Q2 2026 Alibaba Group Holding Ltd Earnings Call

August 20, 2026

Operator: Good day, ladies and gentlemen. Thank you for standing by. Welcome to Alibaba Group's June quarter 2026 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.

Speaker #1: 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 at Alibaba Group.

Speaker #1: Please go ahead.

Speaker #2: Thank you. Good day, everyone, and welcome to Alibaba Group's June quarter 2026 earnings conference call. Joining the call today are Jiu Cai, Chairman; Eddie Wu, Chief Executive Officer; Toby Xu, Chief Financial Officer; and Jiang Fan, Chief Executive Officer of Alibaba E-Commerce Business Group.

Lydia Liu: Thank you. Good day, everyone, and welcome to Alibaba Group's June quarter 2026 earnings conference call. Joining the call today are Joseph Tsai, Chairman, Eddie Wu, Chief Executive Officer, Toby Xu, Chief Financial Officer, Jiang Fan, Chief Executive Officer of Alibaba E-commerce Business Group. Before we get started, I would like to remind you that today's discussion may contain forward-looking statements based on management's current expectations that are subject to risks and uncertainties. We also make reference to non-GAAP financial measures. Reconciliations between GAAP and non-GAAP measures are included in today's earnings press release and investor presentation. Our comments will be on year-over-year comparisons unless we state otherwise. A replay of the call will be available on our website later today. With that, I would like to turn the call over to Eddie.

Speaker #2: Before we get started, I would like to remind you that today's discussion may contain forward-looking statements based on management's current expectations, which are subject to risks and uncertainties.

Speaker #2: We also make reference to non-GAAP financial measures. Reconciliations between GAAP and non-GAAP measures are included in today's earnings press release and investor presentation. Our comments will be on year-over-year comparisons unless we state otherwise.

Speaker #2: A replay of the call will be available on our website later today. With that, I would like to turn the call over to Eddie.

Speaker #3: 各位投资人。

Eddie Wu: Good evening, good morning, and welcome to Alibaba Group's earnings call for the Q1 of fiscal year 2027. Over the past quarter, Alibaba's strategic AI investments have translated into robust results, with total group revenue growing 9% year-over-year. AI commercialization has also accelerated across the board. Alibaba Cloud's external revenue grew 45%, and EBITDA increased 133% year-over-year, continuing to deliver on our commitment to accelerate growth. Revenue from AI-related products has maintained triple-digit growth for the 12th consecutive quarter, with annual revenue run rate surpassing 49.5 billion RMB, around 7.3 billion US dollars. It is the core engine of Alibaba Cloud's growth acceleration. I will now walk you through four key areas: AI and cloud commercialization, full-stack AI capabilities, AI application ecosystem, and consumption business. First, AI and cloud commercialization accelerated across the board and is expected to sustain high growth going forward.

Speaker #4: Good evening, good morning, and welcome to Alibaba Group's earnings call for the second quarter of fiscal year 2026. Over the past quarter, Alibaba's strategic AI investments have translated into robust results, with total group revenue growing 9% year over year.

Speaker #4: AI commercialization has also accelerated across the board. Alibaba Cloud's external revenue grew 45%, and EBITDA increased 133% year over year, continuing to deliver on our commitment to accelerate growth.

Speaker #4: Revenue from AI-related products has maintained triple-digit growth for the 12th consecutive quarter, with annual revenue run rate surpassing 49.5 billion RMB, or around $7.3 billion USD.

Speaker #4: It is the core engine of Alibaba Cloud’s growth acceleration. I’ll now walk you through four key areas: AI and cloud commercialization, full-stack AI capabilities, the AI application ecosystem, and the consumption business.

Speaker #4: First, AI and cloud commercialization accelerated across the board and is expected to sustain high growth going forward. This quarter, Alibaba Cloud's external revenue growth accelerated to 45%, a 22-quarter high, while adjusted EBITDA margin reached 11.6%.

Eddie Wu: This quarter, Alibaba Cloud's external revenue growth accelerated to 45%, a 22-quarter high, while adjusted EBITDA margin reached 11.6%. Notably, this 45% growth was broad-based, driven by compute storage Model-as-a-Service, MaaS, and AI applications. We proactively scaled back low-margin business, continuing to improve the quality of our growth. This quarter, annual revenue run rate from AI-related products exceeded 49.5 billion RMB, and its share of Alibaba Cloud's external revenue rose to 35%. AI-related products generate significantly higher gross margins than the average cloud portfolio. Our recurring AI-related product revenue spans multiple layers, AI compute, MaaS, and AI applications. This multilayered mix of AI revenue sources and monetization models means growing customer demand at any layer converts directly into commercial opportunity for us. This structural advantage will underpin sustained rapid growth in recurring AI-related product revenue going forward.

Speaker #4: Notably, this 45% growth was broad-based, driven by compute, storage, model-as-a-service (MaaS), and AI applications. We proactively scaled back low-margin business, continuing to improve the quality of our growth.

Speaker #4: This quarter, annual revenue run rate from AI-related products exceeded RMB 49.5 billion. Revenue rose by 35%. AI-related products generate significantly higher gross margins than the average cloud portfolio. Our recurring AI-related product revenue spans multiple layers: AI compute, models, and AI applications.

Speaker #4: This multi-layered mix of AI revenue sources and monetization models means that growing customer demand at any layer converts directly into commercial opportunity for us. This structural advantage will underpin sustained rapid growth in recurring AI-related product revenue going forward.

Speaker #4: The surge in AI agents directly drives demand for tokens and GPU compute, while also significantly boosting demand for our traditional cloud products across CPU compute, storage, databases, and networking.

Eddie Wu: The surge in AI agents directly drives demand for tokens and GPU compute, while also significantly boosting demand for our traditional cloud products across CPU compute, storage databases, and networking. Alibaba Cloud is undergoing a comprehensive upgrade to an agentic cloud. Based on the latest data, the ARR of our model and application services, including MaaS, has surpassed 16 billion RMB. Based on current market feedback and our contract pipelines, compute demand will continue to outstrip supply. As we continue to ramp up our supply, our AI and cloud revenue growth will accelerate further in the coming quarters, alongside continued improvement in profitability. Second, our full-stack AI capabilities continue to strengthen, marked by the scaled commercialization of proprietary chips, faster model iteration, and a thriving open source ecosystem. This quarter, deepening synergy between proprietary T-Head chips and proprietary foundation models further improved our AI commercialization efficiency.

Speaker #4: Alibaba Cloud is undergoing a comprehensive upgrade to an agentic cloud. Based on the latest data, the ARR of our model and application services, including MASS, has surpassed RMB 16 billion.

Speaker #4: Based on current market feedback and our contract pipelines, compute demand will continue to outstrip supply. As we continue to ramp up our supply, our AI and cloud revenue growth will accelerate further in the coming quarters.

Speaker #4: Alongside continued improvement in profitability, second, our full-stack AI capabilities continue to strengthen, marked by the scaled commercialization of proprietary chips, faster model iteration, and a thriving open-source ecosystem.

Speaker #4: This quarter, deepening synergy between proprietary T-head chips and proprietary foundation models further improved our AI commercialization efficiency. T-heads established a full-stack proprietary silicon portfolio spanning GPU, CPU, and networking chips as of early August.

Eddie Wu: T-Head has established a full-stack proprietary silicon portfolio spanning GPU, CPU, and networking chips. As of early August, Zhenwu chips have served more than 650 customers on Alibaba Cloud. The Supernode instance, powered by T-Head's next generation Zhenwu M890 AI processor, recently launched on Alibaba Cloud at commercial scale. We expect supply to continue ramping up in the H2 of the year to meet strong customer demand. Alibaba Cloud's Zhenwu M890 Supernode can efficiently run inference workload for foundation models with more than 2 trillion parameters. Both Kimi K3 and Qwen 3.8-Max are already using it to provide MaaS services to external customers. At the data center layer, Alibaba Cloud has cut the delivery time for hyperscale AI data centers to 100 days, a world-leading pace that will significantly speed up our global compute infrastructure buildup.

Speaker #4: Zhenwu chips have served more than 650 customers on Alibaba Cloud. The supernode instance, powered by T-head's next-generation Zhenwu M890 AI processor, was recently launched on Alibaba Cloud at commercial scale.

Speaker #4: We expect supply to continue ramping up in the second half of the year to meet strong customer demand. Alibaba Cloud's Zhenwu M890 supernode can efficiently run inference workloads for foundation models with more than 2 trillion parameters. Both KBK3 and Q1, 3.8 Max are already using it to provide mass services to external customers.

Speaker #4: At the data center layer, Alibaba Cloud has cut the delivery time for hyperscale AI data centers to 100 days—a world-leading pace that will significantly speed up our global compute infrastructure buildout.

Speaker #4: At the model layer, our model release cadence has intensified over the past month, with major iterations across our large language, image, audio, video, and music models, all ranking among the world's top tier.

Eddie Wu: At the model layer, our model release cadence has intensified over the past month with major iterations across our large language, image, audio, video, and music models, all ranking among the world's top tier. Last week, we opened the model weights of Qwen 3.8-Max with 2.4 trillion parameters and the Qwen 3.8-27B model series. To date, the Qwen model series has been downloaded more than 3 billion times globally with more than 300,000 derivative models built on it. We believe a thriving open source model ecosystem drives greater demand for our cloud computing services, creating a virtuous cycle. Third, our AI native applications span both enterprise and consumer use cases, driving rapid growth in token consumption. On the enterprise side, we launched Qwen Work, a new AI productivity product built for enterprise workforce scenarios, delivering agentic capabilities at scale.

Speaker #4: Last week, we opened the modeled weights of Q1 3.8 Max with 2.4 trillion parameters and the Q1 3.8 27B model series. To date, the Q1 model series has been downloaded more than 3 billion times globally, with more than 300,000 derivative models built on it.

Speaker #4: We believe a thriving open-source model ecosystem drives greater demand for our cloud computing services, creating a virtuous cycle. Third, our AI-native applications span both enterprise and consumer use cases, driving rapid growth in token consumption.

Speaker #4: On the enterprise side, we launched Q1 Work, a new AI productivity product built for enterprise workforce scenarios, delivering agentic capabilities at scale. We expect productivity agents to become another engine of ARR growth.

Eddie Wu: We expect productivity agents to become another engine of ARR growth. On the consumer side, the Qwen app continued to steadily grow its user base and is expanding the range of its value-added offerings. Through close coordination between Alibaba Token Hub and Alibaba Cloud, we are running a highly efficient commercial flywheel across compute models, tokens, applications, and monetization. Fourth, our e-commerce businesses remained solid this quarter. In quick commerce, we continued to narrow losses substantially while growing business scale by 45%, with unit economics improving quarter over quarter. Having crossed the AI commercialization inflection point last quarter, we are now seeing growth accelerate and margins expand this quarter. Our AI business' own capacity to self-fund and sustain itself is strengthening, giving us greater confidence to keep investing. Looking ahead, AI has become Alibaba's most certain growth engine. We will stay strategically disciplined and drive long-term growth through our full-stack AI capabilities.

Speaker #4: On the consumer side, the Q1 app continued to steadily grow its user base and is expanding the range of its value-added offerings. Through close coordination between Alibaba Token Hub and Alibaba Cloud, we're running a highly efficient commercial flywheel across compute, models, tokens, applications, and monetization.

Speaker #4: Fourth, our e-commerce businesses remained solid this quarter. In quick commerce, we continued to narrow losses substantially while growing business scale by 45%, with unit economics improving quarter over quarter.

Speaker #4: Having crossed the AI commercialization inflection point last quarter, we're now seeing growth accelerate and margins expand this quarter. Our AI business's own capacity to self-fund and sustain itself is strengthening, giving us greater confidence to keep investing.

Eddie Wu: Our AI business' own capacity to self-fund and sustain itself is strengthening, giving us greater confidence to keep investing. Looking ahead, AI has become Alibaba's most certain growth engine. We will stay strategically disciplined and drive long-term growth through our full-stack AI capabilities.

Speaker #4: Looking ahead, AI has become Alibaba's most certain growth engine. We will stay strategically disciplined and drive long-term growth through our full-stack AI capabilities. I'll now hand over to Toby to walk you through our financial results.

Eddie Wu: I will now hand over to Toby to walk you through our financial results. Thank you.

Speaker #4: Thank you.

Speaker #2: Thank you, Eddie. Our strategic priorities in AI plus cloud and consumption businesses, backed by disciplined investments, delivered a strong result this quarter. Cloud segment revenue growth further accelerated to 45%, with its EBITDA margin sequentially rising to 12%.

Toby Xu: Thank you, Eddie. Our strategic priorities in AI plus cloud and consumption businesses, backed by disciplined investments, delivered strong results this quarter. Cloud segment revenue growth further accelerated to 45%, with its EBITDA margin sequentially rising to 12%. AI-related product revenue continued to drive this momentum, marking the 12th consecutive quarter of triple-digit growth and accounting for 35% of external cloud revenue. The strong performance demonstrates growing customer adoption of our full-stack AI capabilities, spanning AI agents, models, cloud infrastructure, and the proprietary chips, as well as our enhanced scale efficiencies and the robust pricing power in a supply-constrained market. On consumption, Taobao Instant Commerce continued to improve its unit economics while maintaining market share. Overall, e-commerce EBITDA remained relatively stable year over year. To realize synergies across our commerce platforms and strengthen our full-stack AI capabilities, we have implemented strategic alignment of certain businesses in our financial reporting.

Speaker #2: AI-related product revenue continued to drive this momentum, marking the 12th consecutive quarter of triple-digit growth and accounting for 35% of external cloud revenue. The strong performance demonstrates growing customer adoption of our full-stack AI capabilities, spanning AI agents, models, cloud infrastructure, and proprietary chips, as well as our enhanced scale efficiencies and robust pricing power in a supply-constrained market.

Speaker #2: On consumption, Taiwan Instant Commerce continued to improve its unit economics. While maintaining market share, overall e-commerce EBITDA remained relatively stable year over year. To realize synergies across our commerce platforms and strengthen our full-stack AI capabilities, we have implemented strategic realignment of certain businesses in our financial reporting.

Speaker #2: Starting from this quarter, our segment reporting will present the following: First, Alibaba E-commerce Group; second, AI Cloud and Computer Services; third, AI Labs and Applications; and fourth, all others.

Toby Xu: Starting from this quarter, our segment reporting will present the following. First, Alibaba E-commerce Business Group. Second, AI cloud and computer services. Third, AI labs and applications. And number four, all others. Now, let's look at the financial results for this quarter. Total revenue increased 9% year over year to RMB 269 billion, driven by the strong momentum in cloud business and quick commerce. Total adjusted EBITDA decreased 30% to RMB 27.3 billion, primarily attributable to the investment in technology, partly offset by the improved operating results in our cloud business, as well as enhanced operating efficiencies across various businesses. Our GAAP net income was RMB 10.4 billion, a decrease of 75%, primarily due to the decrease in income from operations and decrease in net gains from disposal of investments and mark-to-market changes of our equity investments.

Speaker #2: Now, let's look at the financial results for this quarter. Total revenue increased 9% year over year to RMB 269 billion, driven by the strong momentum in the cloud business and quick commerce.

Speaker #2: Total adjusted EBITDA decreased 30% to RMB 27.3 billion, primarily attributable to investment in technology, partly offset by improved operating results in our cloud business, as well as enhanced operating efficiencies across various businesses.

Speaker #2: Our GAAP net income was RMB 10.4 billion, a decrease of 75%, primarily due to the decrease in income from operations and the decrease in net gains from disposal of investments and mark-to-market changes of our equity investments.

Speaker #2: Operating cash flow this quarter increased by 11% to RMB 22.9 billion, compared to RMB 20.7 billion in the same quarter last year. Free cash flow was an outflow of RMB 44.7 billion.

Toby Xu: Operating cash flow this quarter increased by 11% to RMB 22.9 billion, compared to RMB 20.7 billion in the same quarter last year. Free cash flow was an outflow of RMB 44.7 billion, compared to an outflow of RMB 18.8 billion in the same quarter last year. The decrease was mainly attributed to the investment in cloud infrastructure. CapEx was RMB 67.7 billion this quarter, reflecting our continued investments in AI infrastructure to meet strong and growing customer demand. The significant year-over-year increase is due to several reasons, including fluctuations in procurement cycles, increasing in CPU compute capacity driven by anticipated growing customer adoption of AI agents in a higher pricing of a broad range of chip components. As of 30 June 2026, we held approximately $30.7 billion in net cash. Excluding debt with maturities beyond five years, our net cash position stands at approximately $46.5 billion.

Speaker #2: Compared to an outflow of RMB 18.8 billion in the same quarter last year, the decrease was mainly attributed to the investment in cloud infrastructure.

Speaker #2: Capex was RMB 67.7 billion this quarter, reflecting our continued investments in AI infrastructure to meet strong and growing customer demand. The significant year-over-year increase is due to several reasons, including fluctuations in procurement cycles, an increase in CPU compute capacity driven by anticipated growing customer adoption of AI agents, and higher pricing of a broad range of chip components.

Speaker #2: As of June 30, 2026, we held approximately $30.7 billion in net cash, excluding debt with maturities beyond five years. Our net cash position stands at approximately $46.5 billion. This balance sheet strength gives us confidence to invest for robust growth.

Toby Xu: This balance sheet strength gives us confidence to invest for robust growth. Our AI plus cloud investment has a clear path to attractive ROIC. Our servers equipped with chips typically reach breakeven within three years. With a five-year useful life, we expect them to generate positive free cash flow at least in the two years following breakeven. For the quarter ended 30 June 2026, we repurchased shares of an aggregate consideration of $162 billion. We remain committed to maximizing long-term shareholder returns through disciplined capital allocation across investments for AI plus cloud business growth, share buybacks, and dividends. We will adjust our priorities as market conditions and the strategic needs evolve. Now let's first look at our eCommerce businesses. The new Alibaba E-commerce Business Group reflects our strategic focus on unlocking significant synergies across our domestic and cross-border eCommerce businesses.

