year, with non-food orders at 3 times.

From April onwards, while maintaining order volume, we've continued to drive substantial improvement in UE through enhanced fulfillment logistics efficiency as well as order mix optimization. We are confident that UE will turn positive by the end of fiscal year 2027.

在这个UE优化的同时，我们后续还是会持续通过创新提升用户商家体验，保持我们在即时零售领域的长期竞争力。所以我们有信心在新的规模跟市场份额水这个水位下，未来实现即时零售的整体盈利。那么本季度我们也看到闪购对实物电商的促进，尤其是在新客获取，促进用户活跃度，满足用户多元化消费场景，拉动成交跟商业化，以及物流基建等方面，那么推动淘天整体板块发展。我们继续看到闪购相关品类的带动明显，特别是食品生鲜等品类，那么也基于推动像盒马、猫超等即时零售相关业务的发展。那么我们的实物电商这个季度无论在成交跟CMR方面，这个季度都取得了比较好的一个增长的势头，那么闪购跟即时零售我们也看到在里面起到了非常确定性的正面拉动作用。

While optimizing UE, we will continue to innovate to improve the experience for both consumers and merchants, thereby sustaining our long-term competitiveness in quick commerce. We're confident that our quick commerce business will achieve overall profitability in the future at new scale and market share.

This quarter, quick commerce continued to generate synergies with our conventional e-commerce business as demonstrated in driving customer acquisition, enhancing user engagement, fulfilling diverse consumer demands, increasing transactions, improving monetization, and supporting logistics infrastructure. In terms of categories, quick commerce continued to drive sales in various categories, especially food and fresh produce and healthcare, and contributed to Freshippo's and Tmall Supermarket's accelerated growth.

In our conventional e-commerce business, we saw GMV and CMR demonstrate strong growth momentum in the March quarter, and quick commerce played a vital role in driving that performance.

Next question, please.

哎，好的，晚上好管理层，非常感谢接受我的提问。我想追问一下就是之前管在那个在opening remark管理层说到的那个MaaS MaaS的这个业务。我就想了解一下就是管理层怎么看在MaaS领域阿里巴巴和中国其他头部的AI平台公司以及AI创业公司的优势是什么？我们在美国看到这个AI agent尤其是AI coding已经是AI商业化增速最快的领域，所以想问一下在中国您估计AI AI coding大概什么时候什么时候会看到类似的增增速？另外就是中国企业好像一直不愿意为SaaS产品付费，您觉得这个会不会让中国这个AI coding产品的商业化前景没有美国同行那么有潜力？谢谢。

Good evening, management, for taking my question. I have a follow-up based on your opening remarks concerning MaaS.

I'm wondering, first of all, what are the major advantages that Alibaba has when compared to the other major AI platforms in China, as well as Chinese AI startups? In the United States, we see that AI agents and especially coding are the fastest growth track in AI.

I'm wondering when you think we'll see that kind of growth in China in terms of AI coding? We also know that Chinese customers are less willing than US customers to pay for SaaS.

Do you think that means that the future commercialization of Chinese AI coding products might have less potential than we see with the US counterparts?

好，谢谢您的问题啊。就是您这个问题也问问得很好。就是在阿里云的百炼这个平台上，我们其实是是定位是一个开放型的一个AI推理平台。那在这个推理平台上，现在主要的一个营收确实主要是由我们自研的模型产生的。那我觉得对比一下这些我们的AI创业公司而言，就想我们在模型上面的投入和广度来说，其实是我们会远远超过这些模型创业公司。当然这些模型创业公司在专注于某一个模型或者某一个领域来说，他们也有非常强的技术以及很快的很快的商业商业敏锐度，所以他们的进展也是很快。所以从这个角度上来说，我们如果单纯在看MaaS领域的话，我觉得这些创业公司某种程度上也是也是阿里云的也是阿里云的合作伙伴。所以那但是对阿里巴巴而言，我们会会更强调我们在各个各种不同领域的模型要做更广度的研发。也就是我们会做像基于coding能力为优先的千问基座模型，像我们的视频模型，无论是万相还是我们的Happy Horse，包括更面向未来的世界模型，包括我们的语音模型。我们相信未来在很多的业务场景上面，用户会需要多种不同的模型能力综合来满足他的一些业务需求。所以这个是我觉得我们与这些头部的这些AI创业公司相比的一个区别。同时和他们其实某种程度上也是阿里云百炼的合作伙伴。

Thank you. The way we define our MaaS platform, Bailian Model Studio, is as an open AI inferencing platform.

