Tencent Holdings Ltd. Stock

Good day, and good evening. Thank you for standing by. Welcome to Tencent Holdings Limited 2026 Second Quarter Results Announcement Webinar. I'm Wendy Huang from Tencent IR team. [Operator Instructions] And please be advised that today's webinar is being recorded.

Before we start the presentation, we would like to remind you that it includes forward-looking statements, which are underlined by a number of risks and uncertainties and may not be realized in the future for various reasons. Information about general market conditions is coming from a variety of sources outside of Tencent.

This presentation also contains some unaudited non-IFRS financial measures that should be considered in addition to, but not as a substitute for measures of the group's financial performance prepared in accordance with IFRS. For a detailed discussion of risk factors and non-IFRS measures, please refer to our disclosure documents on the IR section of our website.

Let me now introduce the management team on the webinar tonight. Our Chairman and CEO, Pony Ma, will kick off with a short overview. President, Martin Lau, will provide a strategy review. Chief Strategy Officer, James Mitchell, will provide a business review; and Chief Financial Officer, John Lo, will conclude with financial discussion before we open the floor for questions.

I will now pass it to Pony.

Thank you, Wendy. Good evening. Thank you, everyone, for joining us. As we enter into the third quarter of the year, we are making substantial progress towards building a new AI-empowered Tencent in terms of intelligence, applications and infrastructure. At the intelligent level, Hunyuan 3's production version provides user a wide use model with a strong cost performance metrics and serve as a stepping stone toward the Hunyuan family of models attaining state-of-the-art capabilities in the future.

At the application level, our WorkBuddy AI office productivity service and CodeBuddy AI coding tool are achieving user growth and are the clear leaders in the field in China today. At the infrastructure level, we substantially stepped up our procurement of compute, which will enable us to convert usage of our applications and models into revenue going forward. At the same time, we continue to enhance our existing services with a sustained marketing service revenue growth, several successful recently released games and rapidly increasing video views on Weixin video accounts.

Looking at our financial numbers for the second quarter. Total revenue was RMB 205 billion, up 11% year-on-year. Gross profit was RMB 118 billion, up 13% year-on-year. Non-IFRS operating profit was RMB 76 billion, up 9% year-on-year. Excluding new AI products, non-IFRS operating profit was RMB 86 billion, up 19% year-on-year and non-IFRS net profit attributable to equity holders was RMB 68 billion, up 9% year-on-year.

Turning to our key services. For presentation and social networks, combined MAU of Weixin and WeChat grew year-on-year and quarter-on-quarter to RMB 1.4 billion. For digital content, TME's acquisition of Ximalaya strengthened our audio content and unlocked new synergies with the ecosystem IPs, including from China literature. For games, new game Local Kingdom World ranked first by average DAU and by gross receipts among all new games released in China industry-wide this year. For cloud, WorkBuddy recently ranked first among productivity AI service in China based on monthly interactions.

I will now hand over to Martin for the strategic review.

Thank you, Pony, and good evening and good morning to everybody. Today, we want to provide you with an update on our overall AI strategy. Tencent's existing businesses are growing solidly due to intrinsic modes and AI enablement. As discussed earlier this year, our moats arise from factors, including network effect, depth and value-added along supply chain, IP, low take rates, regulatory requirements and private data. In addition to these modes, we're further deploying AI to boost returns in areas, including Weixin games and advertising. As a result, our existing businesses provide a very strong financial support for our new AI initiatives.

Regarding our new AI initiatives, we've made significant progress in constructing a robust foundation, including a substantially improved Hunyuan 3 foundation model with leading cost performance, WorkBuddy and CodeBuddy that lead the China market in terms of AI productivity usage and Yuanbao and Xiaowei serving as gateways to drive broader consumer AI adoption. We see increasing potential to generate attractive financial returns from franchise products with differentiated advantages, including Hunyuan, WorkBuddy and Xiaowei over time.

We're comfortable in making significant investments in AI because not only there is a substantial upside potential, there is also clear downside protection. The AI investments we're making are mostly in AI infrastructure. And in the worst case, which we do not believe that would happen, we can choose to ramp that infrastructure out at cost recovery or even better prices via Tencent Cloud if needed. Now going on to the different components. First, on Hunyuan Foundation model.

The release of Hunyuan 3's full production version is very successful, showing a substantial step-up in performance compared to the Hunyuan 3 preview version, leveraging the feedback loop from product teams to improve the quality and diversity of data used for post training and by scaling up reinforcement learning, Hunyuan 3 achieved a notable improvement in task completion rates and meaningful reduction in hallucination and error rates. The improvements in Hunyuan 3's capabilities are most evident in its agent capabilities and product experience.