Speaker #2: Our AI plus cloud investment has a clear path to attractive ROIC. Our services equipped with chips typically reach break-even within three years. With a five-year useful life, we expect them to generate positive free cash flow in at least the two years following break-even.

Speaker #2: For the quarter ended June 30, 2026, we repurchased shares for an aggregate consideration of $162 billion. We remain committed to maximizing long-term shareholder returns through disciplined capital allocation across investments for AI plus cloud business growth, share buybacks, and dividends.

Speaker #2: We will adjust our priorities as market conditions and strategic needs evolve. Now, let's first look at our e-commerce businesses. The new Alibaba E-commerce Group reflects our strategic focus on unlocking significant synergies across our domestic and cross-border e-commerce businesses.

Speaker #2: Starting from this quarter, we will present Alibaba E-commerce Group's revenue as follows: first, China e-commerce; second, China quick commerce; third, international e-commerce; and fourth, global wholesale.

Toby Xu: Starting from this quarter, we will present Alibaba E-commerce Business Group's revenue as the following. First, China eCommerce. Second, China Quick Commerce. Third, International eCommerce, and fourth, Global Wholesale. Revenue for Alibaba E-commerce Business Group was RMB 205.9 billion, an increase of 4%. Customer managing revenue decreased by 7%. Excluding the contract revenue impact from the new business development program, customer managing revenue would have grown by 1% year over year. Revenue from China quick commerce business was RMB 53.3 billion, an increase of 45%, driven by Freshippo and Taobao Instant Commerce. Alibaba E-commerce Business Group's adjusted EBITDA remained relatively stable year over year at RMB 39.7 billion, underscoring our cost discipline against the backdrop of increased investments in user experiences and technology. Taobao Instant Commerce continued to improve its unit economics quarter over quarter while maintaining market share, driven by higher average order value and enhanced fulfillment logistics efficiency.

Speaker #2: Revenue for Alibaba e-commerce group was RMB 205.9 billion, an increase of 4%. Customer revenue decreased by 7%, excluding the contract revenue impact from the new business development program.

Speaker #2: Customer management revenue would have grown by 1% year over year. Revenue from our China quick commerce business was RMB 53.3 billion, an increase of 45%, driven by Fresh Apple and Taobao Instant Commerce.

Speaker #2: Alibaba e-commerce group's adjusted EBITDA remained relatively stable year over year at RMB 39.7 billion, underscoring our cost discipline against the backdrop of increased investments in user experiences and technology.

Speaker #2: Taobao Instant Commerce continued to improve its unit economics quarter over quarter, while maintaining market share, driven by higher average order value and enhanced fulfillment logistics efficiency.

Speaker #2: In addition, AliExpress achieved operating profit this quarter. We aim to maintain steady profit in our conventional e-commerce business, while continuing to drive profitability improvement in our quick commerce business.

Toby Xu: In addition, AliExpress achieved operating profit this quarter. We aim to maintain steady profit in our conventional eCommerce business while continuing to drive profitability improvement in our quick commerce business. Now let's review the business updates and results of AI cloud and compute services, which comprises the Cloud Intelligence Group and T-Head. The year-over-year growth of total revenue and revenue from external customers both accelerated to 45%. Revenue from Alibaba Cloud also accelerated, growing 45% year over year. We are confident the growth rate will further accelerate in the coming quarters. This quarter's AI related product revenue was RMB 12.4 billion, implying a revenue run rate of RMB 49.5 billion. It delivered a 12th consecutive quarter of triple-digit growth and accounted for 35% of external cloud revenue.

Speaker #2: Now, let's review the business updates and results of AliCloud and AI Cloud and Compute Services, which comprise the Cloud Intelligence Group and T-Head.

Speaker #2: The year-over-year growth of total revenue and revenue from external customers both accelerated to 45%. Revenue from Alibaba Cloud also accelerated, growing 45% year over year.

Speaker #2: We are confident the growth rate will further accelerate in the coming quarters. This quarter's AI-related product revenue was RMB 12.4 billion, implying an annual revenue run rate of RMB 49.5 billion. It delivered the 12th consecutive quarter of triple-digit growth and accounted for 35% of external cloud revenue.

Speaker #2: The adjusted EBITDA margin expanded to 12%, driven by improved economies of scale, stronger pricing power of AI-related products, and a tight market supply.

Toby Xu: The adjusted EBITDA margin expanded to 12%, driven by improved economies of scale and a stronger pricing power of AI related products amid tight market supply. We expect EBITDA margin to further expand steadily in the coming quarters by improving resource utilization, optimizing model portfolio, and innovating new scenarios. We are accelerating the growth of AI plus cloud business and driving greater benefits of scale. AI lab and applications comprises AI model labs, DingTalk consumer business group, and DingTalk work. Its adjusted EBITDA was a loss of RMB 13.9 billion, primarily due to our increased investment in AI capabilities and higher inference costs related to DingTalk APP. The loss significantly narrowed quarter-over-quarter due to the reduction in marketing expenses for DingTalk APP. We expect the segment loss to narrow over the coming quarters, driven by improving efficiency in both model training and marketing spend on DingTalk APP.

Speaker #2: We expect EBITDA margin to further expand steadily in the coming quarters. By improving resource utilization, optimizing our model portfolio, and innovating new scenarios, we are accelerating the growth of our AI plus cloud business and driving greater benefits of scale.

Speaker #2: AI Lab and Applications comprises AI Model Labs, Quick Consumer Business Group, and Quick Work. Its adjusted EBITDA was a loss of RMB 13.9 billion, primarily due to our increase in investment in AI capabilities and higher inference costs related to Quick App.

Speaker #2: The loss significantly narrowed quarter over quarter due to the reduction in marketing expenses for Quick APP. We expect the segment loss to narrow over the coming quarters, driven by improving efficiency in both model training and marketing spend on Quick APP.

Speaker #2: We have launched our frontier language, coding, video, audio, image, and music models, all delivering top-tier performance. Two hundred fifty million users have had their first AI-driven shopping experience through Quick APP's agentic features across an expanding range of e-commerce and other services since the launch of Quick APP.

Toby Xu: We have launched our frontier language coding, video, audio, image, and music models, all delivering top-tier performance. 250 million users have had their first AI-driven shopping experience through DingTalk APP's agentic features across an expanding range of eCommerce and other services since the launch of DingTalk APP. All other segment revenue remained stable at RMB 28.8 billion. All others adjusted EBITDA was a loss of RMB 3.3 billion, primarily due to our increased investment in technology. AI has progressed from incubation to commercialization at scale. As we expand our market share, strengthen AI leadership, and improving operating efficiency, we are gaining greater strategic and financial flexibility to make disciplined and sustained investments in both full stack AI capabilities and consumption opportunities, driving secular growth and greater value for our shareholders. Thank you. That's the end of our prepared remarks. We can open up for Q&A.

Speaker #2: All other segment revenue remained stable at RMB 28.8 billion. All Others' adjusted EBITDA was a loss of RMB 3.3 billion, primarily due to our increased investment in technology.

Speaker #2: AI has progressed from incubation to commercialization at scale. As we expand our market share, strengthen AI leadership, and improve operating efficiency, we are gaining greater strategic and financial flexibility to make disciplined and sustained investments in both full-stack AI capabilities and consumption opportunities.

Speaker #2: Driving secular growth and creating greater value for our shareholders. Thank you. That concludes our prepared remarks. We can now open up for Q&A.

Speaker #1: Thank you, Toby. We will now begin the Q&A session. You are welcome to ask questions in Chinese or English. If needed, third-party translators will provide consecutive interpretation.

Lydia Liu: Thank you, Toby. We will now begin the Q&A session. 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 statements in the original language will preview. Operator, please start Q&A session. Thank you.

Speaker #1: In the case of any discrepancy, our management statements in the original language will prevail. Operator, please start the Q&A session. Thank you.

Speaker #3: Thank you. If you wish to ask a question, please press star one on the telephone and wait for your name to be announced. If you wish to cancel your request, please press two.

Operator: Thank you. If you wish to ask a question, please press star one on your telephone and wait for your name to be announced. If you wish to cancel your request, please press two. If you are on a speakerphone, please pick up the handset to ask a question. To give more people the opportunity to ask questions, please keep yourself to no more than one question at a time. Your first question comes from Alicia Yap with Citigroup. Please go ahead.

Speaker #3: If you are on a speakerphone, please pick up the handset to ask a question. To give more people the opportunity to ask questions, please limit yourself to no more than one question at a time.

Speaker #3: Your first question comes from Alicia Yap with Citi Group. Please go ahead.

Speaker #4: Thank you. Good evening, management. Thanks for taking my questions, and also congrats on your solid cloud performance. Management, please comment on the reasons and the drivers for the significant increase in CapEx this quarter.

Alicia Yap: Thank you. Good evening, management. Thanks for taking my questions and also congrats on your solid cloud performance. Could management please comment on the reasons and the drivers for the significant increase in the CapEx this quarter? What is the expected CapEx trend for the coming quarters? Are there any updates to the existing 3-year CapEx budget that you have of this RMB 380 billion that you mentioned before? We would appreciate if management can also provide a breakdown of the CapEx allocation across the different services like the training costs and all that. What is management expected return on the invested capital for this investment? Thank you.

Speaker #4: And also, what is the aspect that CapEx trend for the coming quarters? And are these are there any updates to the existing three-year CapEx budget that you have of this 380 billion that you mentioned before?

Speaker #4: And also, we would appreciate it if management could provide a breakdown of the CapEx allocation across the different services, like the training costs and so on.

Speaker #4: And then also, what is management's expected return on the invested capital for this investment? Thank you.

Speaker #5: Oh, 大家晚上好，也祝贺你们取得云方面的非常扎实的业绩表现。我想问的问题主要是有关于本季度 CapEx 大幅增加背后的原因和驱动力。还想了解一下接下来几个季度你们对于 CapEx 的总体趋势怎么看，以及对于之前公布的，就是三年投入 3,800 亿的这样一个预算，是不是有任何新的更新。另外，想要了解当前这些 CapEx 的分配情况，多少用于训练等等各方面的一个分解，然后管理层是否可以评论这些 CapEx 它的一个投入资本的回报率。

Alicia Yap: 感谢管理层接受我的问题。大家晚上好，也祝贺你们取得云方面的非常扎实的业绩表现。我想问的问题主要是有关于本季度CapEx大幅增加背后的原因和驱动力。还想了解一下接下来几个季度你们对于CapEx的总体趋势怎么看，以及对于之前公布的三年投入RMB 3,800亿的这样一个预算，是不是有任何新的更新？另外想要了解当前这些CapEx它的分配情况，多少用于训练等等各方面的一个分解。然后管理层是否可以评论这些CapEx它的一个投入资本的回报率。

Eddie Wu: [Foreign language].

Speaker #6: 好，谢谢您的问题。这个问题我觉得挺重要的，我也想借这个问题详细解释一下我们在 AI 方面的整体商业模型，以及对未来 CapEx 投入的预期。我们去年 2 月份公布了三年 3,800 亿的投资计划，到今年 6 月季度末已经累计投入了 1,900 亿，进度还是符合预期的。本季度的 671 亿确实高了一些，但因为硬件交付有一个周期，并不是每个季度均匀的，所以更多是设备交付的波动性。同时，本季度我们还增加了对 CPU 的采购，因为 Agent 时代我们看到对 CPU 的需求在大幅增长。当然也有芯片组件价格上涨的因素在其中。总体来看，我们不应该强调本年度的 CapEx 是 671 亿乘以 4 这样的一个匀速投入建设，但总体来说，我们还是希望今年的投入建设能够保持一个更积极的态度。

Joseph Tsai: 好，谢谢您的问题。这个问题我觉得挺重要的，我也想借这个问题详细解释一下我们的AI方面的整个的商业模型，以及对未来的CapEx投入的一个预期。我们去年2月份公布了三年3,800亿的投资计划，到今年6月季度末已经累计投入了1,900亿，进度还是符合预期的。本季度的677亿确实高了一些，但是因为硬件交付它有一个周期，并不是每个季度均匀的，所以更多的是一个设备交付的波动性。同时本季度我们还增加了对于CPU的采购，因为agent时代我们看到对CPU的需求在大幅地增长，当然也有芯片组件价格的上涨的因素构成。总体来看，我们不应该强调本年度的CapEx是677乘以4这样的一个匀速投入的建设。但总体来说，我们是希望我们今年的投入建设还是维持在一个更积极的态度上。Thank you very much for the question.

Speaker #5: Thank you very much for the question. It's an important question, and I'd like to take the opportunity to perhaps explain generally what our business model is for AI, and our expectations around CapEx going forward.

Joseph Tsai: It is an important question. I would like to take the opportunity perhaps to explain generally what our business model is for AI at our expectations around CapEx going forward. Indeed, last February, we announced a 3-year capital investment plan with total investment of RMB 380 billion. As of the end of the June quarter this year, we had already spent RMB 190 billion with progress broadly in line with our expectations. While this quarter spending of RMB 67.1 billion is somewhat higher, hardware deliveries follow different procurement cycles. There can be fluctuations in the cadence and pace of hardware deliveries. It is not evenly distributed across different quarters. The increase primarily reflects volatility in those equipment delivery schedules. At the same time, we increased procurement of CPUs this quarter as we are witnessing a substantial surge in demand driven by the agent-centric era.

[Translator]: It is an important question. I would like to take the opportunity perhaps to explain generally what our business model is for AI at our expectations around CapEx going forward. Indeed, last February, we announced a 3-year capital investment plan with total investment of RMB 380 billion. As of the end of the June quarter this year, we had already spent RMB 190 billion with progress broadly in line with our expectations. While this quarter spending of RMB 67.1 billion is somewhat higher, hardware deliveries follow different procurement cycles. There can be fluctuations in the cadence and pace of hardware deliveries. It is not evenly distributed across different quarters. The increase primarily reflects volatility in those equipment delivery schedules. At the same time, we increased procurement of CPUs this quarter as we are witnessing a substantial surge in demand driven by the agent-centric era.

Speaker #5: So indeed, last February, we announced a three-year capital investment plan with total investment of RMB 380 billion as of the end of the June quarter this year.

Speaker #5: We had already spent RMB 190 billion, with progress broadly in line with our expectations. While this quarter's spending of RMB 67.1 billion is somewhat higher, hardware deliveries follow different procurement cycles.

Speaker #5: There can be fluctuations in the cadence and pace of hardware deliveries, so it's not evenly distributed across different quarters. The increase primarily reflects volatility in those equipment delivery schedules.

Speaker #5: At the same time, we increased procurement of CPUs this quarter, as we are witnessing a substantial surge in demand driven by the agent-centric era.

Speaker #5: Of course, rising prices for semiconductor components have also contributed to this trend. So I don't think we should take the spending for this quarter and multiply it by four to come up with an annualized figure for the year or to expect there will be a steady linear progression.

Joseph Tsai: Of course, rising prices for semiconductor components have also contributed to this trend. I do not think we should take the spending for this quarter and multiply it by 4 to come up with an annualized figure for the year or to expect that there will be a steady linear progression.

[Translator]: Of course, rising prices for semiconductor components have also contributed to this trend. I do not think we should take the spending for this quarter and multiply it by 4 to come up with an annualized figure for the year or to expect that there will be a steady linear progression.

Speaker #5: The build-out has been progressing at a steady pace, but that is the overall situation.

Joseph Tsai: The build-out has been progressing at a steady pace, but that is the overall situation。好。我也想趁此机会跟各位投资人朋友解释一下全栈式的AI平台的服务的商业模式，本质上是一个重资产的一个商业模式。我们现在看到所有的AI的变现方式，无论是AI软件订阅，还是大模型的API推理，还是GPU的AS服务，以及AI相关的训练或者推理的软件服务，本质上所有的这些变现都需要在AI的算力中心这个基础上，而AI算力中心的建设，我们才能够获得市场份额的高速增长。所以这是一个非常明确的一个重资产的商业模式。而重资产商业模式要获得高速的增长的前提，需要在CapEx投入上进行前置。所以我们会看到，我们从2025年开始进入了一个非常积极的硬件方面的一个投资建设周期。从这个角度上来说，我们要获得一个高速增长，就必须在前面几年去投入更多的AI算力中心的建设。所以这是我们商业模式上决定的，就必须是CapEx先行，才能获得后面的业务的增长。Next, let me expand on our full stack AI business model.

[Translator]: The build-out has been progressing at a steady pace, but that is the overall situation.

Eddie Wu: [Foreign language].

Speaker #6: 我也想趁着今晚各位投资人朋友解释一下，全站式的 AI 平台服务的商业模式本质上是一个重资产的商业模式。我们现在看到，所有的 AI 变现方式，无论是 AI 软件订阅，还是大模型的 API 推理，还是 GPU 的服务，以及 AI 相关的训练或者推理的软件服务，本质上所有这些变现都需要建立在 AI 算力中心这个基础上。而 AI 算力中心的建设，才能够带来市场份额的高速增长。所以，这是一个非常明确的重资产商业模式。而重资产商业模式要获得高速增长的前提，是需要在 CapEx 投入上进行前置。所以我们会看到，从 2025 年开始，我们将进入一个非常积极的硬件投资建设周期。从这个角度来说，要获得高速增长，就必须在前面几年投入更多 AI 算力中心的建设。所以，这是我们的商业模式决定的，必须是 CapEx 先行，才能获得后面的业务增长。

Speaker #5: business model. This is an asset-heavy business model. If you think about all of the different ways that AI is monetized and can be monetized be it through software subscriptions, be it through API calls, through models as a service, through training, inference, you know, in all of these different respects, you need compute centers to run and to monetize.

