Alibaba Group Holding Limited (BABA) Q4 2026 Earnings Report, Transcript and Summary

Good day, ladies and gentlemen. Thank you for standing by. Welcome to Alibaba Group's March Quarter and Full Fiscal Year 2026 Results Conference Call. [Operator Instructions] After management's prepared remarks, there will be a Q&A session. I would now like to turn the call over to Lydia Lu, Head of Investor Relations of Alibaba. Please go ahead.

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. And with that, let me turn the call over to Eddie.

[Interpreted] Welcome to Alibaba Group's Fiscal Year 2026 Fourth Quarter Earnings Call. Over the past quarter, Alibaba's high-intensity investment in our 2 strategic priorities of AI + 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 3 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 4 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 RMB 35.8 billion, 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 1 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 RMB 10 billion in the June quarter and RMB 30 billion 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 MaaS 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 have 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 Q1 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, Qwen app fully integrated Taobao and Tmall's commerce service capabilities on May 7. And 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 scale. In summary, the return on our investments in AI + Cloud and consumption are increasingly clear. AI + 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 in a pivotal juncture where our technology investments are beginning to pay off commercially. We'll maintain our strategic results 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 talk you through our financial results. Thank you.

Thank you, Eddie. Our strategic priorities remain laser focused on AI + Cloud and consumption businesses. Multiple growth catalysts, including technological advancement and business innovation are aligning to create strong tailwinds. On AI + Cloud, our full stack capability span models, cloud infrastructure and applications. With established leadership in every layer, the strong growth of our AI + Cloud businesses and a 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 a consolidated basis, total revenue was RMB 243.4 billion. Excluding revenue from Sun Art 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 in the cloud business and enhanced operating efficiencies across various businesses. Our GAAP net income was RMB 23.5 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 Sun Art and Intime in the same quarter last year, partly offset by the decrease in adjusted EBITA. Operating cash flow was an inflow of RMB 9.4 billion. Free cash flow was an outflow of RMB 17.3 billion. We are reinvesting our operating cash flow to enhance our competitive advantage in AI. As of March 31, 2026, we held approximately USD 38 billion in net cash. Excluding debt with maturities beyond 5 years, our net cash position stands at approximately USD 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 RMB 122 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 RMB 20 billion. The quick commerce business further improved the UE and increased the AOV quarter-over-quarter, primarily driven by order mix optimization. Alibaba China E-commerce Group adjusted EBITA was RMB 24 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 breakeven, driven by a combination of logistics optimization and operating efficiency. The unit economics of AliExpress' Choice business continue to improve substantially on a sequential basis. Next, let's look at the business update 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 continue to increase now account for 30%. This quarter's AI revenue is RMB 9 billion and the annual revenue run rate is RMB 36 billion or USD 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 others segment revenue decreased by 21% to RMB 65.5 billion, mainly due to the disposal of Sun Art and Intime businesses as well as the decrease in revenue from Cainiao, partially offset by the increase in revenue from Freshippo and Amap. All others adjusted EBITA was a loss of RMB 21.2 billion, primarily due to the increased 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 USD 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'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. [Foreign Language] Operator, please start the Q&A session. Thank you.

[Operator Instructions] Your first question comes from Ronald Keung with Goldman Sachs.

Thanks for sharing the very sizable AI MaaS and applications ARR scale and the target for the first time. So I just want to ask, how much of that ARR is driven by our in-house models like Qwen versus third-party models? And given the recent token price hikes, what would be the implications to MaaS and also our Cloud margins as a result?

[Foreign Language] [Interpreted] 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 2 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 2 pieces, but this is an open platform. So we are providing access both to our proprietary models as well as third-party models, including open source models and closed models. But for the time being, most of that revenue is coming from our own proprietary models, including Qwen as well as Tmall as well as our voice and video generating models. [Foreign Language] 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. So 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. And 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. 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. And 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. So 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 2, we see that this should be a process of continued price improvement. So I think from this point of view, the rapid growth in this business over the next few quarters will result in a very positive impact on our overall gross profit margin.

Your next question comes from Kenneth Fong with UBS.

Congrats on the very strong progress on the AI. I have a question regarding the return on invested capital on the AI investment. So 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. So how do investors assess the return on this investment? And what is the management's framework for balancing the aggressive AI spending versus earnings stability?

[Foreign Language] [Interpreted] 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. So 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. And we've been extremely resolute in making those investments precisely because we've seen the historic opportunity of AI. [Foreign Language] [Interpreted] So we've been very resolute in making those investments over the past year. And looking forward to the next 2 years, we intend to be equally resolute in continuing these investments, again, because we see this is 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. First of all, the major contributor of operating cash flow for the group is Taobao and Tmall and that cash flow is very stable. And 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. So we see these developments over the next 2 years as being highly positive for our net cash flow. [Foreign Language] [Interpreted] 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. So 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 31, 2026, we held approximately USD 38 billion in net cash. And if you exclude debt with maturities beyond 5 years, our net cash position stands at approximately USD 58 billion. So that balance sheet strength also gives us confidence to reinvest for growth. And 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. So 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.