The model's performance step-up across reasoning agent and long contest tasks delivered clear advantages for use cases such as coding, office work, financial modeling and front-end design. These performance improvements drove accelerated user adoption and growing external customer demand, validating its practical utility in real-world usage as demonstrated by the approximately 6x increase in average daily token usage of Hunyuan 3 compared to the preview version across all channels during the pay period. Additionally, Hunyuan 3 consistently ranks among the top 3 models globally on open router based on token usage.

Hunyuan 3's production version has performed well and will serve as a stepping stone towards the Hunyuan family of models, achieving state-of-the-art capabilities in the future while providing users with the cost performance efficiency that they need today. We have been integrating Hunyuan into our products, making great impact. For WorkBuddy, Hunyuan can facilitate complex agent workflows with higher task success rates and reduced time to completion. For Yuanbao, Hunyuan delivers leading execution quality and information retrieval data processing, document workflows and everyday decision-making.

In games, we're leveraging Hunyuan for AI teammate creation and code review for games, including our flagship game, Peacekeeper Elite. And in Weixin, we deployed Hunyuan 4 powering the AI assistant in official accounts and developer tools for mini programs. At the same time, product integration is making Hunyuan better. By continuously feeding real-world product usage and domain feedback into model training, our model product codesign approach allows Hunyuan to validate model accuracy and identify and work on edge cases, enabling faster model iteration and sustained performance gains. Having now established a new system for fast model iteration and with Hunyuan 3 validating the system, we're accelerating the improvement of our model. We're scaling more powerful reinforcement learning to substantially upgrade models after pretraining is done, and we're in the process of upgrading multimodal capabilities.

More importantly, we're training a larger pad model, Hunyuan 4, which we expect to release later this year. By accelerating the technical iteration and pushing the boundaries of model intelligence, we're confident Hunyuang's capabilities will reach state-of-the-art level. We believe we will generate significant return in building a large and valuable AI native new business for Tencent. The rationale behind investing in our own foundation model is that we can achieve better unit economics, more innovative features and more exposure to the value of intelligence through co-design across our applications, our model and our compute infrastructure, especially at this early stage of AI diffusion.

And moving on to the application front. Our AI office productivity workspace, WorkBuddy and coding tool CodeBuddy are achieving breakout success in terms of capability and user growth that the clear leading office productivity service in China based on monthly interactions. WorkBuddy serves as a one-stop shop workspace that orchestrates multiple agents to handle complex work from end to end. Users can remotely control WorkBuddy via Weixin and WeCom as well as VPC and access to over 70,000 skills from Tencent Cloud Skill Hub.

Besides the rapid user adoption of WorkBuddy, it is also achieving high retention rates and high willingness to pay among users as it directly contribute to users' productivity. It also attracts growing and more vibrant developer community by embedding skill pay and Weixin Pay inside task flows to enable payouts for developers when their skills are called. This progress supports our view that there are substantial opportunities to be unlocked in the productivity market, including coding and existing office work scenarios. We're currently focused on investing in market education and extending our market leadership position. Over time, product economics will be attractive as enhanced premium benefits accelerate paying user growth while we can reduce token costs through agent efficiency, inference efficiency and model optimization.

Given Tencent applications such as Weixin RCom and Tencent Meeting are already widely used by enterprises, WorkBuddy provides a new way for us to monetize our enterprise relationships. On the consumer front, we recently released a prototype of Xiaowei, which delivers an embedded and context-aware agent AI experience within Weixin, leveraging Weixin's social graph, knowledge graph, merchant reach and payment functionality. Xiaowei is powered by the Weixin customized model, WeLM, built with a focus on user privacy, Weixin specific use cases and cost efficiency.

Xiaowei can help users navigate and derive insights from Weixin's diverse content universe in a personalized and efficient manner. Xiaowei can also leverage Weixin's unique mini program ecosystem to help users discover products, make purchase decisions and place orders, laying the groundwork for an agent-to-agent transaction move. While the prototype can technically handle advanced agent workflows, we currently configure Xiaowei to require user intervention and multiple step confirmations as safety measures. Xiaowei will be rolled out to broader user base in a phased approach as we work on several core initiatives to elevate the user experience.

These include upgrading Xiaowei's dialogue, memory and recommendation capabilities, expanding service and content integrations, scaling our AI infrastructure and upgrading our harness to support a significantly larger user base. As we upgrade Weixin for the AI era, we can do it in a cost-efficient way, and we're confident that AI will over time accelerate the growth and thus the monetization of the entire Weixin ecosystem, generating attractive return for us.