Certainly, at present, the majority of Bailian's revenue is driven by our own proprietary models. In contrast to the AI startups in China, I think that we are investing at a much higher scale and across a much broader range of different model types.

In contrast, those startups may tend to focus on a very narrow particular vertical segment, and they can move rapidly ahead with that kind of focus. Strictly in terms of our MaaS business, I think those AI startups really are partners rather than competitors.

At Alibaba, we particularly place emphasis on our model capabilities and developing them across all different spaces and all verticals to serve a very broad and diverse set of needs, including our coding model capabilities, including image-based models, both Wanxiang and Happy Horse, as well as these new world models, and of course voice models as well. We aim to provide all different kinds of models to meet all different kinds of needs.

This is different, I think, from those startups, and at the same time those startups are our partners.

好，您说的关于AI coding这个问题也很好。就是其实您说何时能迎来类似的增速，其实我觉得我们的判断是在中国就现在已经迎来了类似的速度。也就是从我们自己在百炼平台上看到趋势，以及行业内其他像这些和我们合作关系比较好的这些AI创业公司那边看到，其实从去年11、12月份开始到现在，到今年的5月份，这一段时间的大量的公司的API需求的这个增长，几乎大部分都是有AI coding的能力的提升来带来的。而AI coding它不是简单的只是说我们替代了软件工程师的工作。由于AI模型的能力的提升，以及AI coding和整个的agent的运行环境的这些结合，也就是所谓的哈尼斯工程啊这些数据领域的这些结合，我们看到由AI coding去驱动的复杂任务agent已经可以几乎可以在各个数字化的工作任务当中去完成任务。那所以这一无论美国还是中国，这一波AI需求带来的带来的增速，主要是靠的是AI coding能力的提升。因为AI coding能力的提升，结合电脑或者数字化的这些工具场景，理论上是可以解决几乎所有数字化工作的未来未来的这些复杂任务。所以这个是一个整个的我们觉得未来2到3年内一个非常重要的一个一个增长

一个增长趋势吧。然后我再，OK。 The other part of your question was about when we can see the similar kind of growth in China as is being witnessed in the US around AI coding.

I would say in terms of what we're seeing, based on the trends that we ourselves see on Bailian as well as the experience of some of these AI startups in China who work closely with us, I would say China is already there. Most of the growth that we're seeing in utilization from say November or December of last year through to May of this year has been driven by capability upgrades in terms of coding.

These models are not just able to replace software engineers. Basically, they're able to solve a wide array of very complex tasks beyond just coding per se in any kind of digitalized productivity scenario.

We've seen AI coding capabilities improve significantly in both the US and in China, and these capabilities are capable of supporting much more than just coding per se. It can address a whole wide range of very complex tasks in the workplace in so far as those tasks can be digitalized.

Looking ahead to the next 2 to 3 years, we see this is a very, very important growth driver.

好，其实我们看到您说的关于说中国长期企业存在SaaS付费意愿较低的问题，那我觉得在现在这个大模型的这个时代，有一个非常大的区别。就是现在的AI的模型的能力越来越强，当它可以帮助帮助这些用户真正的完成工作当中的复杂任务的时候，我们看到无论是美国的企业还是中国的企业，对于为它帮助他完成工作任务，帮助会为这个智能能力买单。这个这个需求在美国和中国都是一样的，而且都会非常强。理论上来说，只要帮助他完成了这个工作任务，在他的企业内，这部分工作任务创造的价值大于token的成本，某种程度上，这个对于API的token的需求就会是无限的。所以从这个角度上来说，我们也看到底层的对于AI的这个需求的增长还是会非常长期确定性。那从我们自己看到的，也可以分享一下我们自己看到的一些数据。那我们在我们的百炼平台上看到的整体的增速非常 非常之快，对比去年11、12月份的数据，那我们今年5、6月份的数据我们应该会增长增长10倍以上。而且就是在最近，我们其实我们其实的ARR应该已经突破了80亿。那也就是是说在这个季度我们突破100亿的ARR是一个非常确定性的事情。所以我们看到无论是中国企业还是美国企业，对于愿意为智能能力买单，愿意为通过这个智能能力调用这个智能能力帮助他完成真实的工作任务，这个这个事情买单是一个非常普适性的一一个选择。