Joseph Tsai: This is an asset-heavy business model. If you think about all of the different ways that AI is monetized and can be monetized, be it through software subscriptions, be it through API calls, through models as a service, through training inference, in all of these different respects, you need compute centers to run and to monetize. It is only possible to monetize

[Translator]: This is an asset-heavy business model. If you think about all of the different ways that AI is monetized and can be monetized, be it through software subscriptions, be it through API calls, through models as a service, through training inference, in all of these different respects, you need compute centers to run and to monetize. It is only possible to monetize

Speaker #5: So it's only possible to monetize when you have that compute capacity in place. What that means is we need to be investing upfront in order to be able to grow this business model.

Eddie Wu: When you have that compute capacity in place. What that means is that we need to be investing upfront in order to be able to grow this business model and monetize across all of those different areas. That is why beginning in 2025, we began a heavy investment cycle in hardware. This is really a function of that asset heavy business model, as I explained. In order to be able to capture that future growth, we first need to make these CapEx investments to build out the necessary compute capacity.

[Translator]: When you have that compute capacity in place. What that means is that we need to be investing upfront in order to be able to grow this business model and monetize across all of those different areas. That is why beginning in 2025, we began a heavy investment cycle in hardware. This is really a function of that asset heavy business model, as I explained. In order to be able to capture that future growth, we first need to make these CapEx investments to build out the necessary compute capacity.

Speaker #5: And monetize across all of those different areas. So, that's why, beginning in 2025, we began a heavy investment cycle in hardware. And this is really a function of that asset-heavy business model, as I explained, in order to be able to capture that future growth.

Speaker #5: We first need to make these CapEx investments to build out the necessary compute capacity.

Speaker #6: 后面我再来解释一下，为什么在现在这个阶段进行 CapEx，进行 AI 算力相关的 CapEx 投资的回报确定性非常高。行业共识是在 2030 年之前，我们看不到 AI 算力紧缺的这个情况会有非常大的改变。所以在这个行业背景下，我们现在看到我们的 AI 算力的 CapEx 投资回报确定性非常高。从数据上来看，按照我们现在的 AI 产品的平均毛利水平，我们的 CapEx 可以实现在三年之内回本。而我们 AI 的产品毛利润水平还在持续提升的过程中，这个回报周期未来还会持续缩短，比如说往 2.5 年回本的方向去推进。

Joseph Tsai: 好，后面我再来解释一下为什么在现在这个阶段进行AI算力相关的CapEx投资的回报确定性非常高。行业共识是在2030年之前我们看不到AI算力紧缺的这个情况会有非常大的改变。所以在这个行业背景下，我们现在看到我们的AI算力的CapEx投资回报确定性非常高。从数据上来看，按照我们现在的AI产品的平均毛利水平，我们的CapEx可以在三年之内回本。而我们AI的产品的毛利润水平还在处于持续的提升过程当中，这个回报周期未来还会持续地缩短，比如说往2.5年回本的方向去推进。

Eddie Wu: [Foreign language].

Speaker #5: We view the return on invested capital in AI-related CapEx as highly certain. There's consensus across the industry that the current shortage in AI compute will not be resolved until at least 2030.

Eddie Wu: Next, let me explain why we see return on invested capital in AI related CapEx as highly certain. There is a consensus across the industry that the current shortage in AI compute will not be resolved until at least 2030. Industry wide then it makes sense that there should be high certainty in our investments in AI compute. Based on average gross margins today, roughly, we can break even on AI related CapEx in 3 years. Of course, average gross margin continues to rise, and we expect to be able to shorten that payback period, say to 2.5 years.

Speaker #5: So, industry-wide, it makes sense that there should be high certainty in our investments in AI compute. Based on average gross margins today, we can roughly break even on AI-related CapEx in three years.

Speaker #5: And of course, average gross margin continues to rise, and we expect to be able to shorten that payback period—say, to 2.5 years.

Eddie Wu: [Foreign language].

Speaker #6: 按照我们现在的投资回报周期，我们的 AI 算力在投入三年之后回本之后，还会非常长时间的持续不断的贡献正向的现金流。从我们现在看到的实际情况来看，一个最直接的例子在我们的数据中心里面，2020 年购买的 A100，2018 年购买的 V100，到现在还是近乎满载的被客户使用。算力资产 AI 算力资产的实际使用寿命周期远远长于理论上的折旧周期。

Joseph Tsai: 按照我们现在的投资回报周期，我们的AI算力在投入三年之后，回本之后，还会非常长时间地持续不断地贡献正向的现金流。从我们现在看到的实际情况来看，一个最直接的例子，在我们的数据中心里面，2020年购买的A100，2018年购买的V100，到现在还是近乎满载地被客户使用。AI算力资产的实际使用寿命周期远远长于理论上的折旧周期。

Eddie Wu: [Foreign language].

Eddie Wu: Following that 3-year payback period then, these AI assets that we have invested in can achieve very positive and robust cash flow. To give you some direct examples, A100 purchased in 2020 or V100 purchased in 2018, even today are still running at full capacity.

[Translator]: Following that 3-year payback period then, these AI assets that we have invested in can achieve very positive and robust cash flow. To give you some direct examples, A100 purchased in 2020 or V100 purchased in 2018, even today are still running at full capacity.

Speaker #5: That three-year payback period, then, these AI assets that we've invested in can achieve very positive and robust cash flow. So to give you some direct examples, an A100 purchased in 2020, or a V100 purchased in 2018, even today are still running at full capacity.

Speaker #6: 同时，我们在提升 AI 产品的毛利率水平和投资回报率上有三个重要的手段。第一是我们可以持续提升 AI 产品的毛利率，比如包括我们现在持续投入推动我们的 SOTA 模型建设，拓展高毛利的 MAS 业务。同时，还可以使用我们更完善的产品组合来提升我们的 AI 2.0 产品或者 AI 相关的软件产品的竞争力，从而提升毛利率水平。我们看到 AI 产品毛利率还在持续提升，本季度也带动了阿里云整体板块的利润率提升 4.4 个百分点，达到 11.6%。这是初步的验证。

Joseph Tsai: 同时我们在提升AI产品的毛利率水平上和投资回报率上有三个重要的手段。第一是我们可以持续提升AI产品的毛利率，比如包括我们现在持续投入推动我们的SOTA模型建设，拓展高毛利的MaaS业务。同时还可以使用我们更完善的产品组合来提升我们的AI IaaS产品或者AI相关的软件产品的竞争力，从而提升毛利率水平。我们看到AI产品的毛利率还在持续提升，本季度已经带动了阿里云整体板块的利润率提升4.4个百分点，来到11.6%。这是初步的验证。

Eddie Wu: [Foreign language].

Eddie Wu: Additionally, we have three means that we can leverage to further enhance gross margin and return on invested capital. First is we can continue to develop state-of-the-art models and enhance gross margin on AI products themselves and continue to expand a higher margin Model-as-a-Service MaaS businesses. We can adapt our product mix across IaaS and across software to achieve higher gross margin on the portfolio as a whole. As a result of improving gross margin, you have already seen an overall increase of 4.4 percentage points in Alibaba Cloud's overall segment profitability, bringing it this quarter to 11.6%. That represents initial validation of that thesis.

[Translator]: Additionally, we have three means that we can leverage to further enhance gross margin and return on invested capital. First is we can continue to develop state-of-the-art models and enhance gross margin on AI products themselves and continue to expand a higher margin Model-as-a-Service MaaS businesses. We can adapt our product mix across IaaS and across software to achieve higher gross margin on the portfolio as a whole. As a result of improving gross margin, you have already seen an overall increase of 4.4 percentage points in Alibaba Cloud's overall segment profitability, bringing it this quarter to 11.6%. That represents initial validation of that thesis.

Speaker #5: We have three means that we can leverage to further enhance gross margin and return on invested capital. First is that we can continue to develop state-of-the-art models and enhance gross margin on AI products themselves, and continue to expand higher-margin model-as-a-service (MaaS) businesses.

Speaker #5: And we can adapt our product mix across IaaS and across software to achieve higher gross margin on the portfolio as a whole. And you know, as a result of improving gross margin, you've already seen an overall increase of 4.4 percentage points in Alibaba Cloud's overall segment profitability, bringing it this quarter to 11.6%.

Speaker #5: So that represents initial validation of that thesis.

Speaker #6: 第二个重要措施是我们的自研芯片，也可以说是在这个过程当中最重要的一个方案。我们平头哥的自研芯片路径覆盖 GPU、CPU 和网络芯片，这是新一代 AI 数据中心最核心的芯片组合。在 AI 数据中心里面，最昂贵的成本就是芯片以及存储。自研芯片是我们长期重要的方向。随着我们平头哥自研芯片未来产能的持续提升，在我们数据中心的自研芯片比例还会持续提升，替代更多商业化采购的芯片。我们知道在现在这个算力紧缺的时代，商业化芯片的毛利率本身就很高，所以自研芯片比例的大幅提升会大幅度提升我们的产品竞争力以及毛利水平。

Joseph Tsai: 第二个重要措施是我们的自研芯片，也可以说是在这个过程当中最重要的一个方案。我们平头哥的自研芯片路径覆盖GPU、CPU和网络芯片，这是新一代AI数据当中最核心的芯片组合。在AI数据中心里面最昂贵的成本就是芯片以及存储。自研芯片是我们长期重要的方向。随着我们平头哥自研芯片未来的产能的持续提升，在我们的数据中心的这种自研芯片的比例还会持续提升，替代我们更多的商业化采购的芯片。我们知道在现在这个算力紧缺的时代，商业化芯片本身它们的毛利率就很高，所以自研芯片的比例大幅提升，会大幅度提升我们的产品竞争力，以及我们的毛利水平。

Eddie Wu: [Foreign language].

Eddie Wu: A very important piece of this is our ability to deploy our own proprietary chips. As you know, our own T-Head proprietary chips span GPUs, CPUs, and networking chips, which are the critical chipsets for AI. In AI data centers, the most expensive components are of course chips and storage. We have a very significant advantage in being able to deploy our own proprietary chips. As we ramp up deployment of our own proprietary chips in our data centers, as they account for an increasing proportion of total chips and replace commercially procured chips, we can expect to see substantially higher gross margin as well as profitability.

[Translator]: A very important piece of this is our ability to deploy our own proprietary chips. As you know, our own T-Head proprietary chips span GPUs, CPUs, and networking chips, which are the critical chipsets for AI. In AI data centers, the most expensive components are of course chips and storage. We have a very significant advantage in being able to deploy our own proprietary chips. As we ramp up deployment of our own proprietary chips in our data centers, as they account for an increasing proportion of total chips and replace commercially procured chips, we can expect to see substantially higher gross margin as well as profitability.

Speaker #5: Our ability to deploy our own proprietary chips is key. As you know, our T-Head proprietary chips span GPUs, CPUs, and networking chips, which are the critical chipsets for AI.

Speaker #5: And in AI data centers, the most expensive components are, of course, chips and storage. So we have a very significant advantage in being able to deploy our own proprietary chips. As we ramp up deployment of our own proprietary chips in our data centers, as they account for an increasing proportion of total chips and replace commercially procured chips, we can expect to see substantially higher gross margin as well as profitability.

Speaker #6: 我们还有第三点也很重要，我们还有多种商业化的手段来提升我们的现金流的使用效率，比如我们和合作伙伴共建 AI 的算力中心，比如我们现在有一些的 AI 的算力合同已经开始采取预付的方式。所以这些的通过商业上的方式也可以大幅提升我们的投资回报率。

Joseph Tsai: 第三点也很重要。我们还有多种商业化的手段来提升我们的现金流的使用效率，比如我们和合作伙伴共建AI的算力中心，比如我们现在有一些AI的算力合同已经开始采取预付的方式，所以这些通过商业上的方式也可以大幅提升我们的投资回报率。

Eddie Wu: [Foreign language].

Speaker #5: Third, and also very importantly, we have means to monetize and achieve better efficiency in the utilization of our own cash flow. These include, for example, co-building data centers with partners, as well as pre-charging and receiving prepayments for compute-based services.

Eddie Wu: Third, and also very importantly, we have means to monetize and get better efficiency of utilization of our own cash flow. These include, for example, co-building data centers with partners, as well as pre-charging and receiving prepayments for compute-based services. These are important ways in which we can further enhance ROIC.

[Translator]: Third, and also very importantly, we have means to monetize and get better efficiency of utilization of our own cash flow. These include, for example, co-building data centers with partners, as well as pre-charging and receiving prepayments for compute-based services. These are important ways in which we can further enhance ROIC.

Speaker #5: So, these are important ways in which we can further enhance ROIC.

Speaker #6: 通过这三条路径，我们可以持续地把 AI CAPEX 的回本周期推向更短的时间，比如推向 2.5 年，甚至接近 2 年。我们我觉得可以给大家算一个简单的框架，如果按我们现在的 AI 产品毛利水平，CAPEX 三年回本的条件下，理论上把我们的帧数控制在 33% 以内，就可以实现正向的现金流。但这现在不是我们的战略选择。由于 AI 还处于整个行业的非常早期阶段，对我们的战略选择，我们是会坚定地投入 CAPEX 的积极的建设去推动业务的高速增长。而后面随着我们的产品毛利率的提升，自研芯片的替代比例的提高，我们的回本周期将进入 2.5 年甚至更短的时候，我们可以看到在追求 40% 以上帧数的同时，还能够就能够维持正向的现金流。这是我们的长期方向。

Joseph Tsai: 通过这三条路径，我们可以持续地把AI CapEx的回本周期推向更短的时间，比如推向2.5年，甚至接近2年。我觉得可以给大家算一个简单的框架，如果按我们现在的AI产品毛利水平，CapEx 3年回本的条件下，理论上把我们的增速控制在33%以内，就可以实现正向的现金流。但这现在不是我们的战略选择。由于AI还处于整个行业的非常早期阶段，对我们的战略选择，我们是会坚定地投入CapEx的积极的建设，去推动业务的高速增长。而后面随着我们的产品毛利率的提升，自研芯片的替代比例的提高，我们的回本周期将进入2.5年甚至更短的时候，我们可以看到，在追求40%以上增速的同时，还能够维持正向的现金流，这是我们的长期方向。

Eddie Wu: [Foreign language].

Speaker #5: So, through these three different methods, we can shorten the payback period for AI CAPEX—for example, to two and a half years, or even two years.

Eddie Wu: Through these three different methods, we can shorten the payback period for AI CapEx, for example, to 2.5 years or even 2 years. We can apply a simple framework to understand this. At our current level of gross margin for AI products, and under the assumption of a 3-year payback period on CapEx, theoretically, keeping our growth rate below 33% would already enable positive cash flow. However, that is not our strategic choice at this time. Given that AI remains in a very early stage, we are committed to aggressively investing in CapEx and proactively scaling up to drive our rapid business expansion. As our product gross margin improves and our proprietary chip substitution rate increases, our payback period will shorten to 2.5 years or even less.

[Translator]: Through these three different methods, we can shorten the payback period for AI CapEx, for example, to 2.5 years or even 2 years. We can apply a simple framework to understand this. At our current level of gross margin for AI products, and under the assumption of a 3-year payback period on CapEx, theoretically, keeping our growth rate below 33% would already enable positive cash flow. However, that is not our strategic choice at this time. Given that AI remains in a very early stage, we are committed to aggressively investing in CapEx and proactively scaling up to drive our rapid business expansion. As our product gross margin improves and our proprietary chip substitution rate increases, our payback period will shorten to 2.5 years or even less.

Speaker #5: And we can apply a simple framework to understand this. At our current level of gross margin for AI products, and under the assumption of a three-year payback period on CAPEX, theoretically, keeping our growth rate below 33% would already enable positive cash flow.

Speaker #5: However, that is not our strategic choice at this time. Given that AI remains at a very early stage, we're committed to aggressively investing in CAPEX and proactively scaling up to drive our rapid business expansion.

Speaker #5: As our product gross margin improves and our proprietary chip substitution rate increases, our payback period will shorten to two and a half years, or even less.

Speaker #5: And so, under those circumstances, while pursuing growth of over 40%, we'll also be able to maintain positive cash flow. So that is our long-term strategic direction.

Eddie Wu: Under those circumstances, while pursuing growth of over 40%, we will also be able to maintain positive cash flow. That is our long-term strategic direction.

[Translator]: Under those circumstances, while pursuing growth of over 40%, we will also be able to maintain positive cash flow. That is our long-term strategic direction.

Speaker #6: 好。

Joseph Tsai: OK.

Speaker #1: Next question please.

Lydia Liu: Next question please.

Speaker #2: Thank you. Your next question comes from Charlene Liu with HSBC. Please go ahead.

Operator: Thank you. Your next question comes from Charlene Liu with HSBC. Please go ahead.

Speaker #3: I'm from HSBC, but thank you very much for this opportunity. Thank you for taking my question. First, can we get an update on the latest developments in Quick Commerce and the reclassification of multiple business lines that are now regrouped under the Alibaba E-Commerce Group?

Charlene Liu: I am from HSBC. Thank you very much for this opportunity. Thank you for taking my question. First, can we get an update on the latest developments in quick commerce and under the reclassification of multiple business lines which are regrouped under the Alibaba E-commerce Business Group? Can you talk about the future strategic focuses of these lines of businesses?

Speaker #3: Can you talk about the future strategic focuses of these lines of businesses? Let me quickly translate the question myself. 非常感谢给到我这个提问的一个机会。我想问一个跟电商相关的问题。首先，我想问一下闪购的进展情况。另外，公司把很多业务进行了梳理，组成了阿里巴巴电商集团。那这些业务未来的各自战略重点是什么呢？谢谢您。 Thank you.

Charlene Liu: Let me quickly translate the question myself。非常感谢，给到我这个提问的一个机会。我想问一个跟电商相关的一个问题。首先我想问一下闪购的进展的一个情况。另外呢，公司把很多个业务进行了梳理，组成了阿里巴巴电商集团，那这些业务未来各自的一些战略重点是什么呢？谢谢您。Thank you。

Charlene Liu: Let me quickly translate the question myself. [Foreign language].