Turning to Yuanbao. We are focusing on improving its capabilities and user experience, particularly in search, speech recognition and text-to-speech functionality. We're also improving its ability to address broader long-tail AI needs of consumers, including multimodal generation. Yuanbao plays an important role in the co-design flywheel as its conversational use cases generate valuable feedback to help improve our Hunyuan family of models. Over time, functionalities developed and owned by Yuanbao can become atomic capabilities for use in other Tencent products such as WorkBuddy, CodeBuddy, Weixin and QQ Browser.

And with that, I pass on to James.

Thank you, Martin. For the quarter, total revenue was up 11% with social networks contributing 16%, domestic games 23%; international games 9%; marketing services 21%; and FinTech and Business Services 30%. Our gross profit was up 13%, within which VAS gross profit increased 14%, Marketing Services 21% and FinTech and Business Services 9%. Value-added service revenue was RMB 98 billion, up 8% year-on-year. Within which the social network revenue was up 1% to RMB 32 billion, driven by increased revenue from app-based game item sales, partially offset by decreased revenue from long-form video subscriptions, where revenue decreased 6% year-on-year.

However, our exclusive drama series, The Lead, was the most watched drama series across all video platforms in China in the second quarter. Audio subscription revenue increased 8%, driven by higher music ARPU and enriched content stemming from the inclusion of Ximalaya. We facilitated users discovering new music by enabling one-click access from video accounts to QQ Music. In May, we completed the acquisition of Ximalaya. By bringing Ximalaya into Tencent Group, we can enhance Tencent Music's resilience, deepen the content supply relationship between China literature and Ximalaya and provide users with new content formats, including audio books and podcasts.

Domestic games revenue grew 17%, primarily driven by Delta Force, VALORANT PC, VALORANT Mobile and Rocu Kingdom World. International Games revenue was down 1%, although up 4% in constant currency terms as revenue growth from [indiscernible] and VALORANT PC was offset by revenue decreases from 2 Supercell games. For communications and social networks, video accounts total time spent grew over 20% in the second quarter, benefiting from enriched content supply, upgraded interactivity and the introduction of a new multivariable content ranking system. We've added content that appeals to younger users through IP partnerships with game studios, music labels and TV shows. And we've provided new revenue sharing opportunities for creators, expanding the population of creators that generate direct revenue from within the video accounts.

MiniShop's GMV increased within which GMV generated from Weixin's centralized e-commerce gateway page grew significantly. For MiniShop's merchants, we introduced marketing tools such as Lucky Draws, helping them to enhance brand awareness and drive product discovery. And for MiniShop's consumers, we enhanced rewards for repeat shoppers to increase customer life cycles and thus customer lifetime value to merchants. On domestic games, DeltaForce achieved lifetime high average DAU in the second quarter, driven by the Burst Fest campaign, the game's first professional esports final and a global 20 versus 20 tournament.

In terms of production, the Delta Force team have integrated AI across multiple workflows, including using data agents for performance analysis and the Hunyuan 3D model for asset generation. VALORANT PC also achieved lifetime high average DAU in the second quarter, benefiting from the Skirmish: Ascension mode with round-progressive weapons and the Summit map with droppable walls. The game expanded its reach by influencer collaborations, on-the-ground city events and promotions in over 10,000 Internet cafes.

Among new games, Roco Kingdom World ranked fifth by average DAU and eighth by gross receipts across all mobile games released industry-wide in the second quarter, making it the highest ranked new title released year-to-date. The game has maintained a rapid content delivery cadence since launch, adding 100 creatures and expanding the map with 7 new regions. On July 9, we released Runaway Evolution. This game is adapted from Rust, a survival open world crafting game on PC that has generally ranked among the top 20 games on stream by concurrent users for the past 8 years, thanks to its unique high-risk, high-reward gameplay in which players compete to outlast the other players on their server in 1 week compared to Sprint.

Runaway Evolution seeks to tailor this gameplay for China market preferences by availability on mobile as well as PC devices and via a sandbox safe for new players. Among our international games, League of Legends DAU increased year-on-year in the second quarter, primarily driven by the ARAM: Mayhem mode. We launched League Classic, a nostalgia mode that reengages long-time fans by recreating early era gameplay with pre-rework champions, classic runes and the original Summoner's Rift map layout.

Warframe's DAU grew year-on-year and gross receipts achieved a lifetime high in this quarter, benefiting from new Wolf-themed Prime Warframe and a new storyline, Jade Shadows: Constellations. Arrows: Puzzle Escape, a maze clearing game developed by MiniClip's subsidiary, Lessmore, was the most downloaded mobile game globally in the second quarter. Arrow's success demonstrates that the innovative capabilities of MiniClip's family of studios, supported by MiniClip's publishing expertise can together pioneer and break out leaders in new genres of casual games.

