Transcript: Alibaba Gr Hldgs Q1 2027 Earnings Conference Call

On Thursday, Alibaba Gr Hldgs (NYSE:BABA) discussed first-quarter financial results during its earnings call. The full transcript is provided below.

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The full earnings call is available at https://edge.media-server.com/mmc/p/cnqsvuvm/

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Summary

Alibaba Gr Hldgs reported a 9% year-over-year revenue growth driven by strategic AI investments, with Alibaba Cloud's external revenue growing 45% and AI-related product revenue maintaining triple-digit growth.

The company is focusing on AI and cloud commercialization, scaling proprietary chips, enhancing AI-native applications, and solidifying its e-commerce business, with AI becoming a major growth engine.

Total revenue for the quarter was RMB 269 billion, with adjusted EBITDA decreasing by 30% due to technology investments; GAAP net income decreased by 75% mostly due to lower income from operations and equity investments.

CapEx increased significantly to RMB 67.7 billion, primarily due to AI infrastructure investments and fluctuations in procurement cycles, with expectations of continued investment driven by high demand for AI compute capacity.

Management reaffirmed commitment to long-term strategic investments in AI and cloud, projecting accelerated revenue growth and margin improvements in these areas, aiming for a US$100 billion external cloud revenue goal by 2030.

Full Transcript

Lydia Liu, Head of Investor Relations

Thank you for standing by. Welcome to Alibaba Gr Hldgs' 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 Gr Hldgs. Please go ahead. Thank you. Good day everyone, and welcome to Alibaba Gr Hldgs' June quarter 2026 earnings conference call. Joining the call today are Zhu Cai, Chairman; Eddie Wu, Chief Executive Officer; Toby Xu, Chief Financial Officer; and 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.

Eddie Wu, Chief Executive Officer

Good evening, good morning, and welcome to Alibaba Gr Hldgs' earnings call for the first quarter of fiscal year 2027. Over the past quarter, Alibaba Gr Hldgs' 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 US$7.3 billion. 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, AI application ecosystem, and consumption business. 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%. 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.

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.

T-Head has established a full-stack proprietary silicon portfolio spanning GPU, CPU, and networking chips. As of early August, Chunwu chips have served more than 650 customers on Alibaba Cloud. The supernode instance powered by T-Head's next-generation 890 AI processor recently launched on Alibaba Cloud at commercial scale. We expect supply to continue ramping up in the second half of the year to meet strong customer demand. Alibaba Cloud's JunWoo M890 super node can efficiently run inference workload for foundation models with more than 2 trillion parameters.

Both KPK3 and QN 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 buildout. 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 Qin 3.8 Max with 2.4 trillion parameters and the QN 3.8 27B model series. To date, the QN 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 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. On the consumer side, the Kuin 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.

Fourth, our E-commerce businesses remain 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'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.

Looking ahead, AI has become Alibaba Gr Hldgs' most certain growth engine, but 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. Thank you.

Toby Xu, Chief Financial Officer

Thank you, Eddie. Our strategic priorities in AI, 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 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 realignment of certain businesses in our financial reporting. 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 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 decreasing net gains from disposal of investments and mark-to-market changes of our equity investments. 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 only 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, and a higher pricing of a broad range of chip components.

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 point. This balance sheet strength gives us confidence to invest for robust growth. Our AI cloud investment has a clear path to attractive ROIC. Our service 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 at least in the two years following breakeven.

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

Starting from this quarter we will present Alibaba E-commerce Group's revenue as the following: first, China e-commerce; second, China quick commerce; third, international e-commerce; and fourth, global wholesale. Revenue for Alibaba E-commerce Group was RMB 205.9 billion, an increase of 4%. Customer management revenue decreased by 7%. Excluding the contract revenue impact from the new business development program, customer management 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 Flashhipo and Taobao Instant Commerce. 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. 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.

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. 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 an annual 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. 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 Cloud business and driving greater benefits of scale. AI Lab Applications comprises AI Model Labs, Queen Consumer Business Group and Queen 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 Queen App.

The loss significantly narrowed quarter over quarter due to the reduction in marketing expenses for QueenApp. We expect the segment loss to narrow over the coming quarters, driven by improving efficiency in both model training and marketing spend on queenapping. 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 QueenApp's agentic features across an expanding range of e-commerce and other services since the launch of Queenapping.

All Other segment revenue remained stable at RMB 28.8 billion. All Others adjusted EBITDA was a loss of 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 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, 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.

Lydia Liu, Head of Investor Relations

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 prevail. Operator, please start the Q&A session.

OPERATOR

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, please press. If you're on a speakerphone, please pick up the handset to ask questions. 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.

Alicia Yap, Analyst at Citigroup

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

And also we would appreciate if management can also provide a breakdown of the CapEx allocation across the different services like the training cost and all that. And then also what is management expected return on the invested capital for this investment? Thank you.