[Foreign Language] [Interpreted] Thank you. You asked about our investments in AI and the ROI on those investments going forward. So on top of what Toby has 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 2 factories, if you like. The first we can call the AI training factory. The second, we can call the inferencing factory. And 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 a solid return on investment in those factories, in those areas, is very clear. On the 2B side by monetizing our 2B offerings, including our cloud-based IaaS as well as MaaS, of course, and our AI-native apps. And I can tell you that today, there isn't a single card on our service that is idle. So we see the ROI on this investment in the next 3- to 5-year period as being extremely clear.

Your next question comes from Thomas Chong with Jefferies.

My question is on quick commerce. I've talked about the improvement in UE in the prepared remarks. I just wanted to get some more color about the drivers behind in terms of AOV, subsidies ratio, fulfillment ratio, et cetera. And 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 3 years?

[Foreign Language] [Interpreted] Thank you. Well, 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 2.7x that of the same quarter last year with non-food orders at 3x. 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. So we are confident that UE will turn positive by the end of fiscal year '27. [Foreign Language] [Interpreted] 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. So 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.

Your next question comes from Jialong Shi with Nomura.

[Foreign Language] [Interpreted] 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 start-ups? 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 U.S. customers to pay for SaaS. So do you think that will -- that means that the future commercialization of Chinese AI coding products might have less potential than we see with the U.S. counterparts?

[Foreign Language] [Interpreted] Thank you. Well, 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. But in contrast to the AI start-ups 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 start-ups may tend to focus on a very narrow particular vertical segment and they can move rapidly ahead with that kind of focus. And strictly in terms of our MaaS business, I think those AI start-ups really are partners rather than competitors. But in 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, so both on Wanxiang and HappyHorse as well as these new world models and, of course, voice models as well. So we aim to provide all different kinds of models to meet all different kinds of needs. And this is different, I think, from those start-ups. And at the same time, those start-ups are our partners. [Foreign Language] [Interpreted] Okay. 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 U.S. around AI coding. And 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 start-ups 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. And these models are not 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. So we've seen AI coding capabilities improve significantly in both the U.S. and in China, and these capabilities are capable of supporting much more than just a 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. So looking ahead to the next 2 to 3 years, we see this as a very, very important growth driver. [Foreign Language] [Interpreted] 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 U.S. 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. So we see growth in AI demand as a long-term certainty. And 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 10x growth. In terms of our ARR, it's already over RMB 8 billion. And I think this quarter, it's highly certain that we can achieve ARR of over RMB 10 billion.

Your next question comes from Ellie Jiang with Macquarie.

Just wanted to stay on the topic of that global comparisons. So if you look at it globally, the overseas peers seems to have captured the most immediate ROIs in enterprise agentic workflows, whereas for the consumer and the monetization which remained a bit lagged. So 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 resources allocation between 2B and 2C initiatives? If going forward enterprise side continues to gain more traction, will we consider gradually shifting more resources away from Qwen app to Cloud and MaaS?

[Foreign Language] [Interpreted] Thanks for that question. And it's a good question. But 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 2C side as well as on the 2B side. Now certainly, at present, we see higher willingness to pay on the 2B side because it's easier to show a business case with compelling ROI for a business. And at present, most of our infrastructure resources are therefore channeled to the 2B side. But at the end of the day, AI ultimately is an invention that's there to be a helper and assistant to humans, to help humans with a whole range of things spanning their own daily life, their studies and their work. And what AI does really is the same across all of those scenarios. It's about solving problems. And that's true for 2B and for 2C. So certainly, there's less willingness to pay today for 2C, but we're already seeing a business model where consumers are paying for individual usage in the U.S. 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. So 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.

Our next question comes from Joyce Ju with Bank of America.

[Foreign Language] [Interpreted] 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?

[Foreign Language] [Interpreted] 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. But 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. So 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 in 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. But 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 the cost inflation has been over 100%. So given that higher replacement cost effect, we have a certain pricing power with respect to new customers and also old customers. So 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've said, MaaS represents a much higher level of gross margin than IaaS or traditional types of IT operations. So as demand for inference continues to grow exponentially, we expect this will be very positive for gross margin. And 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 cloud platform, and that also will contribute to a better gross margin. But for several objective reasons that I've outlined, I think, overall in the next 2 to 3 years, we can expect to see a significantly higher gross margin for Alibaba Cloud, and we can expect to start to see that in the next 1 to 2 quarters.

Your last question comes from Gary Yu with Morgan Stanley.

I have a question regarding CapEx. So 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? And also management mentioned about T-Head opportunity. What is the current penetration of T-Head being deployed on AliCloud? And as this penetration increase margin uplift we should expect from our in-house chip?

[Foreign Language] [Interpreted] Thanks. So 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 target. But 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. So we need 10x the amount of data center infrastructure compared to what we had in 2022. But there are different ways to get that compute capacity. Some of it can be CapEx. Part of it can also be OpEx. And we're actually now acquiring quite a bit of computing capacity using OpEx. The situation is complex today for reasons we've discussed. But I think it's likely, given that kind of investment, that we will overshoot the original CapEx figure that we had stated of RMB 380 billion. But 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. So there are different ways that we can get to where we need to get. But the bottom line is that the demand for compute infrastructure is going to be 10x of 2022. [Foreign Language] [Interpreted] Yes. So 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. But 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. But 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 globally leading AI chip vendors today, their gross margins are as high as 60% or even 80%. So 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 than 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.

Thank you. You now may disconnect your lines. [Portions of this transcript that are marked [Interpreted] were spoken by an interpreter present on the live call.]