On your other comment, we have also taken note of the lower willingness in China to pay for SaaS. However, I think that is poised to change as the models become increasingly powerful and are able to truly solve for very complex tasks, very complex problems.

As they are providing truly valuable intelligence, I think we can expect to see the same demand for that kind of service in China as in the US. In a certain sense, when the value provided by tokens exceeds the cost of those tokens, the demand for tokens will become infinite in a sense.

We see growth in AI demand as a long-term certainty. I can also share some numbers with you in terms of the growth that we're seeing on our own Bailian platform from November, December last year through to May of this year.

It's higher than a 10 times growth. In terms of our ARR, it's already over 8 billion, and I think this quarter, it's highly certain that we can achieve ARR of over 10 billion.

Next question, please.

Good evening management, and thank you very much for taking my question. Just wanted to stay on the topics of the global comparisons.

If you look at globally, the overseas peers seems to have captured the most immediate ROIs in enterprise agentic workflows, whereas for the consumer and the monetization would remain a bit lagged. Going forward, considering that Alibaba is investing kind of in multi-fronts for infrastructure, models, cloud, and Qwen app, how do we evaluate the strategic priority and the resources allocation between 2B and 2C initiatives?

If going forward, enterprise side continues to gain more traction, would we consider gradually shift more resources away from Qwen app to cloud and MaaS? Thank you.

感谢管理层接受我的提问。我还是想接着刚才我们讲的这样一个国际间的对比来提问。因为展望全球呢，我们似乎海外的一些同行，他们是在企业的这些智能体工作流方面是更好地把握到了就是眼前的这个机会。但是对他们来说，消费端的这个变现还是相对滞后的。那么展望未来，虽然我们阿里巴巴在投资多种这个基础设施、多种模型、云、千问APP等等，那么我们就是阿里巴巴对于2C、2B这两边的战略优先级是怎么考虑的，以及资源分配的这个优先级如何？那么如果未来的话，企业端发展得更加好的话，我们会不会把更多的资源从2C端转移到这个比如MaaS这一方面？ 对，非常感谢您的这个问题啊。就是您这个问题其实问得也很好，但是从我们自己的从AI本本身本质上的这个原理来说，其实它更更是一个计算范式的革命。那在计算这个范式的革命，其实最后其实还是要能够帮助用户去完成任务，或者帮助用户去去更好的去解决问题。那么从这个角度上来说，我觉得2B和2C本质上是一样的。但是就现在来说最我们看到无论是全球还是在中国，最能够接受客户付费意愿的确实在这个2B的领域。因为这和它的ROI更容易计算，也就是这些企业的付费意愿更强，所以我们的大部分的推理资源其实也是投入在这个2B的这个这个商业化领域。但是另外一个层面，其实AI无非最终就是要作为人的一个助理。那做作为人的助理而言，有工作的助理，也有个人的助理，也有学习的助理。从某种程度上来说，其实它要本质要解决的问题是一样的，就是用AI怎么样帮助人去解决任务。而这个任务可能有2B、2C或者学习、工作、生活。那么我们相信2C的2C的业务可能它的就现在的客户的接受程度和付费意愿来说，它需要一定的投资周期。但是我们相信2C的AI助理一样会随着技术的技术的进展，以及客户的接受程度，或者在帮助他完成更多的任务之后，慢慢形成一个它的商业模式。这个商业模式我们其实在海外也已经看到了，是吧？包括我们在国内其实也会在我觉得在未来1到2年之内，我们也会看到在2C的AI助理方面也有很多的商业化的这个这个进展会产生。

Thanks for that question. It's a good question.