Arrow's monetizes via in-app advertising, so we report its revenue in our Marketing Services segment rather than the international gaming subsegment. Adjusted to include Arrows and other in-app advertising game revenue in the prior year and current periods, our international games year-on-year revenue growth would have been 4 percentage points faster than the disclosed figures. For Marketing Services, revenue grew 22% year-on-year to RMB 44 billion, driven by higher eCPM and impressions.

Most major categories increased their marketing spending with us, including e-commerce, Internet services and local services. We upgraded AI Marketing Plus end-to-end execution capabilities to better support closed-loop Mini Shop and Mini drama advertisers. For example, AI Marketing Plus now enables Mini shop owners to automatically select products for promotion, generate product-relevant ad creatives and then run smart bidding to buy inventory for those creatives. We significantly scaled up the parameters of our advertising AI recommendation system to capture user interest with greater granularity and thus improve ad conversion rates.

Video accounts ad impressions grew rapidly year-on-year driven by higher video views and ad load, although ad loads remain well below the short video industry average. Mini Programs attracted increasing marketing spend for mini drama and Mini Game Studios. For FinTech and Business Services, segment revenue was RMB 60 billion, up 9%. Fintech Services revenue grew year-on-year, driven by increases in commercial payment, wealth management and consumer loan services. For Commercial payment, the number of transactions grew year-on-year, while the decline in value per transaction narrowed. For Wealth Management, aggregated customer assets increased year-on-year, benefiting from the popularity of automated investment strategies and thematic index funds.

Within Business Services, while we're still working through capacity constraints, our cloud revenue growth rate accelerated from high teens percentage year-on-year in the first quarter to low 20s percentage in the second quarter, benefiting from AI-related demand, international expansion and increased usage and pricing for general cloud services. AI-related demand translated into increased revenue across GPU rental, Model as a Service and Work boy and CodeBuddy token usage. Our international cloud business expanded rapidly using skills developed with CodeBuddy is enabling us to conduct customer cloud migrations over to Tencent Cloud faster than we could in the past, for example, on behalf of the leading telecom company in Indonesia.

And now I'll pass to John.

Thank you, James. For the second quarter of 2026, total revenue was RMB 204.8 billion, up 11% year-on-year. Gross profit was RMB 118.4 billion, up 13% year-on-year. Operating profit was RMB 67.3 billion, up 12% year-on-year. Interest income was RMB 4.2 billion, up 2% year-on-year. Finance costs were RMB 3 billion compared with RMB 3.9 billion in the same period last year, reflecting favorable ForEx movements and lower interest expenses due to lower average interest rates.

Our share of losses of associates and joint venture was RMB 10 billion for the second quarter of 2026, primarily reflecting our share of the fair value adjustment recognized by an unlisted investee from revaluation of this issued convertible redeemable preferred shares arising from increased valuation of the investee, which was excluded from our non-IFRS profit.

On a non-IFRS basis, our share of profit of associates and joint venture for this quarter was RMB 6.4 billion compared with share of profits of RMB 6.3 billion in the same period last year. Income tax expense increased by 3% year-on-year to RMB 11.7 billion. On non-IFRS financial figures, operating profit was RMB 75.6 billion, up 9% year-on-year. Operating profit, excluding new AI products was RMB 86.1 billion, up 19% year-on-year. Net profit attributable to equity holders was RMB 68.4 billion, up 9% year-on-year. Diluted EPS was RMB 7.433, up 9% year-on-year.

Moving on to gross margins for Q2. Overall gross margin was 58%, up 1 percentage point year-on-year. By segment, last gross margin increased by 4 percentage points year-on-year to 64%, driven by a favorable revenue mix shift towards high-margin internally developed games. Marketing Services gross margin was 57%, down 0.3 percentage points year-on-year as higher revenue supported by enhancements to our AI group and marketing capabilities largely offset higher costs, including depreciation and operating costs associated with expanding our AI infrastructure to improve ads and content recommendation. FinTech and Business Services gross margin was 52%, broadly stable year-on-year. On operating expenses, selling, marketing Selling and marketing expenses were RMB 11.9 billion, up 26% year-on-year due to higher marketing spend to support our games business and to drive adoption of our [indiscernible]. R&D expenses rose by 35% year-on-year to RMB 27.2 billion, primarily reflecting higher R&D spend to support 1-year model enhancements -- AI initiatives and development of AI capabilities across our products and services.

G&A, excluding R&D expenses decreased by 1% year-on-year to RMB 11.5 billion. At quarter end, we had approximately 116,000 employees, up 4% year-on-year and 1% quarter-on-quarter mainly driven by head count additions to our games and our technology platform, including AI-related headcount. Our second quarter non-IFRS operating margin was 36.9% Million percent, down 0.6 percentage point year-on-year. Non-IFRS operating margin excluding new AI products was 42%, up 2.8 percentage points year-on-year. [indiscernible] and Coolbuddy inference needs Weixin AI initiatives and development of AI capabilities of [indiscernible] products and services as well as to meet growing external demand for our cloud services.