Speaker #2: 好，谢谢你的翻译。我想给大家介绍一下我们新财年我们对这个电商板块进行了重新的梳理。那未来我们会围绕着中国电商即时零售，还有国际电商，全球

Joseph Tsai: 好，谢谢你的翻译。我先给大家介绍一下，我们新财年我们对这个电商板块进行了重新的梳理。那未来我们会围绕着中国电商、即时零售

Joseph Tsai: [Foreign language].

Jiang Fan: 还有国际电商、全球B2B四个核心板块向大家持续同步我们的进展。今天我想先简要分享一下这四个板块的进展跟思考。首先中国电商。国内电商的短期宏观环境还是面临挑战。放眼长期，我们聚焦核心供给，同时希望通过AI提升电商的体验跟整体经营效率。首先在供给方面，从去年开始，淘宝天猫就聚焦对包括品牌商家在内的原创商家进行扶持，同时挖掘优质产业带的白牌供给的潜力。

Jiang Fan: [Foreign language].

Speaker #5: B2B 四个核心板块向大家持续同步我们的进展。那今天我想先简要分享一下这四个板块的进展跟思考。首先，中国电商，国内电商的短期宏观环境还是面临挑战。那放眼长期，我们聚焦核心供给，同时希望通过 AI 提升电商的体验跟整体经营效率。首先在供给方面，从去年开始，淘宝天猫就聚焦对平台，包括品牌商家在内的原创商家进行扶持，同时挖掘优质产业带的白牌供给的潜力。 Okay, thank you very much for the question as well as for the translation. In the new fiscal year, indeed, we've realigned our e-commerce business segments, and moving forward, we'll be updating progress on four core areas: China e-commerce, quick commerce, international e-commerce, and global B2B, or global wholesale.

Eddie Wu: Okay, thank you very much for the question as well as for the translation. In the new fiscal year, indeed we have realigned our e-commerce business segments. Moving forward, we will be updating progress on four core areas: China e-commerce, quick commerce, international e-commerce, and global B2B global wholesale. Let me then briefly share the strategic priorities and key considerations for each of these four segments in the period ahead. Starting with China e-commerce. While the domestic e-commerce landscape faces short term macroeconomic challenges, our long term strategy centers on strengthening core supply capabilities. At the same time, we aim to leverage AI to enhance the overall shopping experience and improve operational efficiency across the board. First, regarding supply, since last year, Taobao and Tmall have focused on supporting original merchants, including branded sellers, while simultaneously unlocking the potential of high quality white label suppliers from key industrial clusters.

[Translator]: Okay, thank you very much for the question as well as for the translation. In the new fiscal year, indeed we have realigned our e-commerce business segments. Moving forward, we will be updating progress on four core areas: China e-commerce, quick commerce, international e-commerce, and global B2B global wholesale. Let me then briefly share the strategic priorities and key considerations for each of these four segments in the period ahead. Starting with China e-commerce. While the domestic e-commerce landscape faces short term macroeconomic challenges, our long term strategy centers on strengthening core supply capabilities. At the same time, we aim to leverage AI to enhance the overall shopping experience and improve operational efficiency across the board. First, regarding supply, since last year, Taobao and Tmall have focused on supporting original merchants, including branded sellers, while simultaneously unlocking the potential of high quality white label suppliers from key industrial clusters.

Speaker #5: Let me then briefly share the strategic priorities and key considerations for each of these four segments in the period ahead. So, starting with China e-commerce: While the domestic e-commerce landscape faces short-term macroeconomic challenges, our long-term strategy centers on strengthening core supply capabilities. At the same time, we aim to leverage AI to enhance the overall shopping experience and improve operational efficiency across the board.

Speaker #5: So first, regarding supply, since last year Taobao and Tmall have focused on supporting original merchants, including branded sellers, while simultaneously unlocking the potential of high-quality white-label suppliers from key industrial clusters.

Speaker #5: 我们会继续加强和头部品牌商的合作关系，帮助品牌客户实现稳定且可持续性的生意发展。天猫依然是品牌商和很多原创商家最核心的经营阵地。同时，我们也会深入产业带，挖掘源头好货，支持更多制造业工厂在平台上开店经营，并利用平台 AI 能力，帮助更多白牌商家进行更加简单、更加高效的托管经营。产业带托管经营模式在平台的交易比例正在持续提升。在刚过去的 618，尽管宏观环境面临一定挑战，从结果上看符合我们的预期，尤其是核心商家的经营结果还是取得了不错的成绩。We will continue to strengthen our partnerships with leading brand merchants, helping them achieve stable and sustainable business growth. Tmall remains the most critical operational hub for both major brands and many original merchants.

Jiang Fan: 我们会继续加强和头部品牌商的合作关系，帮助品牌客户实现稳定且可持续性的生意发展。天猫依然是品牌商跟很多原创商家最核心的经营阵地。同时我们也会深入产业带，挖掘源头好货，支持更多制造业工厂直接在平台上开店经营。也利用平台AI能力，帮助更多白牌商家进行更加简单、更加高效的托管经营。产业带托管经营模式在平台的交易比例在持续提升。在刚过去的618，尽管宏观环境面临一定挑战，从结果上看符合我们的预期，尤其是核心商家的经营结果还是取得了不错的成绩。

Jiang Fan: [Foreign language].

Eddie Wu: We will continue to strengthen our partnerships with leading brand merchants, helping them achieve stable and sustainable business growth. Tmall remains the most critical operational hub for both major brands and many original merchants. At the same time, we are diving deeper into industrial clusters to source high quality products directly from their origins. We are supporting more manufacturing factories and operating directly on our platform and leveraging our platform AI capabilities to enable white label merchants to adopt a simpler and more efficient managed operation model. The share of transactions being generated through that industrial cluster managed model continues to rise steadily. In the past quarter during the recent 618 Shopping Festival, despite certain macroeconomic challenges, the outcomes were aligned with our expectations, and notably, core merchants achieved solid growth.

[Translator]: We will continue to strengthen our partnerships with leading brand merchants, helping them achieve stable and sustainable business growth. Tmall remains the most critical operational hub for both major brands and many original merchants. At the same time, we are diving deeper into industrial clusters to source high quality products directly from their origins. We are supporting more manufacturing factories and operating directly on our platform and leveraging our platform AI capabilities to enable white label merchants to adopt a simpler and more efficient managed operation model. The share of transactions being generated through that industrial cluster managed model continues to rise steadily. In the past quarter during the recent 618 Shopping Festival, despite certain macroeconomic challenges, the outcomes were aligned with our expectations, and notably, core merchants achieved solid growth.

Speaker #5: At the same time, we are diving deeper into industrial clusters to source high-quality products directly from their origins. We are supporting more manufacturing factories in operating directly on our platform, and leveraging our platform's AI capabilities to enable white-label merchants to adopt a simpler and more efficient managed operation model.

Speaker #5: And the share of transactions being generated through that industrial cluster-managed model continues to rise steadily. In the past quarter, during the recent 6.18 shopping festival, despite certain macroeconomic challenges, the outcomes were aligned with our expectations, and notably, core merchants achieved solid growth.

Speaker #5: 同时我们也看到 AI 在电商供需两侧的机会。那么用户侧我们会持续推出更多基于 AI 能力的新体验、新场景，例如多模态搜索、AI 适应等。另一方面，利用 AI 技术提升现有购物场景下的体验跟效率，例如我们看到 AI 对我们的商品推荐带来了非常显著的提升。商家侧我们看到商家已经在经营中非常普遍地使用 AI，我们在经营的各个环节尝试通过 AI 帮助商家提升能力，尤其是数据分析、广告营销、客服等环节。商家可以明显受益。后面我们也会跟千问办公合作，推出更加适配电商场景的 AI 智能体。 The same time we see significant opportunities for AI across both the supply and demand sides of e-commerce.

Jiang Fan: 同时我们也看到AI在电商供需两侧的机会。那么用户侧，我们会持续推出更多基于AI能力的新体验、新场景，例如多模态搜索、AI试衣等。另一方面，利用AI技术提升现有购物场景下的体验跟效率。例如我们看到AI对我们的商品推荐带来了非常显著的提升。商家侧我们看到商家已经在经营中非常普遍地使用AI。我们在经营的各个环节尝试通过AI帮助商家提升能力，尤其是数据分析、广告营销、客服等环节，商家可以明显受益。后面我们也会跟Qwen Office合作，推出更加适配电商场景的AI智能体。

Jiang Fan: [Foreign language].

Eddie Wu: At the same time, we see significant opportunities for AI across both the supply and demand sides of e-commerce. On the consumer side, we will continue to launch new experiences and scenarios powered by AI, such as multimodal search and virtual try ons. Our goal is twofold. First, to use AI technology to enhance the experience and efficiency of existing shopping scenarios. We have already observed that AI has driven significant efficiency gains in our product recommendations. Secondly, to drive new kinds of AI driven interaction. On the merchant side, we observed that merchants are already widely adopting AI in their operations. We are exploring ways to leverage AI across various operational links to boost merchant capabilities, particularly in data analytics, advertising and marketing, and customer service, where merchants can derive clear benefits. Going forward, we will also collaborate with Qwen Office to launch AI agents that are specifically tailored for e-commerce scenarios.

[Translator]: At the same time, we see significant opportunities for AI across both the supply and demand sides of e-commerce. On the consumer side, we will continue to launch new experiences and scenarios powered by AI, such as multimodal search and virtual try ons. Our goal is twofold. First, to use AI technology to enhance the experience and efficiency of existing shopping scenarios. We have already observed that AI has driven significant efficiency gains in our product recommendations. Secondly, to drive new kinds of AI driven interaction. On the merchant side, we observed that merchants are already widely adopting AI in their operations.

Speaker #5: On the consumer side, we will continue to launch new experiences and scenarios powered by AI, such as multimodal search and virtual try-ons. Our goal is twofold.

Speaker #5: First, we aim to use AI technology to enhance the experience and efficiency of existing shopping scenarios, and we've already observed that AI has driven significant efficiency gains in our product recommendations.

Speaker #5: And secondly, to drive new kinds of AI-driven interaction. On the merchant side, we observed that merchants are already widely adopting AI in their operations. We're exploring ways to leverage AI across various operational links to boost merchant capabilities.

[Translator]: We are exploring ways to leverage AI across various operational links to boost merchant capabilities, particularly in data analytics, advertising and marketing, and customer service, where merchants can derive clear benefits. Going forward, we will also collaborate with Qwen Office to launch AI agents that are specifically tailored for e-commerce scenarios.

Speaker #5: Particularly in data analytics, advertising and marketing, and customer service, where merchants can derive clear benefits. And going forward, we'll also collaborate with Quinn Office to launch AI agents that are specifically tailored for e-commerce scenarios.

Speaker #4: 然后回到 700 售的这个问题，那么经过一年多的发展与投入，淘宝闪购的规模跟市场份额都已经发生了实质性的变化。无论是用户心智、供给丰富性、物流体验还是订单规模，都取得了巨大的提升。上个季度我们在用户跟订单规模都保持上涨的前提下，我们实现了优异的大幅度优化。亏损规模显著缩小。在今天这样一个基础上，接下来我们会加速整合盒马、天猫、超市等相关板块，发展非餐饮品类的 700 售，尤其是加速发展前置仓。盒马过去一年加快前置仓的布局，带动了整个交易额的同比加速。

Jiang Fan: 然后回到即时零售的这个问题。经过一年多的发展与投入，淘宝闪购的规模跟市场份额都已经发生了实质性的变化。无论是用户心智、供给丰富性、物流体验还是订单规模都取得了巨大的提升。上个季度我们在用户跟订单规模都保持上涨的前提下，我们实现了优益的大幅度优化，亏损规模显著缩小。在今天这样一个基础上，接下来我们会加速整合盒马、天猫超市等相关板块，发展非餐饮品类的即时零售，尤其是加速发展前置仓。盒马过去一年加快前置仓的布局，带动了整个交易额的同比加速。

Jiang Fan: [Foreing language].

Speaker #5: Next on Quick Commerce: After more than a year of investment and development, Taobao Instant Commerce has undergone substantial changes in scale and market share, with significant improvements across user mind share, supply diversity, logistics experience, and order volume.

Eddie Wu: Next on Quick Commerce. After more than a year of investment and development, Taobao Instant Commerce has undergone substantial changes in scale and in market share, with significant improvements across user mindshare, supply diversity, logistics experience and order volume. Last quarter, while maintaining growth in both users and orders, unit economics UE substantially improved and losses significantly reduced. On that basis, we will accelerate the integration of businesses such as Freshippo and Tmall Supermarket to develop the non-food categories growth within the Quick Commerce business, and will place a particular focus on expanding our front warehouses. Over the past year, Freshippo has accelerated the development of front warehouses, leading to a year-over-year increase in GMV.

[Translator]: Next on Quick Commerce. After more than a year of investment and development, Taobao Instant Commerce has undergone substantial changes in scale and in market share, with significant improvements across user mindshare, supply diversity, logistics experience and order volume. Last quarter, while maintaining growth in both users and orders, unit economics UE substantially improved and losses significantly reduced. On that basis, we will accelerate the integration of businesses such as Freshippo and Tmall Supermarket to develop the non-food categories growth within the Quick Commerce business, and will place a particular focus on expanding our front warehouses. Over the past year, Freshippo has accelerated the development of front warehouses, leading to a year-over-year increase in GMV.

Speaker #5: Last quarter, while maintaining growth in both users and orders, unit economics (UE) substantially improved and losses were significantly reduced. On that basis, we will accelerate the integration of businesses such as Freshippo and Tmall Supermarket to develop non-food category growth within the Quick Commerce business.

Speaker #5: And we'll place a particular focus on expanding our front warehouses. Over the past year, Freshifo has accelerated the development of front warehouses, leading to a year-over-year increase in GMV.

Speaker #4: 同时，闪购也会持续拓展更多品类覆盖，在一些重点品类上持续创新，提升消费者体验。我们认为非餐饮品类的 7-11 售交易额规模将在下个财年内超过餐饮品类，并带动电商大盘很多实物品类。7-11 售板块预计在 2029 财年实现整体盈利。长期来看，我们认为 7-11 售有望贡献平台整体交易额的 30%，成为电商板块的第二增长曲线。

Jiang Fan: 同时，闪购也会持续拓展更多品类覆盖，在一些重点品类上持续创新，提升消费者体验。我们认为非餐饮品类的即时零售交易额规模将在下个财年内超过餐饮品类，会带动电商大盘很多实物品类。即时零售板块预计在FY29实现整体盈利。长期看，我们认为即时零售有望贡献平台整体交易额的30%，成为电商板块的第二曲线。

Jiang Fan: [Foreign language].

Speaker #5: Meanwhile, Quick Commerce will continue to expand its category coverage and innovate in key areas to enhance the consumer experience. We expect the transaction volume of Quick Commerce for non-food categories to surpass that of food categories within the next fiscal year.

Eddie Wu: Meanwhile, Quick Commerce will continue to expand its category coverage and innovate in key areas to enhance the consumer experience. We expect the transaction volume of Quick Commerce for non-food categories to surpass that of food categories within the next fiscal year, driving growth in many different physical goods categories across the overall e-commerce business. The Quick Commerce business is expected to achieve overall profitability in FY29. In the long term, we believe it has the potential to contribute 30% of the platform's total GMV, becoming the second growth curve for our e-commerce business.

[Translator]: Meanwhile, Quick Commerce will continue to expand its category coverage and innovate in key areas to enhance the consumer experience. We expect the transaction volume of Quick Commerce for non-food categories to surpass that of food categories within the next fiscal year, driving growth in many different physical goods categories across the overall e-commerce business. The Quick Commerce business is expected to achieve overall profitability in FY29. In the long term, we believe it has the potential to contribute 30% of the platform's total GMV, becoming the second growth curve for our e-commerce business.

Speaker #5: We are driving growth in many different physical goods categories across the overall e-commerce business. The Quick Commerce business is expected to achieve overall profitability in fiscal year 2029.

Speaker #5: In the long term, we believe it has the potential to contribute 30% of the platform's total GMV, becoming the second growth curve for our e-commerce business.

Speaker #4: 然后关于国际电商板块，短期来看我们的海外电商确实受到了国际税收政策和地缘环境的影响。面临一定的这样的一个压力，但我们也看到，尽管市场环境很复杂，跨境电商依然保持交易规模上涨的同时，盈利水平也有显著提升。不管是交易规模还是盈利能力，我们都认为跨境业务具备长期潜力。另外我们在土耳其、中东等区域的本地电商平台也发展很快，东南亚等市场的经营效率也在持续改善。

Jiang Fan: 然后关于国际电商板块，短期来看，我们的海外电商确实受到了国际税收政策和地缘环境的影响，面临一定的压力。但我们也看到，尽管市场环境很复杂，跨境电商依然保持交易规模上涨的同时，盈利水平也有显著提升。不管是交易规模还是盈利能力，我们都认为跨境业务具备长期潜力。另外，我们在土耳其、中东等区域的本地电商平台也发展很快，东南亚等市场的经营效率也在持续改善。

Jiang Fan: [Foreign language].

Speaker #5: Third is international e-commerce. In the short term, our international e-commerce business has indeed been affected by tariff policies and the geopolitical environment, pressuring growth.

Eddie Wu: Third is international e-commerce. In the short term, our international e-commerce business has indeed been affected by tariff policies and the geopolitical environment pressuring growth. That said, despite the complex market environment, our cross-border business has delivered significant improvement in profitability while maintaining growth in transaction volume. In terms of both transaction scale and profitability, we believe the cross-border business holds long term growth potential. In addition, our local e-commerce platforms in international markets such as Turkey and the Middle East are growing rapidly, and operating efficiency in markets such as Southeast Asia continues to improve.