I think fundamentally from the perspective of AI development, it's really all about a paradigm shift in computing, and it's about leveraging this new technology to help users, whoever they are, to complete tasks and solve problems, and that applies equally on the to-C side as well as on the to-B side. Now, certainly at present, we see higher willingness to pay on the to-B side because it's easier to show a business case with compelling ROI for a business.

At present, most of our infrastructure resources are therefore channeled to the to-B side. At the end of the day, AI ultimately is an invention that's there to be a helper, an assistant to humans, to help humans with a whole range of things, spanning their own daily life, their studies, and at their work.

What AI does really is the same across all of those scenarios: it's about solving problems. That's true for to-B and for to-C.

Certainly, there's less willingness to pay today for to-C, but we're already seeing a business model where consumers are paying for individual usage in the US, and I'm confident that the same will come to be the case in China, especially as the technology improves, as it's better able to help them solve real problems in their daily lives. We think that ultimately, this will be the same business model internationally, and I think we'll probably get there in China in the next say 1 to 2 years.

Next question, please.

感谢管理层接受我的提问。我是想follow up一下前面提到的关于我们云业务的未来发展。除了加速之外，能不能请管理层再跟我们讲一下在EBITA margin上的趋势，特别是在未来几个季度随着我们的加速，我们会不会看到和国外类似的这个margin扩张的这么一个趋势？谢谢。

Thanks, management. I have a follow-up question also on the future growth of the cloud business, and I'd just like to understand what your view is on EBITA margins in the cloud business over the next few quarters.

Do you think as this business accelerates, we can expect to see similar margins as we see in your international peers?

好，非常感谢您的一个问题。就是就现在AI的技术以及对于AI技术对各行业的渗透来说，我们现在觉得还是处于一个早期的阶段。但是就我们的阿里云以及我们的AI业务的目标而言，主要还是要做增长，以及用户数，以及用户的token消耗和这个和这个市场份额，以绝对领先的我们希望还是说能够超过行业平均增速的平平均增长速度来进一步快快速地获取生产市场份额，来夯实我们的绝对的市场领先地位。利润率是我们的第二目标。但是由于现在现在有几个几个行业的一个非常明确的一个一个行业特点，也就是第一，我们觉得判断未来3到5年内其实AI的行业的这个需求还是很难，因为有有很大的物理瓶颈的限制。无论是AI数据中心的建设的周期，以及行业内芯片或者memory各方面的各方面的生产周期物理物理扩产物理物理整个的产能的这个增长都觉得我们觉得还是3到5年内很难能够支撑AI的需求的这个增长。所以这个角度上来说，阿里云历史上因为有很强大的一个客户规模效应和资产我们历史上的IT CapEx的规模效应。在这个规模效应下，由于现在的市场供需的紧张，现在实际上我们新的一台服务器，某种程度上相同的服务器在今年去部署上线的成本是在我们两年前部署上线的1倍以上，也就是这个成本增长了100%以上。那这样的一个新服务器的重置成本对于我们的云的客户，老客户的需求以及新客户的需求都有一个定价的牵引作用。这个定价牵引作用我们相信对于未来一个比较长周期内云的各项服务的一个一个资产定价会是有个比较正向的提升的一个提升的一个效果吧。那还有第二个就是我们还看到一个就是我们阿里云的MaaS业务的快速增长。因为MaaS业务本身就是一个收入相当于毛利对比我们传统的IaaS，就是整个IT资产类的业务相对来说是一个高毛利的业务。同时由于我们刚才已经说到了，由于整个推理技术的优化，单卡的产能还会持续的提升，所以我们现在看到的一个情况，如果我们一个同样的一个服务器交给我们的百炼平台所创造的营收和毛利水平是高于我们传统的云计算简单的算力服务的。所以这个业务的收入的占比提升，我们也会相信能够提升我们未来的毛利水平。那还有一个就是我们的全栈技术优势，平头哥的我们的AI芯片的一个自研，以及平头哥AI芯片的未来的规模放量，有助于我们在整体来说提供一个可能在中国最好的一个性价比水平的一个推理平台。那这个推理平台我们相信也能够创造出更好的一个毛利更好一个毛利率，和我们的模型进行一个比较强的协同。所以因为这几个特殊因为这几个客观的一个因素存在，所以我们判断未来这个1到2年阿里云的毛利率会有一个比较显著的一个提升，那最也会在最近的一两个季度内看到这些变化。

I think when it comes to the deep penetration of AI technology across all different industries, we're still really in the early days of that long process. Our objective is clear.