Nonoperating CapEx was RMB 1 billion. Free cash flow was negative RMB 13.8 billion, reflecting large AI infrastructure CapEx and AI-related prepayments as well as seasonally lower games gross receipts. Excluding the prepayments for complete procurement, free cash flow would have been RMB 37.6 billion. Net cash position was RMB 58.2 billion compared with RMB 146.9 billion as at 31st of March 2026 reflecting capital expenditure payments of RMB 59.3 billion and 2025 dividend payments of RMB 41.6 million made during the quarter.

Thank you, John. We shall now open the floor for questions.

[Operator Instructions] The first question comes from the Robin Zhu from Bernstein.

I guess -- if we look at your latest quarter's CapEx, RMB 53 billion, it's a step-up from the previous quarter annualizes over RMB 200 billion if we just multiply by 4. How should we think about the D&A costs, the results from this? To what extent do you think this will be paid off from incremental revenues that come as a result of your investments in AI or is this essentially eating into earnings into the next few quarters? And would love to hear your thoughts on the time lags involved when it comes to the payback cycle, especially if we include some of the R&D costs incurred as well.

Thank you for the question, Robin. So given the surge in demand and therefore, rental pricing for compute, we could recover the depreciation almost immediately by renting the compute out to third parties as many Neo cloud businesses are doing. And we would then achieve a decent return in an immediate time frame. However, in reality, we're playing a different game or executing a larger strategy in that we're allocating a very substantial proportion of the new compute to building our own models to state-of-the-art status and also to deploying popular icing, bringing our own AI applications to market leadership in China. And our [indiscernible] is that by providing the superior intelligence that we can achieve through state-of-the-art models through market-leading AI applications, that superior intelligence then convert into superior economic returns over the longer term, for example, by selling tokens through the work by the application. So that's the path we've chosen.

So just to elaborate a little bit more on that, right. So I think at the time being, you can actually sort of look at the Tencent businesses and break it into 2 businesses. One is actually the existing core franchises, which actually -- solid growth and also with quite a bit of operating leverage. That's the high-quality growth track that we have been building, and we continue with that.

And then there's another new AI-native business that we're actually building. And the new AI-native business would involve, as James said, our own model as well as new applications that we're building and also sort of a corresponding compute infrastructure. And the financials you should look at there is the revenue and profit in relation to our core existing business. And we do separately disclose the investments in our AI native business as an operating line.

And then when you look at the CapEx, I would say the CapEx will be divided into 2 parts, too, right? One part is really in relation to our existing business, which you can -- just like in the past, right, you can just say, "Oh, this is the free cash flow in which we generate operating cash flow and there is a CapEx in relation to that. And that part of the business is still very, very cash flow generative. And then there is another set of CapEx, which is related to the new native business, which is essentially a lump sum that we need to invest in order to get our compute for model training in order to prepare for inference needs and in order to also order some more for building our AI compute and AI cloud business. So that's essentially what it is.

And the reason we're actually investing in all these compute is that we need that in order to essentially get the business kick started. And at the same time, when we make the investment, there's clear upside that we're seeing because our model is doing well. our new applications is doing well, and we also have a lot of demand for compute. Today, if we can actually allocate the compute towards leasing on the Tencent Cloud would actually sort of generate a lot more revenue and would generate a significant return from the CapEx. As a matter of fact, for the prepayment and for some of the compute orders that we have made a couple of months ago, today, we can actually sell that at more than 30% profit compared to the price that we paid just a few months ago. But we believe if we use this compute for building our own model and building our application and than allocating the compute for rental in that order.

Over time, we will build a very significant AI native business, and that will be hugely profitable as well as highly cash as well as return generated for Tencent. So that's the way we think about the business right now.

Got it. And if I may have a follow-up just on Workbuddy. I love to hear your thoughts on every AI lab is essentially incentivized to develop their own harness apps or some kind. And your thoughts on how the market breaks down between first and third-party harness apps, how you would like to set up WorkBuddy to compete against these first part of harnesses and whether WorkBuddy in your mind is a piece of enterprise software that sits next to Tencent meeting docs. Or is this a new platform play that essentially becomes a marketplace for AI in the future?

Yes. Well, I think it is indeed a new platform that it's a very flexible work base for agentic AI. The core purpose is actually sort of it would solve all the productivity need of office workers and of all kinds of people who engage in their own businesses, right? One person companies and the like. And below that, there will be a harness, which actually helps the users to make use of the capability of different models to solve the agentic problems of the users.