[Translator]: Third is international e-commerce. In the short term, our international e-commerce business has indeed been affected by tariff policies and the geopolitical environment pressuring growth. That said, despite the complex market environment, our cross-border business has delivered significant improvement in profitability while maintaining growth in transaction volume. In terms of both transaction scale and profitability, we believe the cross-border business holds long term growth potential. In addition, our local e-commerce platforms in international markets such as Turkey and the Middle East are growing rapidly, and operating efficiency in markets such as Southeast Asia continues to improve.

Speaker #5: That said, despite the complex market environment, our cross-border business has delivered significant improvement in profitability while maintaining growth in transaction volume. In terms of both transaction scale and profitability, we believe the cross-border business holds long-term growth potential.

Speaker #5: In addition, our local e-commerce platforms in international markets, such as Turkey and the Middle East, are growing rapidly, and operating efficiency in markets such as Southeast Asia continues to improve.

Speaker #4: 最后，关于全球的 B2B 业务。B2B 业务包括我们的 1688 平台和 Alibaba.com。过去 20 年，这项业务一直在持续发展。我们看到 AI 技术会给 B2B 交易平台带来非常大的变化，甚至可能从根本上改变原有的商业模式。尤其是 agent 代理模式，会在 B2B 交易中扮演越来越重要的角色。我们面向跨境电商商家推出的 AI 智能体 XU Work，上线后很快就有 5 万付费商家在使用。AI 正在全面改变 B2B 商家，尤其是跨境商家做生意的方式。我们认为，基于过去 20 多年在这个领域的积累，我们有机会在 AI 时代的 B2B 和跨境贸易领域，创造出全新的业务模式和商业机会。

Jiang Fan: 最后关于全球的B2B业务。B2B业务包括我们的1688.com平台跟Alibaba.com。过去20年这个业务一直在持续的发展，我们看到AI技术会给B2B交易平台带来非常大的变化，甚至可能从根本上改变原来的商业模式，尤其是agent代理模式，会在B2B交易中扮演越来越重要的角色。我们面向跨境电商商家推出的AI智能体Axio Work，上线后很快就拥有了5万的付费商家在使用。AI正在全面改变B2B商家，尤其是跨境商家做生意的方式。我们认为基于过去20多年在这个领域的积累，我们有机会在AI时代的B2B跟跨境贸易领域创造出全新的业务模式跟商业机会。

Jiang Fan: [Foreign language].

Speaker #5: And fourth is global B2B. Our B2B businesses, including the 1688 and Alibaba.com platforms, have grown consistently over the past two decades, and we see that AI technology will bring profound changes to our B2B platforms.

Eddie Wu: Fourth is global B2B. Our B2B businesses, including the 1688.com and Alibaba.com platforms, have grown consistently over the past two decades. We see that AI technology will bring profound changes to our B2B platforms and may even fundamentally reshape existing business models. In particular, the agentic model will play an increasingly important role in B2B transactions. We have launched Axio Work, which is an AI agent for cross-border merchants, and it had already attracted over 50,000 paying merchants shortly after its launch. AI is comprehensively transforming the way that B2B merchants do business, especially cross-border merchants. We believe that building on our two decades of know-how in this field, we have the opportunity to create entirely new business models and commercial opportunities in B2B and in cross-border trade in the AI era.

[Translator]: Fourth is global B2B. Our B2B businesses, including the 1688.com and Alibaba.com platforms, have grown consistently over the past two decades. We see that AI technology will bring profound changes to our B2B platforms and may even fundamentally reshape existing business models. In particular, the agentic model will play an increasingly important role in B2B transactions. We have launched Axio Work, which is an AI agent for cross-border merchants, and it had already attracted over 50,000 paying merchants shortly after its launch. AI is comprehensively transforming the way that B2B merchants do business, especially cross-border merchants. We believe that building on our two decades of know-how in this field, we have the opportunity to create entirely new business models and commercial opportunities in B2B and in cross-border trade in the AI era.

Speaker #5: And may even fundamentally reshape existing business models. In particular, the agentic model will play an increasingly important role in B2B transactions. We've launched Axio Work, which is an AI agent for cross-border merchants, and it has already attracted over 50,000 paying merchants shortly after its launch.

Speaker #5: AI is comprehensively transforming the way that B2B merchants do business, especially cross-border merchants. We believe that building on our two years of know-how in this two decades of know-how in this field, we have the opportunity to create entirely new business models and commercial opportunities in B2B and in cross-border trade in the AI era.

Speaker #4: 总体来看，过去几年我们的我们在电商板块的几个分别几个领域完成了阶段性的布局。接下来我们希望继续发挥我们从供给协同到 AI 技术的优势，让各个业务在 AI 时代释放更多的潜力。同时也实现更加多元化的收入利润结构，推动整个板块更加稳健的发展。

Joseph Tsai: 总体来看，过去几年我们在电商板块的分别几个领域完成了阶段性的布局。接下来我们希望继续发挥我们从供给协同到AI技术的优势，让各个业务在AI时代释放更多的潜力，同时也实现更加多元化的收入利润结构，推动整个板块更加稳健的发展。

Joseph Tsai: [Foreign language].

Speaker #5: Overall, over the past few years, we have completed new strategic positioning for our e-commerce businesses across several key areas. Going forward, we aim to continue leveraging our strengths.

Eddie Wu: Overall, over the past few years, we have completed new strategic positioning for our e-commerce businesses across several key areas. Going forward, we aim to continue leveraging our strengths from supply chain synergies to AI technology to unlock greater growth potential for the e-commerce segment in the AI era, while building a more diversified revenue and profit structure to drive steadier development of the overall segment.

[Translator]: Overall, over the past few years, we have completed new strategic positioning for our e-commerce businesses across several key areas. Going forward, we aim to continue leveraging our strengths from supply chain synergies to AI technology to unlock greater growth potential for the e-commerce segment in the AI era, while building a more diversified revenue and profit structure to drive steadier development of the overall segment.

Speaker #5: From supply chain synergies to AI technology, we aim to unlock greater growth potential for the e-commerce segment in the AI era, while building a more diversified revenue and profit structure to drive steadier development of the overall segment.

Speaker #3: I'll pause to let us go to the next question. Thank you. Your next question comes from Yangbai with CICC. Please go ahead.

Lydia Liu: Operator, let's go to the next question.

Operator: Thank you. Your next question comes from Yang Bai with CICC. Please go ahead.

Speaker #2: 谢谢。管理层好。我的问题是关于云 AI 的业务。我们观察到阿里云的收入增速逐季提升，本季度已经来到了 45%。那么公司此前其实也提出过未来 5 年外部云收入突破千亿美元的长期目标，这次也提出了未来几个季度仍会加速。那么我想请教两点。第一就是如果展望未来几个季度，云业务的增长节奏支撑云计算进一步加速增长的核心驱动因素是什么？第二就是当前其实行业还是处于一个算力供给瓶颈的阶段，虽然管理层刚才也提到可能在 2030 年前这个供需格局都必会有变化，但也想请教一下，如果是站在一个更长期维度去看，云业务长期增长的核心驱动武器都有哪些？是否会和短期有所不同？谢谢。

Yang Bai: 谢谢。管理层好，我的问题是关于云AI的业务。我们观察到阿里云的收入增速逐季提升，本季度已经来到了45%。公司此前其实也提出过未来五年外部云收入突破千亿美元的长期目标，这次也提出了未来几个季度仍会加速。那么我想请教两点。第一，如果展望未来几个季度云业务的增长节奏，支撑云计算进一步加速增长的核心驱动因素是什么？第二，当前其实行业还是处于一个算力供给偏紧的阶段，虽然管理层刚才也提到可能在2030年前这个供需格局都必会有变化。但也想请教一下，如果是站在一个更长期维度去看云业务长期增长的核心驱动器都有哪些？是否会和短期有所不同？谢谢。

Yang Bai: [Foreign language].

Speaker #5: Thank you. My question is about the cloud and AI business. We've seen that Alibaba Cloud's revenue growth has been accelerating quarter by quarter, reaching 45% this quarter.

Eddie Wu: Thank you. My question is about the Cloud and AI business. We have seen that Alibaba Cloud's revenue growth has been accelerating quarter by quarter, reaching 45% this quarter. We know the company has previously set a long-term goal of exceeding USD 100 billion in external cloud revenue over the next five years. You have also now indicated that growth will remain on an accelerated trajectory in the quarters ahead. So I would like to ask two questions. First, looking ahead to the coming quarters, what do you anticipate being the pace of growth in the cloud business? What are the core drivers underpinning the continued acceleration of cloud computing growth? Secondly, as you have mentioned, the industry is now in a phase of relatively tight capacity in terms of supply of compute. You just mentioned that demand dynamic may shift around 2030.

[Translator]: Thank you. My question is about the Cloud and AI business. We have seen that Alibaba Cloud's revenue growth has been accelerating quarter by quarter, reaching 45% this quarter. We know the company has previously set a long-term goal of exceeding USD 100 billion in external cloud revenue over the next five years. You have also now indicated that growth will remain on an accelerated trajectory in the quarters ahead. So I would like to ask two questions. First, looking ahead to the coming quarters, what do you anticipate being the pace of growth in the cloud business? What are the core drivers underpinning the continued acceleration of cloud computing growth? Secondly, as you have mentioned, the industry is now in a phase of relatively tight capacity in terms of supply of compute. You just mentioned that demand dynamic may shift around 2030.

Speaker #5: We know the company has previously set a long-term goal of exceeding $100 billion in external cloud revenue over the next five years.

Speaker #5: And you've also now indicated that growth will remain on an accelerated trajectory in the quarters ahead. So I'd like to ask two questions. First, looking ahead to the coming quarters, what do you anticipate being the pace of growth in the cloud business?

Speaker #5: What are the core drivers underpinning the continued acceleration of cloud computing growth? And then, secondly, as you've mentioned, the industry is now in a phase of relatively tight capacity in terms of supply of compute.

Speaker #5: And you just mentioned that the supply-demand dynamic may shift around 2030. So I'd like to ask, from an even longer-term perspective, what are the fundamental growth drivers for the cloud business?

Eddie Wu: I would like to ask from an even longer-term perspective, what are the fundamental growth drivers for the cloud business? Do they differ from those in the short term? Thank you.

[Translator]: I would like to ask from an even longer-term perspective, what are the fundamental growth drivers for the cloud business? Do they differ from those in the short term? Thank you.

Speaker #5: And do they differ from those in the short term? Thank you.

Speaker #4: 好。谢谢你的问题。我觉得这个问题我可以稍微展开一点，分三个部分来讲吧。第一讲一下就是我们的现在的业务的现状和数据。然后在后面再来讲一下我们觉得驱动我们的 AI 相关的业务的增长的动能。最后再来讲一下从我们的现在的分析来看，长期的一个远期展望吧。那第一部分我先来讲一下就是我们的现在的现状和数据。我们看到就是 AI 加云的外部收入已经持续 9 个季度加速增长。那本季度的已经持续加速到 45%。我们看到客户的需求强劲，而我们的供给相对别的云厂商来说也具备非常强的优势。所以未来几个季度我们判断收入还会收入增速还会持续加速。我们看到本季度 AI 相关的产品，本季度的收入来到 124 亿元人民币，对应年化我们可以换算的约 73 亿美元。那在我们现在的数据的业务预测情况下，我们在下个季度的 AI 产品的年化收入将接近 100 亿美元。所以可以看到我们的增速还是还是非常之高的。同时我们也判断未来几个季度我们的 EBITDA 利润率会逐季进行会有一个每个季度会有都会有一些逐步的提升。那所以还有还有我们对于我们的云业务相关相当重要的我们的 MAS 业务在本季度的 AI 需求的增长，以及我们的推理效率的提升，共同推动下那我们本季度的最新的 MAS 业务的 ARR 现在也已经突破了 160 亿元人民币。哦不对，我稍微补充一下，应该是 8 月份最新的这个数据已经突破了 160 亿元人民币。

Joseph Tsai: 好，谢谢你的问题。我觉得这个问题我可以稍微展开一点，分三个部分来讲。第一，讲一下我们现在的业务的现状和数据，然后在后面再来讲一下我们觉得驱动我们的AI相关的业务的增长的动能。最后再来讲一下从我们现在的分析来看，长期的远期展望。第一部分我先来讲一下我们的现在的现状和数据。我们看到AI加云的外部收入已经持续9个季度加速增长。本季度的已经持续加速到45%。我们看到客户的需求强劲，而我们的供给相对别的云厂商来说也具备非常强的优势。所以未来几个季度我们判断收入增速还会持续加速。我们看到本季度AI相关的产品，本季度的收入来到124亿元人民币，对应年化我们可以换算得约$73亿。在我们现在的数据的业务预测情况下，我们在下个季度的AI产品的年化收入将接近$100亿。所以可以看到我们的增速还是非常之高的。同时我们也判断未来几个季度我们的EBITA利润率每个季度都会有一些逐步的提升。还有对我们的云业务相当重要的我们的MaaS业务，在本季度的AI需求的增长以及我们的推理效率的提升共同推动下，我们本季度最新的MaaS业务的ARR现在也已经突破了160亿元人民币。我稍微补充一下，应该是8月份最新的这个数据已经突破了160亿元人民币。

Eddie Wu: [Foreign language].

Speaker #5: Thank you for the question. I think I can expand on this in three different areas. I can start by looking at our current business and the relevant data.

Eddie Wu: Thank you for the question. I think I can expand on this in three different areas. I can start by looking at our current business and the relevant data. Secondly, I can discuss the drivers for growth.

[Translator]: Thank you for the question. I think I can expand on this in three different areas. I can start by looking at our current business and the relevant data. Secondly, I can discuss the drivers for growth.

Speaker #5: Secondly, I can discuss the drivers for growth. And then, thirdly, I can share with you our long-term perspective based on that analysis. So let me begin with the first part: covering our current business and the key metrics.

Eddie Wu: Thirdly, I can share with you our long-term perspective based on that analysis. Let me begin with the first part covering our current business and the key metrics. As you have seen, external revenue for the AI and Cloud segment has been accelerating now for nine consecutive quarters. In this last quarter, growth has already accelerated to 45%. We are seeing very strong customer demand, and our offerings boast a distinct competitive advantage compared to those of other cloud providers. As a result, we expect revenue growth to continue accelerating over the coming quarters. We have observed that AI-related products generated CNY 12.4 billion in revenue this quarter. If we convert that into an annualized US dollar figure, that works out to $7.3 billion in annual revenue. Looking ahead to the next quarter, our own forecast is that the same annualized revenue for AI quarters next quarter will approach $10 billion. Our growth rate remains exceptionally strong. At the same time, we also expect our EBITDA margin to improve quarter by quarter sequentially over the next few quarters. Additionally, something very important in respect of the cloud business is growth in demand for MaaS. We have seen very significant growth in demand for MaaS this quarter, coupled with ongoing improvement in inference efficiency. The ARR of our MaaS business has now surpassed CNY 16 billion. Actually, let me clarify, that is the latest data as of August, it has already surpassed CNY 16 billion.

[Translator]: Thirdly, I can share with you our long-term perspective based on that analysis. Let me begin with the first part covering our current business and the key metrics. As you have seen, external revenue for the AI and Cloud segment has been accelerating now for nine consecutive quarters. In this last quarter, growth has already accelerated to 45%. We are seeing very strong customer demand, and our offerings boast a distinct competitive advantage compared to those of other cloud providers. As a result, we expect revenue growth to continue accelerating over the coming quarters.

Speaker #5: So as you've seen, external revenue for the AI and cloud segment has been accelerating now for nine consecutive quarters. And in this last quarter, growth has already accelerated to 45%.

Speaker #5: We're seeing very strong customer demand, and our offerings boast a distinct competitive advantage compared to those of other cloud providers. As a result, we expect revenue growth to continue accelerating over the coming quarters.

[Translator]: We have observed that AI-related products generated CNY 12.4 billion in revenue this quarter. If we convert that into an annualized US dollar figure, that works out to $7.3 billion in annual revenue. Looking ahead to the next quarter, our own forecast is that the same annualized revenue for AI quarters next quarter will approach $10 billion. Our growth rate remains exceptionally strong. At the same time, we also expect our EBITDA margin to improve quarter by quarter sequentially over the next few quarters. Additionally, something very important in respect of the cloud business is growth in demand for MaaS. We have seen very significant growth in demand for MaaS this quarter, coupled with ongoing improvement in inference efficiency. The ARR of our MaaS business has now surpassed CNY 16 billion. Actually, let me clarify, that is the latest data as of August, it has already surpassed CNY 16 billion.

Speaker #5: We've observed that AI related products generated 12.4 billion RMB in revenue this quarter. And so if we convert that into an annualized US dollar figure, that works out to 7.3 billion US dollars in annual revenue.

Speaker #5: Looking ahead to the next quarter, our own forecast is that that same annualized revenue for AI quarters next quarter will approach $10 billion US dollars.

Speaker #5: So our growth rate remains exceptionally strong. At the same time, we also expect our EBITDA margin to improve sequentially, quarter by quarter, over the next few quarters.

Speaker #5: Additionally, something very important with respect to the cloud business is the growth in demand for MAS. We've seen very significant growth in demand for MAS this quarter, coupled with ongoing improvement in inference efficiencies.

Speaker #5: So the ARR of our MAS business has now surpassed RMB 16 billion. Actually, let me clarify—that's the latest data as of August.

Speaker #5: It has already surpassed RMB 16 billion.