Our objective is to achieve growth, to drive growth, to drive growth in token consumption, and to acquire larger market share. We aim to maintain growth that is faster than the market average in order to gain larger market share and firmly cement our absolute market leadership position.

Those are the primary objectives, and margin is still secondary. The other thing to be pointed out is that for the next 3 or even 5 years to come, there are physical constraints on production, production capacity for chips, for memory, for the physical things that are needed to support all this growth in demand.

An advantage that we have at Alibaba Cloud is the scale of our customer base, as well as the scale effect from all of the CapEx that we've put in over these years. In this environment of market scarcity, we're already seeing that the cost for us to deploy one new server this year is double what that same server would have cost a year ago, so that the cost inflation has been over 100%.

Given that higher replacement cost effect, we have a certain pricing power with respect to new customers, and also old customers. I think in the long term, the asset pricing effect will be positive for our revenues going forward.

Secondly, we see very rapid growth in MaaS, as we reported to you, and inherently, as we said, MaaS represents a much higher level of gross margin than IaaS or traditional types of IT operations. As demand for inference continues to grow exponentially, we expect this will be very positive for gross margin.

Due to the optimization of our reasoning technology, the output capacity, the productivity of a single card will continue to rise. An additional factor is as we continue to scale up the deployment of T-Head, the T-Head chips represent the highest value for money compute power on the platform, and that also will contribute to a better gross margin.

For several objective reasons that I've outlined, I think overall, in the next 2 to 3 years, we can expect to see significantly higher gross margin for Alibaba Cloud, and we can expect to start to see that in the next 1 to 2 quarters.

Operator, let's take the last question. Thank you.

Hi, for the opportunity. I have a question regarding CapEx.

What kind of level of CapEx investment is required in order to satisfy the demand from both MaaS and also the long-term cloud revenue? Also management mentioned about the T-Head opportunity.

What is the current penetration of T-Head being deployed on Ali Cloud? As this penetration increase of margin uplift we should expect from our in-house chip?

Thank you.

非常感谢管理层接受我的问题。我第一个问题是关于我们的资本开支方面，就是为了实现我们这个MaaS以及云业务方面的收入目标，我们需要维持什么样的一个资本开支的水平？另外一个问题刚才讲到平头哥，想知道现在在我们的系统中平头哥芯片的渗透率已经达到百分之多少？然后随着它的进一步渗透，具体可以给我们的毛利带来多大的提升？ 好，谢谢您的问题啊。就是你的第一个问题也比较重要，就是其实我们在上个季度的我们的讲稿中也已经提到了，就是我们其实对未来5年的一个营收的目标有一个非常高的营收目标。那在这个目标情况下，其实我们对比2022年2022年和2023年的，也就是AI大模型还没爆发的这个年代的就是阿里云的外部营收，那个收入目标大概是是一个增长10倍的收入目标。那粗浅的计算可以可以理解为，至少是当时阿里巴巴阿里云所持有的数据数据机房资产的10倍以上，才能够支撑我们的长期的业务目标。所以某种程度上我们未来要建的数据中心的规模，基本上是一个对比2022年是一个10倍以上的一个增长。这是我们所有投入的CapEx也好，包括我们现在还有不少方式不少用OpEx方式去获取的这些算力来说，这是一个我们的总的目标。所以我们的对比前面三年，前面所说的3年3800亿来说，我们面向未来的这个5年目标来说，其实我们相信我们为了获取这些算力中心所获取的这个投入的投入的资金会远远超过我们原来的原来的3800亿。当然现在这个情况因为已经比较复杂，不见得会所有的算力中心都会由我们自建的CapEx去获取，比如说我们会用OpEx租赁的方式去获取，包括我们随着我们平头哥芯片的产能的扩大，我们也可能会通过去销售平头哥AI服务器的方式去销售给各个算力中心或者说数据中心的服务商，同时和这些数据中心的服务商共同去建设。所以未来会有多种方式去支撑我们的数据中心的容量的一个扩张。但是最基本的，最基本的这个数据需求数据中心的需求来说，我们是应该是对标大模型没有爆发前的2022年的一个10倍的一个一个数据中心规模。