And over time, there will be many models serving the users through WorkBuddy. There will be many skills developed over time by all kinds of different developers. And the purpose is actually solving productivity problems and then the platform itself would make use of all kinds of different tools and models available to do that. And then of course, we are the orchestrator, right? So we can actually choose the right model and choose the right skills to help users solve the problems. And we choose that to make sure that the work is done perfectly, but at the same time, it will be done also very economically, right? And will be one of the models that will be provided by WorkBuddy. But at the same time, if you can actually solve a lot of the user problems, right, then -- and it [indiscernible] effective then [indiscernible] would actually be one of the main models within the WorkBuddy, but it would not be the only model.

Thanks, Robin. We will take the next question from Kenneth Fong from UBS. .

I have a question regarding the Xiaowei development. So could management share any preliminary feedback or challenges from the testing phase of Xiaowei and then from a commercial standpoint, how should we evaluate the net monetization potential, specifically as agents simplify the transaction path, we worry that it may just be shifting the exceeding volume away from traditional user self-performed transaction in mini program. over to the agents, which carry a higher computing cost without a meaningfully higher net new GTV and furthermore, would the short-term user Tencent journey in a way -- risk also lowering the high-margin ad impression inventory as well?

Well, I think all the risks that you said would not be relevant because we believe when AI enable the Weixin ecosystem to be more intelligent, and it can actually sort of help users to execute transactions, explore content and manage their daily life with a lot of AI right. Then the AI, the Weixin ecosystem, which is already very rich and powerful will become even more useful to users, right? So if you imagine the time when QQ was a communication and social tool in the PC stage. And then when we get into the mobile age, then Weixin appears and Weixin essentially sort of ecosystem magnified QQ's value by more than 10x, right, because it's enabled in the mobile age and it becomes mobile first.

So when we look at AI, it would lead us another huge opportunity for the Weixin ecosystem to be first enabled by AI. And over time, it will be AI first application ecosystem. And when that happens, users would have a lot of great experiences like right now, you actually sort of you have to type and you have to sort of navigate through clicks in the future if you just tell Xiaowei one instruction and Xiaowei can go off and help you execute the transaction and execute your instruction and that would be an incredible experience for the users. It would also be an incredible empowerment for the entire ecosystem. So we believe if we can deliver that experience, if we can control the cost of that delivery.

And if you look at the design of VOM is actually for privacy, for cost efficiency and for making sure that it can execute within the Weixin environment, all the needs of the users right now. And if we can do that, then we can really empower Weixin for the AI age under controllable cost. And when that happens, Weixin's ecosystem would expand and that would translate into a lot of value just based on the current monetization mechanisms within Weixin. And I think that's the future that we are seeing. And with the launch of the prototype, we grow more and more confident about that will be happening.

And I have a follow-up question on the AI cloud with domestic API token prices [indiscernible] rapid commoditization. So -- and also China cloud market remains structurally price sensitive. So how do we think about the margin profile of Tencent AI cloud currently compared to, say, us and pass offering. And as this gradually scale up as AI adoption scale. So how should we also think about the margin progression going forward?

Well, it is true that domestic token prices are low, but the domestic token manufacturing costs are also extremely low, and I think, much lower than widely perceived or externally estimated. So the token business, it can be positive gross margin at these low token prices because the cost is low. And if you look at the gross margin for the paying users of work by the -- where you look at the gross margin for our model as a service, then the gross margins today are already comparable to the gross margins for Tencent Cloud overall. .

Of course, WorkBuddy body in aggregate has a lower gross margin because there's a proportion of free users whom we're subsidizing to drive market share and market growth. But on the paying users, we're generating a pretty good gross margin right now. And on your broader concern, it is true also that the China cloud market is price competitive. But that environment has changed greatly in the last several months as the input costs, particularly for memory have gone up. So we have been increasing the prices we charge to our customers. We increased prices across the board in May for Tencent Cloud. And beyond those headline price increases, we've also been more substantially reducing discounts. So the overall pricing environment in cloud in China is not as difficult as it's been in the past.

Thank you, Kenneth. We will take the next question from Ronald Keung from Goldman Sachs.

So two questions. I think first on the [indiscernible] model. Just want to hear, after the progress of [indiscernible] 3, which is on cost efficiency, I would say, in very good in agents. Then where will [indiscernible] 4 differentiate itself as we look into a, let's say, RMB 3 trillion permit-size class is looking walk crowded in the next few months. So which category are we looking or which segment or differentiation are we thinking for again.

And then a second question is on the CapEx and the focus on our AI initiatives. But looking at some of our U.S. peers, where there has been shift in strategy on the hyperscaler business. I just want to hear what stage or time line that we think we may focus more on cloud as a potential high ROI business that is worth prioritizing more CapEx on and some similarities and differences that we see potential in cloud versus what home USPs have shifted that focus more from applications to cloud for some of our peers. So 2 questions.