Speaker #4: 好，后面我来解释一下我们的商业模式的增长动能。我觉得首先还是要说一下阿里巴巴在 AI 上面的投入模式，和单一的 AI 公司有最大的一个区别。我们是在 AI 的全栈技术上进行饱和式的投入，尤其是在芯片、AI 云基础设施和模型侧的饱和投入，保证了我们在这三个最重要的技术层面都处于行业的领先地位。而且我们判断 AI 行业的技术发展还在早期，在不同的技术发展阶段，AI 行业的核心商业价值会在芯片、云、模型和应用等不同层次之间流动。而我们全栈式的投入可以保障我们具备最佳的服务能力和最好的性价比，也使得我们在未来行业技术发展的不同阶段都能够保持竞争力和长期的增长动能。

Joseph Tsai: 好，后面我来解释一下我们的商业模式的增长动能。我觉得首先还是要说一下，阿里巴巴在AI上面的这个投入模式和单一的AI公司有最大的一个区别。我们是在AI的full stack技术上进行饱和式的投入，尤其是在芯片、AI云基础设施和模型侧的饱和投入，保证了我们在这三个最重要的技术层面都处于行业的领先地位。而且我们判断AI行业的技术发展还在早期，在不同的技术发展阶段，AI行业的核心商业价值会在芯片、云、模型和应用等不同层次之间流动，而我们全栈式的投入可以保证我们具备最佳的服务能力和最好的性价比，也使得我们在未来行业技术发展的不同阶段都能够保持竞争力和长期的增长动能。

Eddie Wu: [Foreign language].

Speaker #5: Uh, next let me expand on the growth drivers within our business model. So it's important to understand that Alibaba's investment model for AI is fundamentally different from that of pure-play AI companies.

Eddie Wu: Next, let me expand on the growth drivers within our business model. It is important to understand that Alibaba's investment model for AI is fundamentally different from that of pure play AI companies. We are pursuing an intensive strategy across the full stack, including chips, including AI cloud infrastructure, and including models. We maintain a leading position in the industry across all three of those most critical domains. Moreover, we believe that the development of AI and technology across the industry is still in its early stages. Looking forward at different stages of technological development, the core commercial value within the AI industry may shift across different layers, including chips, cloud computing models, and applications. Our full stack investments ensure that we can deliver optimal service capabilities and the best value for money, positioning us favorably in the industry going forward and ensuring that within each stage of technological development, it is possible for us to maintain competitiveness and sustained growth momentum.

[Translator]: Next, let me expand on the growth drivers within our business model. It is important to understand that Alibaba's investment model for AI is fundamentally different from that of pure play AI companies. We are pursuing an intensive strategy across the full stack, including chips, including AI cloud infrastructure, and including models. We maintain a leading position in the industry across all three of those most critical domains.

Speaker #5: We are pursuing an intensive strategy across the full stack, including chips, AI cloud infrastructure, and models. We maintain a leading position in the industry across all three of these most critical domains.

[Translator]: Moreover, we believe that the development of AI and technology across the industry is still in its early stages. Looking forward at different stages of technological development, the core commercial value within the AI industry may shift across different layers, including chips, cloud computing models, and applications. Our full stack investments ensure that we can deliver optimal service capabilities and the best value for money, positioning us favorably in the industry going forward and ensuring that within each stage of technological development, it is possible for us to maintain competitiveness and sustained growth momentum.

Speaker #5: Moreover, we believe that the development of AI and technology across the industry is still in its early stages. Looking forward at different stages of technological development, the core commercial value within the AI industry may shift across different layers, including chips, cloud computing, models, and applications.

Speaker #5: Our full stack investments ensure that we can deliver optimal service capabilities and the best value for money, positioning us favorably in the industry going forward.

Speaker #5: And ensuring that within each stage of technological development, it's possible for us to maintain competitiveness and sustained growth momentum.

Speaker #4: 好，后面我再来讲一下我们觉得在最近一两年的一个短期的、最重要的增长动能。我觉得从 2025 年底开始爆发的大规模商业化推理服务，已经彻底改变了 AI 云的商业模式。刚才我已经提到了，算力才是 AI 营收能力的核心资产。现在所有的 AI 营收模式都是围绕着 AI 算力所展开，而算力紧缺现在又是全行业的中期共识。同时，由于 MAS 推理服务厂商的高毛利，使得 AI 算力不再是原来意义上的成本中心，而是成为与收入正相关的生产资料。所以行业内高定价的算力供不应求，推动了各场景下，不同的场景他们都需要使用 GPU，但是不同场景下他们的定价模型也开始越来越趋近于行业最高毛利的变现方式，共同推动了几乎所有 GPU 相关产品的定价模型。而阿里巴巴同时具备全模态的模型能力，我们的大部分模型能力都处于行业前沿的一线水平，也使得我们在算力的价值实现上具备优势，使得我们在算力定价上有一个非常强的锚点。阿里云具备算力的差异化定价能力。所以我们看到，在旺盛的需求以及算力的商业价值正在被市场重新定价的背景下，我们能够以更健康的价格去签新的合同，客户老合同的续约也会随着新的市场需求，发生定价模式的变化。所以我们看到，阿里云的盈利能力在今年开始都处于一个显著的提升过程当中。

Joseph Tsai: 后面我再来讲一下，我们觉得在最近一两年的一个短期的最重要的增长动能，我觉得从2025年底开始爆发的大规模的商业化推理服务，已经彻底改变了AI云的商业模式。刚才我已经提到了，算力才是AI营收能力的核心资产，现在所有的AI营收模式都是围绕着AI算力所展开，而算力紧缺现在又是全行业的中期共识。同时，由于MaaS推理服务厂商的高毛利，使得AI算力不再是一个原来意义上的成本中心，而是成为与收入正相关的生产资料。所以行业内高定价的算力供不应求，推动了各场景下，不同的场景下他们都需要使用GPU，但是不同场景下，他们的定价模型就开始越来越趋近于行业最高毛利的变现方式，共同推动了几乎所有GPU相关产品的定价模型。而阿里巴巴同时具备全模态的模型能力，我们的大部分模型能力都处于行业前沿的一线水平，也使得我们在算力的价值实现上具备优势，使得我们在我们的算力定价上有一个非常强的锚点。在阿里云具备算力的差异化定价能力。所以我们看到在旺盛的需求以及算力的商业价值正在被市场重新定价，而我们也能够以更健康的价格去签新的合同，以及包括客户老合同的续约，都是随着新的市场需求在发生定价模式的变化。所以我们看到阿里云的盈利能力在今年开始都在处于一个显著的提升过程当中。

Eddie Wu: [Foreign language].

Speaker #5: 呃，next let me look ahead to what we think is going to be the most important growth driver over the next one to two years in the short term.

Eddie Wu: Next, let me look ahead to what we think is going to be the most important growth driver over the next one to two years in the short term. We have seen exponential demand for commercial inference services as of the end of 2025. This exponential growth in demand for inference has marked a fundamental shift in the model whereby compute has now become the core asset driving AI revenue. Today, all AI-related revenue models are centered on AI compute. At the same time, there is a consensus across the industry, as I mentioned, that compute will remain in shortage of supply for some time to come. At the same time, the higher gross margins of mass inference services have also made a major difference.

[Translator]: Next, let me look ahead to what we think is going to be the most important growth driver over the next one to two years in the short term. We have seen exponential demand for commercial inference services as of the end of 2025. This exponential growth in demand for inference has marked a fundamental shift in the model whereby compute has now become the core asset driving AI revenue. Today, all AI-related revenue models are centered on AI compute. At the same time, there is a consensus across the industry, as I mentioned, that compute will remain in shortage of supply for some time to come. At the same time, the higher gross margins of mass inference services have also made a major difference.

Speaker #5: So, we've seen exponential demand for commercial inference services as of the end of 2025. This exponential growth in demand for inference has marked a fundamental shift in the model, whereby compute has now become the core asset driving AI revenue. Today, all AI-related revenue models are centered on AI.

Speaker #5: Compute. And at the same time, there's a consensus across the industry, as I mentioned, that compute will remain in shortage of supply for some time to come.

Speaker #5: At the same time, the higher gross margins of MAS inference services have also made a major difference. If compute was once a cost center, traditionally, compute has now been transformed into a core productive asset whose value generation is positively correlated with revenue.

Eddie Wu: If compute was once a cost center, traditionally, compute has now been transformed into a core productive asset whose value generation is positively correlated with revenue. High-priced computing power remains in short supply across the industry, precisely at a time where you have widespread adoption of GPUs across diverse use cases. Pricing models are tending to converge on the most margin generative monetization approaches. This is driving the pricing models for nearly all GPU-related products. Moreover, Alibaba boasts comprehensive multimodal model capabilities. Our models are at the state-of-the-art level within the industry, giving us a distinct advantage in realizing the value of that compute power and providing a robust anchor for our pricing strategy. When it comes time to price for new customers or to re-sign contracts with existing customers as they renew, we can adopt healthier pricing models.

[Translator]: If compute was once a cost center, traditionally, compute has now been transformed into a core productive asset whose value generation is positively correlated with revenue. High-priced computing power remains in short supply across the industry, precisely at a time where you have widespread adoption of GPUs across diverse use cases. Pricing models are tending to converge on the most margin generative monetization approaches. This is driving the pricing models for nearly all GPU-related products. Moreover, Alibaba boasts comprehensive multimodal model capabilities. Our models are at the state-of-the-art level within the industry, giving us a distinct advantage in realizing the value of that compute power and providing a robust anchor for our pricing strategy. When it comes time to price for new customers or to re-sign contracts with existing customers as they renew, we can adopt healthier pricing models.

Speaker #5: So, high-priced computing power remains in short supply across the industry, precisely at a time when you have widespread adoption of GPUs across diverse use cases.

Speaker #5: So pricing models are tending to converge on the most high margin the most margin generative monetization approaches. So this is driving the pricing models for nearly all GPU related products.

Speaker #5: Moreover, Alibaba boasts comprehensive multimodal model capabilities. Our models are at the state-of-the-art level within the industry, giving us a distinct advantage in realizing the value of that compute power and providing a robust anchor for our pricing strategy.

Speaker #5: So when it comes time to price for new customers, or to re-sign contracts with existing customers as they renew, we can adopt healthier pricing models.

Speaker #5: And so, we expect to see this as a very positive short-term driver for improving margin in the coming year and beyond.

Eddie Wu: We expect to see this as a very positive short-term driver for improving margin in the coming year plus.

[Translator]: We expect to see this as a very positive short-term driver for improving margin in the coming year plus.

Speaker #4: 同时我再来讲一下，就是 AI 云的商业模式长期的规模效应和网络效应，其实是一个会带动长期增长动能的因素。其实前两年行业投资人一直在问 AI 的超级应用是什么，但其实我们认为 AI 最大的超级应用就是以 AI 算力为核心的 AI 云平台。我们看到长期来看，大部分企业核心的 AI 工作负载都需要全站的 AI 云来提供服务，比如大规模的训练、大规模的推理、定制化的推理软件、企业 agent 的开发与运营，这些都需要在一个全站式的云平台上来提供，覆盖 GPU、CPU、存储、数据库和虚拟化，包括 harness 工具等全面的软件云端基础服务。所以，AI 云就像是一个超级城市，训练、推理、企业系统以及 AI agent 就像是这个城市的居民。持续迭代提升全站的 AI 云服务，就像城市的基础设施，源源不断地吸引更多新居民，并提升老居民的留存率。所以我们长期来看，AI 云平台的规模效应和网络效应可以长期推动我们的 AI 业务持续增长。

Joseph Tsai: 我再来讲一下，AI云的商业模式，长期的规模效应和网络效应其实是一个长期的增长动能。其实前两年行业投资人一直在问AI的超级应用是什么？但其实我们认为AI最大的超级应用就是以AI算力为核心的AI云平台。我们看到长期来看，大部分企业的核心的AI工作负载都需要全栈的AI云来提供服务，比如大规模的训练、大规模的推理、定制化的推理软件、企业agent的开发与运营，这些都需要在一个全栈式的云平台来提供覆盖GPU、CPU、存储、数据库和虚拟化，包括harness工具等全面的云端的技术服务。所以AI云就像是一个超级城市，训练推理企业系统以及AI agent就像是这个城市的居民，持续迭代提升全栈的AI云服务就像城市的基础设施，源源不断地吸引更多的新居民，并在提升老居民的留存率。所以我们长期来看，AI云平台的规模效应和网络效应可以长期地推动我们的AI业务长期的增长。

Eddie Wu: [Foreign language]

Speaker #5: 呃，next let me talk about the scale effects and networking effects which are very important long term growth drivers in AI cloud. You know, for the past couple of years a lot of people have asked what is the the super app for AI and the answer to that is that the the real super application is compute cloud based AI compute.

Eddie Wu: Next, let me talk about the scale effects and networking effects, which are very important long-term growth drivers in AI cloud. For the past couple of years, a lot of people have asked, "What is the super app for AI?" The answer to that is that the real super application is cloud-based AI compute, because all of these different workloads need to run on a full stack of AI cloud compute, including training, inferencing, AI software, and agents requiring GPUs, CPUs, storage, databases, virtualization, as well as harness tools among others. AI cloud is like a super city in which workload is the residents and continually iterating full stack AI cloud services are the urban infrastructure, which in turn attracts more new residents and enhances the stickiness of the existing residents. This is where you see an extremely powerful network effect and scale effect.

[Translator]: Next, let me talk about the scale effects and networking effects, which are very important long-term growth drivers in AI cloud. For the past couple of years, a lot of people have asked, "What is the super app for AI?" The answer to that is that the real super application is cloud-based AI compute, because all of these different workloads need to run on a full stack of AI cloud compute, including training, inferencing, AI software, and agents requiring GPUs, CPUs, storage, databases, virtualization, as well as harness tools among others. AI cloud is like a super city in which workload is the residents and continually iterating full stack AI cloud services are the urban infrastructure, which in turn attracts more new residents and enhances the stickiness of the existing residents. This is where you see an extremely powerful network effect and scale effect.

Speaker #5: Because all of these different workloads need to run on a full stack of AI cloud compute, including training, inferencing, AI software and agents requiring GPUs, CPUs, storage, databases, virtualization, as well as harness tools, among others.

Speaker #5: So, AI cloud is like a supercity in which workload is the resident, and continually iterating full-stack AI cloud services are the urban infrastructure, which in turn attracts more new residents and enhances the stickiness of the existing residents.

Speaker #5: So this is where you see an extremely powerful network effect and scale effect.

Speaker #4: 因此鉴于我们拥有亚洲云厂商里最多的数据中心具备最强的规模效应，同时我们自研的平头哥 AI 芯片的规模化部署扩大，避免了外购高端的商业化 GPU 的高额溢价，对毛利的侵蚀，同时由于我们自研模型的行业 SOTA 的能力具备极高的算力定价能力，因此我们从行业的发展趋势以及我们自身的产品优势上来看，AI 家云的长期的营收增长和利润率的增长动能非常强劲。所以对于加速实现 2030 年前云外部收入 1,000 亿美元的目标，我们具备极强的信心，也认为对 AI 云业务实现 20% 以上的利润率有很强的可见性。

Joseph Tsai: 因此鉴于我们拥有亚洲云厂商里最多的数据中心，具备最强的规模效应。同时我们自研的平头哥AI芯片的规模化部署扩大，避免了外购高端的商业化GPU的高额溢价对毛利的侵蚀。同时由于我们自研模型的行业SOTA的能力，具备极高的算力定价能力。因此我们从行业的发展趋势以及我们自身的产品优势上来看，AI加云的长期的营收增长和利润率的增长动能非常强劲。所以对于加速实现2030年前云外部收入1,000亿美元的目标，我们具备极强的信心，也认为对AI云业务实现20%以上的利润率有很强的可见性。

Eddie Wu: [Foreign language].

Speaker #5: Given that we operate the largest number of data centers of any Asian cloud provider, we benefit from the strongest economies of scale. At the same time, the large-scale deployment of our proprietary T-Head AI chips allows us to avoid the high price premiums associated with procuring expensive commercial GPUs, thus avoiding erosion of our gross margins.

Eddie Wu: Given that we operate the largest number of data centers across any Asian cloud provider, we benefit from the strongest economies of scale. At the same time, the large scale deployment of our proprietary T-Head AI chips allows us to avoid the high price premiums associated with procuring expensive commercial GPUs, thus avoiding erosion of our gross margins. With our state-of-the-art performance in our proprietary models, we possess strong pricing power for our compute resources. Looking ahead from the perspective of industry development trends and our own product strengths, the long-term revenue growth trend and margin expansion trend are exceptionally strong. As a result, we are highly confident in our ability to achieve our goal of CNY 100 billion in external cloud revenue by 2030. We have good visibility into achieving gross margin of 20%.

[Translator]: Given that we operate the largest number of data centers across any Asian cloud provider, we benefit from the strongest economies of scale. At the same time, the large scale deployment of our proprietary T-Head AI chips allows us to avoid the high price premiums associated with procuring expensive commercial GPUs, thus avoiding erosion of our gross margins. With our state-of-the-art performance in our proprietary models, we possess strong pricing power for our compute resources. Looking ahead from the perspective of industry development trends and our own product strengths, the long-term revenue growth trend and margin expansion trend are exceptionally strong. As a result, we are highly confident in our ability to achieve our goal of CNY 100 billion in external cloud revenue by 2030. We have good visibility into achieving gross margin of 20%.

Speaker #5: And with our state of the art performance in our proprietary models we possess strong pricing power for our compute resources. So looking ahead from the perspective of industry development trends and our own product strengths the long term revenue growth trend and margin expansion trend are exceptionally strong and as a result we're highly confident in our ability to achieve our our goal of 100 billion in external cloud revenue by 2030 and we have good visibility into achieving gross margin of 20%.

Speaker #4: 好，谢谢。

Joseph Tsai: 好，谢谢。

Eddie Wu: [Foreign language].

Speaker #3: Next question please.

Lydia Liu: Next question, please.

Speaker #1: Thank you. Your next question comes from Yuan Liao with Citrix. Please go ahead.

Operator: Thank you. Your next question comes from Yuan Liao with CITIC Securities. Please go ahead.