Toby Xu, Chief Financial Officer

Next let me explain why we see 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. So 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 three years 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.

Following 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. 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 businesses.

And 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'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%. So that represents initial validation of that thesis. 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. 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.

So you see here the. 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. So these are important ways in which we can further enhance ROIC. 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.

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. However, that is not our strategic choice at this time. Given that AI remains in a very early stage, we're 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 two and a half years or even less. 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.

OPERATOR

Next question please. Thank you. Your next question comes from Charlene Liu with HSBC. Please go ahead.

Charlene Liu, Analyst at HSBC

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 under the reclassification of multiple business lines which are regrouped under the Alibaba e-commerce group? Can you talk about the future strategic focuses of these lines of businesses? Let me quickly translate the question myself. Thank you.

Eddie Wu, Chief Executive Officer

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 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. 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 and at the same time we aim to leverage AI to enhance the overall shopping experience and improve operational efficiency across the board. 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. 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 in 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, 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. 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, and we've already observed that AI has driven significant efficiency gains in our product recommendations, 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, particularly in data analytics, advertising and marketing, and customer service, where merchants can derive clear benefits.

And going forward, we'll also collaborate with QEN Office to launch AI agents that are specifically tailored for e-commerce scenarios. 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 year-over-year increase in GMV. 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.

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. 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 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 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.

Over the past few years we have completed new strategic positioning for our e-commerce businesses across several key areas. And 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.

OPERATOR

Let's go to the next question. Thank you. Your next question comes from Yang Bai with CICC. Please go.

Yang Bai, Analyst at CICC

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. We know the company has previously set a long-term goal of exceeding US$100 billion in external cloud revenue over the next five years. 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? 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. And you just mentioned that that 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 and do they differ from those in the short term?

Thank you.

Eddie Wu, Chief Executive Officer

Thank you for the question and 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, 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. 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%.

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. We've observed that AI-related products generated 12.4 billion RMB in revenue this quarter, and if we convert that into an annualized US dollar figure, that works out to US$7.3 billion in annual revenue. Looking ahead to the next quarter, our own forecast is that that same annualized revenue for AI next quarter will approach US$10 billion.

So 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've 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 16 billion RMB.

And actually, let me clarify, that's the latest data. As of August it's already surpassed 16 billion RMB. Next, let me expand on the growth drivers within our business model. It's important to understand that Alibaba Gr Hldgs' 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, AI cloud infrastructure, and 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's possible for us to maintain competitiveness and sustained growth momentum.

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'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, and today all AI-related revenue models are centered on AI compute.

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. The higher gross margins of MaaS 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. 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 Gr Hldgs boasts comprehensive models and 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 more healthy pricing models. We expect to see this as a very positive short-term driver for improving margin in the coming year. Next, let me talk about the scale effects and network 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 is that the real super application is compute—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 tools among others. So 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. 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're highly confident in our ability to achieve our goal of 100 billion in external cloud revenue by 2030, and we have good visibility into achieving gross margin of 20%.

OPERATOR

Next question please. Thank you. Your next question comes from Yuanli. Please go ahead.

Yuanli, Analyst

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 16 billion RMB, and last quarter I believe you stated that the target for year end is to surpass 30 billion in MaaS ARR. So I'm 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? And 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?

Eddie Wu, Chief Executive Officer

Thank you for the question. Yes indeed, growth in Bailian's MaaS business is very rapid, and as of August we reached 16 billion RMB—or surpassed 16 billion RMB—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 30 billion ARR by the end of the year. On our MaaS platform, our own proprietary models still account for the majority of the revenue.

That said, 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 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's highly comparable. We're 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.

OPERATOR

Let's take the last question. Thank you. Your final question comes from Alex Yao with JP Morgan. Please go on.

Alex Yao, Analyst at JP Morgan

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 Gr Hldgs 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 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. I'm wondering if this means that the

Eddie Wu, Chief Executive Officer

You know, that's a very professional question and really is a matter of long-term judgment. So 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, and what that means is that whichever layer represents the greatest value and no matter how that may shift across layers and 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.

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 companies. 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.

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. 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 that clients are looking for. It'll 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. It's because they have their eyes on that ultimate endgame where I think that the monetization level will be significantly higher. It will be much higher than what you see today, selling the service through API calls. 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 shipped, and then the latest generation in August has already been deployed on Alibaba's AI Cloud as super nodes. And I think we're one of the only companies that's able to deploy such proprietary chips, domestic chips, at scale. One thing that's really unique about our chips, 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.

So there are now already several hundreds of 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. So in terms of our generation two 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, 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.

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. 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 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, 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.

Lydia Liu, Head of Investor Relations

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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