If you look at the Hunyuan 3 , right, Hunyuan 3 is a very small model, even in today's terms, but it's actually sort of very widely used, right? So I think there are a number of characteristics of Hunyuan 3, which is it actually has the capability of beating -- the matching or beating much larger models. That's one. And two is it's focused on use cases rather than just benchmark beating. And as a result, it has become much more useful than a lot of models of the same size or even bigger size. We believe that's a principle that we will be applying to Hy4 as well. So when Hunyuan 4 comes out, it will be a bigger model and it will be able to beat models of bigger size, and it would also be extremely useful and more useful than Hunyuan 3 and we believe that would actually take us into the next stage of being able to provide much better intelligence to a lot of our users.

And bear in mind that we also have products which are codesigning with model. So when Hunyuan 4 comes around the products that would be using when Hunyuan 4 would actually become even more powerful and even more useful than what they are today, and that would actually provide a very significant lift for the products that it's powering. So I think that's sort of the path. And when Hunyuan 4 is only sort of another stop right now and we'll be sort of upgrading to Hy5. So as we continue to progress we will be approaching -- so at some point in time, we'll definitely sort of be able to reach SOTA.

And once we are there, we would also have a lot of models of different sizes that will be able to solve different kinds of user problems at the different level of model and cost efficiency. And at the same time, we have multiple models that can be used for codesign without different products, and that would help to make the products feature rich and help to make the models -- the products powerful as well as the speed of execution will be fast. So I think that's what we envision when Hunyuan 4 and then subsequently Hunyuan 5 to be like.

And in terms of your second question about allocating CapEx between different use cases, including Tencent Cloud. So the immediate primary use case for the CapEx is for training bigger and better Hunyuan models in the coming months, as Martin discussed. But important secondary use case is providing inference for the use of Hunyuan models as well as DeepSeek and other models behind work body. And so the intention of that work by the initiative is primarily to drive adoption of what we think is a strategically important application with critical feedback loops back to our model and our broader ecosystem but it also has the happy effect of generating revenue upfront.

Now from accounting perspective, the majority of the work body sending by users is on subscriptions. And so similar to games and some of our other businesses, there's a lengthy time lag between the cash receipts coming to us from the users and those cash receipts translating into reported revenue, but we are seeing a substantial ramp in the cash receipts today, and that will translate into reported revenue growth for Tencent Cloud as we move through the year.

And then towards the end of the year and into next year, we'll also have sufficient GPU ASIC capacity to step up in terms of Tencent cloud renting out bare metal GPU or providing model as a service. But within those opportunities, renting out GPU model as a service, and then token production, WorkBuddy, we think that it is a token production for WorkBuddy that carries the most enduring economic value to us. And that's why we're prioritizing it today. Thank you.

We will take the next question Alicia Yap from Citi Group.

Congrats on the solid results. First question is on the Xiaowei. Could management elaborate on your comment on the agent to agent transaction loop. Will this concept lead to the long-term visions for fully autonomous agents ecosystem within the waiting? And then management also highlight that you will explore the on-device inference for Xiaowei. So what are the challenges and the benefits of this approach. And then is this on device inference approach and other reasons why the proprietary VLN malls is more suitable empowering the Xiaowei rather than the external model.

And then a quick follow-up is on your marketing service revenue. So this quarter, the growth rate accelerated to 22%. Should we expect this ongoing upgrade of the ad tech and also this automated campaign to further support this growth momentum. So any further future benefit that you would anticipate from the deeper integrations into your Hunyuan 3 model.

Yes. So on the agent to agent transaction, I think we are envisioning a future in which a lot of users would be executing their instructions and over time, transactions via Xiaowei and via agents, right? And in the past, if you think about the Weixin ecosystem is users interacting with content, interacting with mini programs themselves. And in the future, if they can actually send a complex instruction to an agent and an agent can actually start helping the user to execute transactions. And a lot of the mini programs, a lot of the merchants would actually sort of also have agents, which over time can interact with the agent of the users.

And longer term, there will be even user. Each user has got an agent and they can interact with each other to execute transactions. So I think that essentially is what's possible for the future, and we're building the architecture for making that possible on a step-by-step basis. And in terms of on-device inference, I think it would, number one, be happening maybe step by step, and it will be only over the long run that most of the entrance will be happening on device, right? But I think at some point in time, it's not hard to imagine some kind of influence will be actually happening on device and some infants will be happening in the cloud. And over time, as the on-device compute becomes more and more powerful.