Speaker #4: 呃，感谢管理层接受我的提问，也恭喜公司这个季度在印地钻和 AI 这个领域的积极进展。那我有一个 follow-up 的问题，关于我们的 MAST 业务。刚才 Eddie 也讲到我们 8 月份的 AR 超过 160 亿人民币，那我想问我们上个季度也有讲到年底的一个目标是要突破 300 亿的 MAST AR。那基于现在的进展，我们年底的目标会不会有一些调整？另外，在 MAST 业务当中，我们自研（bring）的模型和三方模型的占比分别是怎么样的？未来模型的竞争加剧，以及有更多开源模型的涌现，这些会怎么影响我们 MAST 的毛利率以及盈利能力？谢谢。

Yuan Liao: 感谢管理层接受我的提问，也恭喜公司这个季度在云计算和AI领域的积极进展。那我有一个follow-up的问题，关于我们的MaaS的业务。刚才Eddie也讲到我们8月份的ARR超过160亿人民币了。那我想问，我们上个季度也有讲到就是年底的一个目标是要突破300亿的MaaS ARR。那基于现在的一个进展呢，我们年底的目标会不会有一些调整？另外就是在MaaS的业务当中，我们own的模型和三方的一个模型的一个占比分别是怎么样的？那未来模型竞争加剧，以及有更多的开源模型涌现，那这些将怎么影响到我们MaaS的毛利率以及盈利的能力？谢谢。

Yuan Liao: [Foreign Language].

Speaker #5: Uh, thanks for the opportunity to ask a question, and congratulations on the strong quarterly results, especially the progress made in the AI sector.

Eddie Wu: Thanks for the opportunity to ask a question and congratulations on the strong quarterly results and especially the progress made in the AI sector. I have a follow-up question on the MaaS business. As Eddie mentioned earlier, ARR as of August has exceeded RMB 16 billion. Last quarter, I believe you stated that the target for year-end is to surpass RMB 30 billion in MaaS ARR. I am wondering, given the progress to date, do you anticipate making any adjustments to that year-end goal? Additionally, within the MaaS business, what are the respective shares of our own proprietary models versus third-party models? As model-related competition intensifies and more open source models emerge, how will these factors possibly affect gross margin and profitability in the MaaS business?

[Translator]: Thanks for the opportunity to ask a question and congratulations on the strong quarterly results and especially the progress made in the AI sector. I have a follow-up question on the MaaS business. As Eddie mentioned earlier, ARR as of August has exceeded RMB 16 billion. Last quarter, I believe you stated that the target for year-end is to surpass RMB 30 billion in MaaS ARR. I am wondering, given the progress to date, do you anticipate making any adjustments to that year-end goal? Additionally, within the MaaS business, what are the respective shares of our own proprietary models versus third-party models? As model-related competition intensifies and more open source models emerge, how will these factors possibly affect gross margin and profitability in the MaaS business?

Speaker #5: So I have a follow-up question on the MAST business. As Eddie mentioned earlier, ARR as of August has exceeded RMB 16 billion, and last quarter I believe you stated that the target for year-end is to surpass RMB 30 billion in MAST ARR.

Speaker #5: So I'm wondering, given the progress to date, do you anticipate making any adjustments to that year-end goal? And then additionally, within the MAST business, what are the respective shares of our own proprietary models versus third-party models?

Speaker #5: And as model-related competition intensifies and more open source models emerge, how will these factors possibly affect gross margin and profitability in the mass business?

Speaker #4: 好，呃，谢谢你的问题。我们现在百炼平台的 MAST 业务增速确实非常迅速。8 月份我们的 ARR 已经突破了 160 亿元人民币。从现在的增速，以及我们后续还会持续上线的更多新模型来看，我们年底突破 300 亿元 ARR 的目标，还是比较有确定性可以实现。同时，你先讲。

Joseph Tsai: 好，谢谢你的问题。我们现在的百炼平台的MaaS业务的增速确实非常迅速。8月份我们的ARR已经突破了160亿人民币。那从现在的增速以及我们现在后面持续还会上线更多的新的模型来看，我们在年底突破300亿的ARR的目标，我们觉得还是会比较确定性地实现。同时，你先讲。

Eddie Wu: [Foreign Language]

Speaker #5: Thank you for the question. Yes, indeed. Growth in Bailian’s MAST business is very rapid, and as of August we reached RMB 16 billion, or surpassed RMB 16 billion, in ARR.

Eddie Wu: Thank you for the question. Yes, indeed. Growth in Bailian's MaaS business is very rapid, and as of August we reached RMB 16 billion or surpassed RMB 16 billion in ARR. Given the current growth momentum as well as the pipeline of new models slated for launch, we remain confident that we will achieve our year-end target of RMB 30 billion ARR by the end of the year.

[Translator]: Thank you for the question. Yes, indeed. Growth in Bailian's MaaS business is very rapid, and as of August we reached RMB 16 billion or surpassed RMB 16 billion in ARR. Given the current growth momentum as well as the pipeline of new models slated for launch, we remain confident that we will achieve our year-end target of RMB 30 billion ARR by the end of the year.

Speaker #5: So, given the current growth momentum as well as the pipeline of new models slated for launch, we remain confident that we will achieve our year-end target of $30 billion ARR by the end of the year.

Joseph Tsai: 在我们现在的MaaS业务中，我们的自研模型还是占大部分的比例，但是我们三方的开源模型的比例，其实营收也是不小。这个还是要说一下我们对于模型竞争的长期看法。从我们现在看起来，一方面客户有比较强的需求，在一个AI应用当中，他可能会使用多方的模型，因为它的每个模型都会有自己的能力特点，同时我们也会看到未来更多的开源模型会更多的涌现。所以从这个角度上来说，其实是有利于阿里云百炼这样的云厂商的推理平台。因为实际上在我们的毛利水平当中，托管开源的免费的三方模型和托管我们的自研模型，从毛利水平上来说其实是相差不大的。我们的自研模型其实更多的是为了长期地去追求我们在模型的智能水平上的提升和AGI方面的突破。但是在短期的MaaS服务上面，实际上整个的毛利水平和托管开源模型的毛利水平是差不多的。所以更加竞争，或者说更加开放繁荣的开源生态，其实是有利于阿里云这样的云厂商的。

Eddie Wu: [Foreign language].

Speaker #4: 业务中我们的自研模型还是占大部分的一个比例，但是我们三方的开源模型的比例其实营收营收也是不小。呃，这个还是要说一下我们对于模型竞争的长期看法。从我们现在看看起来一方面客户有比较强的需求，在一个 AI 应用当中他可能会使用多方的模型，甚至在因为他的整个的每个模型都会有自己的能力特点，同时我们也会看到未来模型的更多的开源模型更会更多的涌现。所以从这个角度上来说其实是有利于阿里云百炼这样的这样的云厂商的推理平台。因为实际上在我们的毛利水平当中托管开源的免费的三方模型和托管我们的自研模型，从毛利水平上来说其实是其实是相差不大的。我们的自研模型其实更多的是更多的是为了长期的去追求我们在模型的智能水平上的提升和 AGI 方面的这个突破。但是在短期的 MAST 服务上面实际上整个的毛利水平和托管开源模型是毛利水平是是差不多的。所以更更加竞争或者说更加开放繁荣的开源生态其实是有利于有利于阿里云这样的云厂商的。

Speaker #5: So, on our MAST platform, our own proprietary models still account for the majority of the revenue. But, having said that, revenue from third-party models is also not small.

Eddie Wu: On our MaaS platform, our own proprietary models still account for the majority of the revenue. Having said that, revenue from third-party models is also not small. Perhaps let me talk a little bit about how we see different model capabilities. A lot of customers tend to need to use or want to use multiple different models in their own AI applications because those different models they can draw on have different characteristics or different capabilities. Having more open source models on platforms like ours, like Bailian, to provide inferencing is a good thing for us and for Bailian. When it comes to gross margin, the level of gross margin that we can achieve on a platform like Bailian from hosting our own proprietary models versus third-party models is actually very similar. It is highly comparable.

[Translator]: On our MaaS platform, our own proprietary models still account for the majority of the revenue. Having said that, revenue from third-party models is also not small. Perhaps let me talk a little bit about how we see different model capabilities. A lot of customers tend to need to use or want to use multiple different models in their own AI applications because those different models they can draw on have different characteristics or different capabilities. Having more open source models on platforms like ours, like Bailian, to provide inferencing is a good thing for us and for Bailian. When it comes to gross margin, the level of gross margin that we can achieve on a platform like Bailian from hosting our own proprietary models versus third-party models is actually very similar. It is highly comparable.

Speaker #5: And having said that, perhaps let me talk a little bit about how we see different model capabilities. A lot of customers tend to need to use, or want to use, multiple different models in their own AI applications because those different models can draw on and have different characteristics or different capabilities.

Speaker #5: So, having more open source models on platforms like ours, like Bailian, to provide inferencing is a good thing for us and for Bailian. When it comes to gross margin, the level of gross margin that we can achieve on a platform like Bailian from hosting our own proprietary models versus third-party models is actually very similar.

Speaker #5: It's highly comparable. We're really developing those proprietary models on the one hand in order to keep creating higher levels of model intelligence, and also as part of our ultimate drive to achieve AGI.

Eddie Wu: We're really developing those proprietary models on the one hand, in order to keep creating higher levels of model intelligence and also as part of our ultimate drive to achieve AGI. But simply from the perspective of the MaaS business, the level of gross margin from those two kinds of models is actually very comparable. Overall, having a prosperous and flourishing open ecosystem with many of these open source models on it is highly favorable for a cloud provider like Alibaba Cloud.

[Translator]: We're really developing those proprietary models on the one hand, in order to keep creating higher levels of model intelligence and also as part of our ultimate drive to achieve AGI. But simply from the perspective of the MaaS business, the level of gross margin from those two kinds of models is actually very comparable. Overall, having a prosperous and flourishing open ecosystem with many of these open source models on it is highly favorable for a cloud provider like Alibaba Cloud.

Speaker #5: But simply from the perspective of the MAST business, the level of gross margin from those two kinds of models is actually very comparable.

Speaker #5: But overall, having a prosperous and flourishing open ecosystem with many of these open-source models on it is highly favorable for a cloud provider like Alibaba Cloud.

Speaker #1: Let's take the last question. Thank you. Your final question comes from Alex Yao with JP Morgan. Please go ahead.

Lydia Liu: Let's take the last question.

Operator: Thank you. Your final question comes from Alex Yao with J.P. Morgan. Please go.

Speaker #4: 呃，好的。谢谢管理层给我问最后这个问题的机会。呃，刚才 Eddie 也花了蛮多篇幅讲咱们的这个全站式的 AI 生态。呃，那我的问题呢就是咱们这个全站式的 AI 生态它的这个价值最终是在哪一层去沉淀或者说去变现啊？因为我们看到的是公司在旗舰模型发布三个月之内就开源了这个 Queen 3.8 Max 的权重，同时呢咱们自研芯片的商业化开展得也挺成功的，现在已经落地到了 650 多家的外部客户。这是不是意味着管理层判断价值将会最终沉淀在算力与调度编排层，而不是模型层？还是说管理层觉得这个 AI 在不同的发展阶段，这个全站式生态的价值可能会沉淀在不同的环节？那如果咱们认为它会长期地沉淀在硬件或者是算力这个层面的话，咱们怎么考虑当政府主导的算力供给，或者同样拥有合规芯片的竞争对手扩大供应以后，在硬件或者算力这层的回报靠什么来保护？谢谢。

Alex Yao: 好的，谢谢管理层给我问最后这个问题的机会。刚才Eddie也花了蛮多篇幅讲咱们的这个全栈式的AI生态。那我的问题就是咱们这个全栈式的AI生态，它的价值最终是在哪一层去沉淀，或者说去变现？因为我们看到的是公司在旗舰模型发布三个月之内就开源了这个Qwen 3.8-Max的权重。同时，咱们自研芯片的商业化开展得也挺成功的，现在落地到了650多家的外部客户。这是不是意味着管理层的判断价值将会最终沉淀在算力与调度编排层，而不是模型层？还是说管理层觉得AI在不同的发展阶段，它的全栈式生态的价值可能会沉淀在不同的环节。那如果是咱们是觉得它会长期的价值沉淀在这个硬件或者是算力这个层面的话，咱们怎么考虑当政府主导的算力供给，或者是同样拥有核硅芯片的竞争对手扩大供应以后，在硬件或者算力这层的回报靠什么来保护？谢谢。

Alex Yao: [Foreign language].

Speaker #5: Thank you for the opportunity to ask the final question. I'd like to come back to Eddie's earlier remarks. He spoke at length about how Alibaba is developing a full-stack AI ecosystem.

Eddie Wu: Thank you for the opportunity to ask the final question. I'd like to come back to Eddie's earlier remarks. He spoke at length about how Alibaba is developing a full stack AI ecosystem. My question really is, in which layer of that full stack ecosystem do you think value will accrete and monetization will be concentrated? We saw just after it had been released for 3 months that you open sourced the weight of your flagship model Qwen 3.8-Max. At the same time, your proprietary chips are also proving successful, now serving over 600 external customers. I'm wondering if this means that the future value will accrete mainly in the compute layer or perhaps in the orchestration layer and not necessarily in the model layer, or do you think that value will accrete to different layers in different stages of development of the industry?

[Translator]: Thank you for the opportunity to ask the final question. I'd like to come back to Eddie's earlier remarks. He spoke at length about how Alibaba is developing a full stack AI ecosystem. My question really is, in which layer of that full stack ecosystem do you think value will accrete and monetization will be concentrated? We saw just after it had been released for 3 months that you open sourced the weight of your flagship model Qwen 3.8-Max. At the same time, your proprietary chips are also proving successful, now serving over 600 external customers. I'm wondering if this means that the future value will accrete mainly in the compute layer or perhaps in the orchestration layer and not necessarily in the model layer, or do you think that value will accrete to different layers in different stages of development of the industry?

Speaker #5: My question really is: in which layer of that full stack ecosystem do you think value will accrete and monetization will be concentrated? You know, we saw just after it had been released for three months that you open sourced the weights of your flagship model, Q1 3.8 Max. At the same time, your proprietary chips are also proving successful, now serving over 600 external customers.

Speaker #5: I'm wondering if if this means that you know the the future value will accrete mainly in the the compute layer or perhaps in the orchestration layer and not necessarily in the in the model layer.

Speaker #5: Or do you think that value will accrete to different layers at different stages of development in the industry? And, in the long term, if you think that value and monetization will largely be concentrated in the hardware and compute layers, then how should we think about competition going forward, given that it will be a government-led process for allocating a lot of that hardware and compute capacity?

Eddie Wu: And in the long term, if you think that value and monetization will largely be concentrated in the hardware and compute layers, then how should we think about competition going forward given that it will be a government-led process for allocating a lot of that hardware and compute capacity?

[Translator]: And in the long term, if you think that value and monetization will largely be concentrated in the hardware and compute layers, then how should we think about competition going forward given that it will be a government-led process for allocating a lot of that hardware and compute capacity?

Speaker #4: 好。呃，你这个问题问得问得很专业啊。就是也涉及到一个长期的判断。那长期的判断来说我觉得其实还是有一些不确定性的。但是总体来说我们觉得在因为我们的由于全站式的 AI 投入所以无论这个价值在哪一层在不同阶段在哪一层的多还是少我们都有机会捕获在我们这个我们这个生态当中。那我说一下我自己个人的短期的判断吧。就现在短期的判断上来说我们觉得大部分的价值还存在于呃芯片和云基础设施这一层。呃这是我们从国内外的更多公司当中也看到的一个情况。就是在当一个技术的早期尤其在一个这个技术的供给稀缺的情况下那大部分的情况确实会是这样。就大量的价值会存在于提供基础设施以及最核心的硬件包括我们的芯片啊存储啊这样的供应商当中。那在阿里巴巴的这个设计当中我们把我们的算力云基础设施和 AI 推理这一层其实是放在一个模块当中放在我们的一个板块当中的。

Joseph Tsai: 好，你这个问题问得很专业，也涉及到一个长期的判断。那长期的判断来说，我觉得其实还是有一些不确定性的。但是总体来说，因为我们由于全栈式的AI投入，所以无论这个价值在不同阶段，在哪一层的多还是少，我们都有机会不过在我们这个生态当中。那我说一下我自己个人的短期的判断吧。就现在短期的判断上来说，我们觉得大部分的价值还存在于芯片和云基础设施这一层。这是我们从国内外更多的公司当中也看到的一个情况，就是在当一个技术的早期，尤其在一个这个技术的供给稀缺的情况下，那大部分的情况确实会是这样，大量的价值会存在于提供基础设施以及最核心的硬件，包括我们的芯片、存储这样的供应商当中。那在阿里巴巴的这个设计当中，我们把我们的算力、云基础设施和AI推理这一层，其实是放在一个模块当中，放在我们的一个板块当中的。

Eddie Wu: [Foreign language].

Speaker #5: Uh, thanks. You know, that's a very professional question, and it really is a matter of long-term judgment. So I think it's inherently associated with a high level of uncertainty.

Eddie Wu: Thanks. That's a very professional question, and really it's a matter of long-term judgment. I think it's inherently associated with a high level of uncertainty. But what I can say is that we are investing in the full stack.

[Translator]: Thanks. That's a very professional question, and really it's a matter of long-term judgment. I think it's inherently associated with a high level of uncertainty. But what I can say is that we are investing in the full stack.

Speaker #5: But what I can say is that we are investing in the full stack, and what that means is that whichever layer represents the greatest value—and no matter how that may shift across layers in different periods of time—all of those layers are part of our ecosystem.