Thanks. The first question is quite an important one, and actually, in our prepared remarks delivered at the last quarter's earnings call, we set out a forecast for the coming 5 years for revenues, and it was a very high target.

Essentially, I think if you compare where things were in the year 2022 before this explosive growth in AI models and what we expect to need in 2033, I think we're talking about a 10x increase. We need 10 times the amount of data center infrastructure compared to what we had in 2022.

There are different ways to get that compute capacity. Some of it can be CapEx, part of it can also be OpEx.

We're actually now acquiring quite a bit of computing capacity using OpEx. The situation is complex today for reasons we've discussed.

I think it's likely, given that kind of investment, that we will overshoot the original CapEx figure that we had stated of 38 380 billion. At the same time, we can acquire some compute through OpEx, and as we have our own proprietary T-Head chips, we can actually also sell AI servers leveraging those chips to other computing centers, or we can co-build computing centers with others.

There are different ways that we can get to where we need to get. The bottom line is that the demand for compute infrastructure is going to be 10x of 2022's.

好，我们我们的自研芯片其实在阿里云的部署，这个比例现在还并不是是属于一个小部分的范畴。当然我这里也分享一下，就平头哥的芯片我们除了有自己的GPU之外，我们的CPU包括我们的存储网络芯片都是一个全栈自研的。所以未来我们有机会用我们一个全栈，从我们的GPU、CPU、存储到网络芯片上去进行一个全栈的一个自研。那现在这个比例还比较低，因为有一些各方面客观的原因，比如说在中国国内的这个整个半导体的产能产能的量还是比较少。当然这几年中国国内的半导体的产能也在持续的扩展扩展当中，所以我们觉得随着这个平头哥我们自研全套芯片的渗透率的提升，对我们毛利率的提升影响会非常大。但这个大现在就是说有一些情况在互相的影响，比如说由于中国的国产的国产半导体的整个的制程相对来说比国外的相对来说还是相对差一点，那么总体同样的一个芯片，无论是能耗啊还是说还是效率上来说都会有一些对比国外先进的芯片来说还还会有些有些差距。但是由于我们可以看到国外主流的AI芯片的毛利率非常之高，是吧？接近基本上接近在60%到80%的毛利率。那么无论就算是国内芯片的总体的性能或者说功耗会有一定的提升，但是在那个60%到对比国外先进芯片60%到80%的毛利率的中间，其实有个非常大的我们觉得有一个性价比提升的空间。但这个性价比提升空间最终对我们的整体毛利的提升的影响，需要看看后面我们的产能的扩张，以及整体的 产能扩张之后对我们的现有的存量有多少 有一个替代的一个比例。 Yeah.

In terms of our T-Head proprietary chips, they can be deployed across a very large part of our AI infrastructure, and not just compute chips, but we have a full stack, including memory. At present, the ratio is still relatively low, and that's because of constraints around production capacity in China, which has been limited.

Of course, it's been growing. As we deploy more and more of our own proprietary T-Head chips, the new chips will certainly contribute very, very significantly to gross margin expansion.

It's true to say that domestically produced semiconductors in China lag behind the leading overseas ones in terms of energy efficiency and production efficiency. However, if you look at global leading AI chip vendors today, their gross margins are as high as 60% or even 80%.

As we ramp up domestic chip production and the capabilities improve, I think there's a lot of room for our chips to be providing very high value for money as compared to that 60% to 80% gross margin that other vendors are taking.

Thank you. This brings us to the end of today's earnings call.

We appreciate your time and participation, and we look forward to speaking with you soon.