Eddie Wu: And what that means is that whichever layer represents the greatest value, and no matter how that may shift across layers in different periods of time, all of those layers are part of our ecosystem. I guess I can share with you my own short-term view. Namely, in the short-term perspective, I think that most of the value will be in chips and in AI cloud infrastructure. It's a pattern that we can see not just in China, but globally across a lot of different companies when a technology is in its early stages, and especially when there's a shortage of supply, lots of the value tends to be concentrated in the infrastructure and in the core hardware, in this case, chips and storage. So in Alibaba's case, we've integrated our compute power, our cloud infrastructure, and our AI inference into one core business segment.

[Translator]: And what that means is that whichever layer represents the greatest value, and no matter how that may shift across layers in different periods of time, all of those layers are part of our ecosystem. I guess I can share with you my own short-term view. Namely, in the short-term perspective, I think that most of the value will be in chips and in AI cloud infrastructure. It's a pattern that we can see not just in China, but globally across a lot of different companies when a technology is in its early stages, and especially when there's a shortage of supply, lots of the value tends to be concentrated in the infrastructure and in the core hardware, in this case, chips and storage. So in Alibaba's case, we've integrated our compute power, our cloud infrastructure, and our AI inference into one core business segment.

Speaker #5: I guess I can share with you my own short-term view. Namely, in the short-term perspective, I think that most of the value will be in chips and in AI cloud infrastructure.

Speaker #5: It's a pattern that we can see not just in China, but globally across a lot of different companies. When a technology is in its early stages, and especially when there's a shortage of supply, lots of the value tends to be concentrated in the infrastructure and in the core hardware—in this case, chips and storage.

Speaker #5: So in Alibaba's case, we've integrated our compute power, our cloud infrastructure, and our AI inference into one core business segment.

Speaker #4: 好。关于您刚才说的模型的这一层的商业价值如何体现那这一层我觉得在行业内的争论也很多啊。我觉得在我们公司内部也是大家各有不同的看法。我只是说一下我的个人看法。呃就我的个人看法而言 AI 大模型的这一层现在现在通过 API 来变现的商业模式我觉得是对于大模型来说是一个短期阶段性的商业模式肯定不是最终极的商业模式。如果我们最其实我们公司投入这么大的算力投入去在我们的全站式的就是全站的模型上面的这个投入其实目标肯定不是为了现在短期的 API 的这这部分收入。因为我们觉得未来当 AI 大模型能够实现 AGI 或者接近 AGI 的能力的时候其实最终的商业模式应该是会直接直接创造产品或者直接创造客户所需要的结果。尤其是在商业的产品研发或者产品创造上面或者商业的直接的运营上面。所以到了那个阶段其实 AI 模型公司或者 AI 模型的商业模式不应该是提供 API 服务啊。那个阶段的商业价值这也是支撑全世界这么多模型公司在现阶段持续不断的军备竞赛投入的原因所在。所以从这个角度上来看我觉得 AI 大模型的大模型的商业价值现在还远远远远没有看到。未来的商业价值会比现在所提供的 API 的商业服务会会会高很多。

Joseph Tsai: 好，关于您刚才说的模型的这一层的商业价值如何体现，那这一层我觉得在行业内的争论也很多，我觉得在我们公司内部也是大家各有不同的看法。我只是说一下我的个人看法。就我的个人看法而言，AI大模型的这一层，现在通过API来变现的商业模式，我觉得是对于大模型来说是一个短期阶段性的商业模式，肯定不是最终极的商业模式。其实我们公司投入这么大的算力，投入在我们的全站的模型上面的这个投入，其实目标肯定不是为了现在短期的API的这部分收入。因为我们觉得未来当AI大模型能够实现AGI或者接近AGI的能力的时候，其实最终的商业模式应该是会直接创造产品，或者直接创造客户所需要的结果，尤其是在商业的产品研发，或者产品创造上面，或者商业的直接的运营上面。所以到了那个阶段，其实AI模型公司或者AI模型的商业模式不应该是提供API服务。那个阶段的商业价值，这也是支撑全世界这么多模型公司在现阶段持续不断地军备竞赛投入的原因所在。所以从这个角度上来看，我觉得AI大模型的商业价值现在还远远没有看到。未来的商业价值会比现在所提供的API的商业服务高很多。

Eddie Wu: [Foreign language].

Speaker #5: Now, turning next to where the ultimate commercial value will be realized from these AI models: you know, it's a question around which there's a lot of debate within the industry, and indeed, there are different views even inside our own company.

Eddie Wu: Let me turn next to where the ultimate commercial value will be realized from these AI models。It's a question around which there's a lot of debate within the industry, and indeed, there are different views even inside our own company。So here I'm just sharing my own personal opinion。But in my personal view, I think that the current monetization model for large language models 通过APIs是一种短期的、过渡性的方法，但肯定不是最终的商业模式。我们的公司在整个平台上投入了大量的计算能力，但目标不仅仅是产生那种短期的API收入。我认为当我们达到实现AGI，或接近实现AGI的阶段时，最终的商业模式将是交付客户真正需要的实际产品和结果，进行实际的R&D，交付产品，并运营业务。所以，这些不同的AI模型公司在今天投入如此多，进行激烈竞争，不仅仅是为了能够提供那类API服务，更是因为他们的目光聚焦在最终的终局，我认为在那里的货币化水平会大幅高于今天通过API调用出售服务的情况。

[Translator]: Let me turn next to where the ultimate commercial value will be realized from these AI models。It's a question around which there's a lot of debate within the industry, and indeed, there are different views even inside our own company。So here I'm just sharing my own personal opinion。But in my personal view, I think that the current monetization model for large language models through APIs is just a short-term approach, a short-term transitional approach, and it's certainly not the ultimate business model.

Speaker #5: So here, I'm just sharing my own personal opinion. But in my personal view, I think that the current monetization model for large language models through APIs is just a short-term approach—a short-term, transitional approach—and it's certainly not the ultimate business model.

[Translator]: You know, our company has invested a tremendous amount od compute across our entire platform, but the objective is not simply to be abke to generate that kind of short-term API revenue. I think when we get to the stage where we have accomplished AGI, or we are close to achieving AGI, at that point the ultimate business model will be delivering actual products, delivering actual results that clients are looking for.

[Translator]: It will be conducting the acrual R&D that delivers products and that delivers operations. So, you know, the reason that all these different model companies are investing so heavily and engaging in an arms race today is not simply to be able to complete to provide the API-based service, because they have their eyes on that ultimate endgame where I think the monetization level will be significantly higher, be much higher than that what you see today selling the service through API calls.

Speaker #5: You know our company has invested a tremendous amount of compute across our entire platform, but the objective is not simply to be able to generate that kind of short-term API revenue.

Speaker #5: I think when we get to the stage where we've accomplished AGI, or we're close to achieving AGI, at that point the ultimate business model will be delivering actual products, delivering actual results.

Speaker #5: The clients are looking for who will be conducting the actual R&D that delivers products and that delivers operations. So, you know, the reason that all these different AI model companies are investing so heavily and engaging in an arms race today is not simply to be able to compete to provide that API-based service.

Speaker #5: It's because they have their eyes on that ultimate endgame, where I think the monetization level will be significantly higher. It'll be much higher than what you see today selling the service through API calls.

Speaker #4: 好。关于您说的在硬件算力层面我觉得你这个问题我也想比较重点的回答一下。因为实际上对于我们的自研芯片平头哥的芯片的布局其实我们在以前的投资人会议上说的比较少。我今天稍微展开一下就是我们的平头哥的上一代芯片已经出货了 50 万片以上而我们刚才所说的全国产化的第一代芯片已经在 8 月份开始以超节点的形式在阿里云上面已经开始全面上架而这一代的芯片我觉得我们是中国市场唯二的可以放量进行对超节点上架的一个公司。所以我们对这一代国产芯片在客户的接受度上以及大规模的商业化程度上我们的信心非常强。因为这里面我也要说一下我们平头哥芯片的在所有国产芯片当中的一个一个不同的特点。因为平头哥的 AI 芯片是就我现在看到是是在国内芯片当中比较独特的一 GP GPU 架构作为一个核心的一个一个技术架构的。那么在这个技术架构下我们同时能够非常好的支持训练和推理的工作负载。所以我们在支持的众多的几百个中大型的客户当中既在帮他们做推理也在帮他们做模型的训练尤其是像众多的具身智能公司和众多的自动驾驶公司包括很多的大的模型公司。所以从这个角度上我们可能是在中国唯一具备就是大规模的训练和推理商业化客户的这样一款芯片。然后另外一个我也想说一下我们对平头哥的第二代的国产芯片的一个期待。我们对平头哥的第二代国产芯片因为今年今年下半年会开始开始逐渐的逐渐的流片和产出我们这一代的芯片会有非常强的算力以及非常强强的互联带宽我们觉得完全可以替代大规模的模型训练。从这个角度上我觉得我们在国内的芯片上的技术上的升位是非常独特的。所以我不觉得有一个所谓政府主导的算力供给会能够有一个非常强的竞争力的芯片所以从这个角度上我们觉得对于平头哥未来成为阿里云的主要核心的核心的竞争力我们觉得还是还是非常有信心的尤其是阿里云现在已经有几百个中大型的客户在平头平头哥的芯片上或者的一个比较好的好的好的使用使用价值在国内我觉得从接触的工程师的角度上来说其实我们的芯片也是说工程师的范围接触的工程师的范围也也是非常广的。

Joseph Tsai: 关于您说的在硬件算力层面，我觉得你这个问题我也想比较重点地回答一下，因为实际上对于我们的自研芯片平头哥的芯片的布局，我们在以前的投资人会议上说得比较少。我今天稍微展开一下，我们的平头哥的上一代芯片已经出货了50万片以上，而我们刚才所说的全国产化的第一代芯片已经在8月份开始以超节点的形式在阿里云上面已经开始全面上架。而这一代的芯片，我觉得我们是中国市场唯二的可以放量进行对超节点上架的一个公司，所以我们对这一代国产芯片在客户的接受度上，以及大规模的商业化程度上，我们的信心非常强。这里面我也要说一下我们平头哥芯片的在所有国产芯片当中的一个不同的特点，因为平头哥的AI芯片就我现在看到是在国内芯片当中比较独特的，以GPGPU架构作为一个核心的技术架构的。那么在这个技术架构下，我们同时能够非常好地支持训练和推理的工作负载，所以我们在支持的众多的几百个中大型的客户当中，既在帮他们做推理，也在帮他们做模型的训练，尤其是像众多的巨型智能公司和众多的自动驾驶公司，包括很多的大的模型公司。所以从这个角度上，我们可能是在中国唯一具备大规模的训练和推理商业化客户的这样一款芯片。另外一个，我也想说一下我们对平头哥的第二代的国产芯片的期待。平头哥的第二代国产芯片因为今年下半年会开始逐渐地流片和产出，我们这一代的芯片会有非常强的算力以及非常强的互联带宽，我们觉得完全可以替代大规模的模型训练。从这个角度上，我觉得我们在国内的芯片技术上的地位是非常独特的，所以我不觉得有一个所谓政府主导的算力供给，会能够有一个非常强的竞争力的芯片。所以从这个角度上，我们觉得对于平头哥未来成为阿里云的主要核心的竞争力，我们觉得还是非常有信心的。尤其是阿里云现在已经有几百个中大型的客户在平头哥的芯片上获得了一个比较好的使用价值。在国内，我觉得从接触的工程师的角度上来说，其实我们的芯片接触的工程师的范围也是非常广的。

Eddie Wu: [Foreign language].

Speaker #5: 呃 in terms of hardware you know I'd like to add a few thoughts regarding our T head proprietary chips. I know it's a topic about which we haven't communicated a lot with investors in the past but the last generation of T head chips we've already manufactured over 500,000 of them and and shipped and then the latest generation in August has already been deployed on AI Alibaba's AI cloud as a super nodes and I think we're one one of the the only companies that's able to deploy such proprietary chips domestic chips at scale.

Eddie Wu: 在硬件方面，我想补充几句关于我们的T-Head自有芯片的事。我知道这是我们过去没有跟投资者沟通很多的话题，但我们已经生产了超过50万片上一代T-Head芯片，并已经出货。而最新一代在8月已经部署到阿里云AI云作为Supernode。我认为我们是少数能够大规模部署这种自有芯片、国产芯片的公司之一。我们T-Head芯片的独特之处在于它采用GPU架构作为核心技术基础，既可以很好地支持训练，也能支持推理工作load。目前已有数百家公司通过阿里云利用这些芯片进行推理以及模型训练。

Eddie Wu: [Foreign language].

Speaker #5: One thing that's really unique about our T-Head chips—domestically manufactured chips—is that they are designed with GPU architecture as their core technical foundation, and they can very well support both training and inference workloads.

Speaker #5: So, there are now already several hundred companies that are leveraging these chips via Alibaba Cloud for both inference as well as for model training, and these span companies across embodied AI, autonomous driving, as well as large model companies.

Eddie Wu: And these span companies across embodied AI, autonomous driving, as well as large model companies. So in terms of our generation 2 of chips, we are going to start developing them in the second half of this year. And we expect them to boast exceptionally high compute power as well as extremely robust interconnection bandwidth, making them fully capable of serving as a direct replacement for existing chips. So I think we're in a really unique position in the chip sector, especially when it comes to large-scale model training. So I don't think that there's any government-led compute supply allocation scheme that could produce chips with such truly strong competitiveness. So I think that T-Head's future is highly certain as a very key and core component of Alibaba Cloud, and we remain highly confident in our core competitive strengths in this area.

[Translator]: And these span companies across embodied AI, autonomous driving, as well as large model companies. So in terms of our generation 2 of chips, we are going to start developing them in the second half of this year. And we expect them to boast exceptionally high compute power as well as extremely robust interconnection bandwidth, making them fully capable of serving as a direct replacement for existing chips. So I think we're in a really unique position in the chip sector, especially when it comes to large-scale model training. So I don't think that there's any government-led compute supply allocation scheme that could produce chips with such truly strong competitiveness. So I think that T-Head's future is highly certain as a very key and core component of Alibaba Cloud, and we remain highly confident in our core competitive strengths in this area.

Speaker #5: So, in terms of our generation two chips, we are going to start developing them in the second half of this year, and we expect them to boast exceptionally high compute power as well as extremely robust interconnection bandwidth, making them fully capable of serving as a direct replacement for existing chips.

Speaker #5: So I think we're in a really, really unique position in the chip sector, especially when it comes to large-scale model training. So I don't think that there's any government-led compute supply allocation scheme that could produce chips with such truly strong competitiveness.

Speaker #5: So, I think that T Head's future is highly certain as a very key and core component of Alibaba Cloud, and we remain highly confident in our core competitive strengths in this area.

Speaker #5: I've interacted with a lot of different engineers across China, and I can tell you that these chips have a very broad audience, with engineers across a wide range of different engineering domains.

Eddie Wu: I've interacted with a lot of different engineers across China, and I can tell you that these chips have a very broad audience with engineers across a wide range of different engineering domains.

[Translator]: I've interacted with a lot of different engineers across China, and I can tell you that these chips have a very broad audience with engineers across a wide range of different engineering domains.

Speaker #4: 好所以总结来说我觉得我们的平头哥的芯片在在支持多行业的训练和推理的这个多样性上我觉得是国产芯片可以说第一从那个我们在行业的未来的这个产能和供应链的布局上我们可以说是前爱的存在从我们对于未来AI芯片的对客户的渠道能力上由于阿里云的长期的在中国的AI云上面是最大的最大市场份额的厂商我们在未来的渠道能力上我觉得会是非常强的存在所以从这个角度上我觉得我们平头哥的芯片长期的商业价值我觉得我们还是非常有信心的

Joseph Tsai: 好，所以总结来说，我觉得我们的平头哥的芯片在支持多行业的训练和推理的多样性上，我觉得是国产芯片可以说第一。从我们在行业的未来的产能和供应链的布局上，我们可以说是前二的存在。从我们对于未来AI芯片的对客户的渠道能力上，由于阿里云长期的在中国的AI云上面是最大市场份额的厂商，我们在未来的渠道能力上，我觉得会是非常强的存在。所以从这个角度上，我觉得我们平头哥的芯片长期的商业价值，我觉得我们还是非常有信心的。

Eddie Wu: [Foreign language].

Speaker #5: 呃 so to sum up I think that our T head chips are definitely the best among domestic Chinese chips for supporting both training and inference across a wide range of different industries so we we really are number one in the industry and then I think in terms of future production capacity and deployment we can confidently claim to be at least one of the top two but in terms of our ability to actually reach customers with AI chips you know Alibaba cloud is the largest player by market share in China's cloud and AI market so I think we have a very strong edge when it comes to channel distribution so from this perspective I am highly confident in the long-term commercial value of T head chips.

Eddie Wu: To sum up, I think that our T-Head chips are definitely the best among domestic Chinese chips for supporting both training and inference across a wide range of different industries. We really are number one in the industry. Then I think in terms of future production capacity and deployment, we can confidently claim to be at least one of the top 2. But in terms of our ability to actually reach customers with AI chips, Alibaba Cloud is the largest player by market share in China's cloud and AI market. I think we have a very strong edge when it comes to channel distribution. From this perspective, I am highly confident in the long-term commercial value of T-Head chips.

[Translator]: To sum up, I think that our T-Head chips are definitely the best among domestic Chinese chips for supporting both training and inference across a wide range of different industries. We really are number one in the industry. Then I think in terms of future production capacity and deployment, we can confidently claim to be at least one of the top 2. But in terms of our ability to actually reach customers with AI chips, Alibaba Cloud is the largest player by market share in China's cloud and AI market. I think we have a very strong edge when it comes to channel distribution. From this perspective, I am highly confident in the long-term commercial value of T-Head chips.

Speaker #1: Thank you very much. We appreciate your support, and we look forward to updating you on our progress next quarter. Thank you.

Lydia Liu: Thank you very much. We appreciate your support, and we look forward to updating you on our progress next quarter. Thank you.

Operator: Thank you. That does conclude our conference for today. Thank you for participating. You may now disconnect.

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Q2 2026 Alibaba Group Holding Ltd Earnings Call

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