And as the model becomes more and more efficient, and you have more entrance happening on people's devices. And I think that would be going back to the normal state of the computing industry, right? If you think about the computing industry as well as the smartphone industry, right? Most of the compute, right, which is CPU actually happens on device. And the cloud actually is sort of only is responsible for a small part of the compute. But in this initial phase of new AI infrastructure, most of the compute because it has to be sort of very powerful, right, and the problem of getting enough compute on device, getting it cheap enough and also getting a power efficient enough, has not happened yet. So that's why everything happens on the cloud.

But there will be a time in which more and more GPU capability will be put into everybody's phone and computer. And when that happens, then more and more inference will be happening on the device and that will be sort of going back to the time when it's actually the software, it's actually the model that becomes much more important. And the return for running modest and the return on renting applications would be higher because the compute CapEx will be just borne by the model company, but it's borne across the ecosystem. And I think that would definitely happen at some point in time and were building and preparing for that.

And on your marketing services question, our advertising revenue growth has ticked up and ticked down in the past, and it will continue to tick up and tick down in the future. I wouldn't sort of straight-line extrapolate anything. And there's a number of reasons. One is that the sort of obverse of the comments I made about in-app advertising games being a drag on the international game segment revenue growth versus where it would otherwise have been, is that they did contribute about 2 percentage points to the advertising segment revenue growth this quarter.

And these in-app advertising games are sort of new product for Tencent to some extent, a new product for the world. And so we don't have the same degree of clarity on what the growth trajectory will be for the advertising game contribution as for or sort of conventional marketing services revenue. In addition, the China consumer and therefore, advertising market remains choppy and there are some economic or consumption headwinds that may have an impact on advertising trends.

That said, we have been outperforming the overall China advertising market, and we're confident we'll continue to do so by a substantial margin given the upside to us from deploying AI targeting given the fact that engagement, especially for our key video accounts inventory is increasing at a good rate. And given we're early in the evolution towards more closed-loop advertising that drives much higher at pricing.

We will take the next question from Alex Liu from Bank of America.

I have only one question. So we noted that Tencent has recently increased the buyback. The buyback activity started from May, while at the same time, the CapEx has been accelerated meaningfully as well. So we understand it's still in the relatively early stage in AI investment cycle. But with that in mind, how should investors think about Tencent's capital allocation priority into the next 12 to 24 months?

I think that -- I note that our capital allocation will be dynamic and reflective of the environment that we see. And so if we identify that there's superior returns from the capital expenditure from increased smart compute and then using that compute to build the model, renting out that compute for work by de tokens, renting out that compute for model as a service, then we'll steer more cash towards the capital expenditures that we had in the past and therefore, potentially less cash towards buybacks, but it will be a dynamic situation.

And the other thing Alex, I do want to stress is that when we look at the CapEx that we allocate for building the AI native business, it is more of a sort of a lump sum that we're going to be investing this year and next year. And then I think one should not assume that it will be sort of every year because sort of the model building part is more of a fixed cost that you actually sort of you have to get enough compute, but it would not be sort of every year, you have to invest more and in terms of the insurance compute, yes, we need to have enough so that we can generate the tokens and we can sort of build a compute business, right?

And but we will only keep on investing if it generates a great return, right? If not, then this is actually sort of the amount that we're going to be investing and then sort of the additional investment in CapEx would actually be tied to sort of what kind of returns that we'll be generating from that business. And so in order to pay for this lump sum, then it should not be just sort of measured against our operating cash flow. It should be measured against how much cash we have on our balance sheet, how much investment portfolio we have on our balance sheet and then the operating cash flow and then a prudent level of debt capacity. So all these would come into play in terms of paying for this initial part of compute investment.

It is [indiscernible] for supplement on CapEx and return consideration. We will move on to the next question from Alex Yao from JPMorgan.

My first question is on Hunyuan flagship strategy. The Hunyuan 3 competes on cost efficiency rather than raw capacity capability. If you succeeded in building a truly frontier level model, which should be larger and more expensive to run, what specific business value with that create that the current 3 cannot deliver today whether a more capable wishing agent or a stronger advertising performance or enterprise customers? And what does that opportunity justify a major increase in training spend over the next 12 months?

Okay. Well, let's be very clear. So Weixin model and the strategy -- the position is very different, right? Weixin agemt doesn't really require or depend on Hunyuan's sort of new regions SOTA status. Weixin's design as we have said a few times is actually centered around user privacy and focusing on solving all the necessary interactions and agentic needs within the Weixin environment and also for cost efficiency. So that's its positioning.

Now the SOTA status would actually allow us to be able to build a very significant token business. And at the same time, it will also empower WorkBuddy to be able to complete even more challenging and more value-added services and operations for users. And one of the things that we actually sort of focused on WorkBuddy is actually not just saying, "Oh, it's an enterprise software and it would just do all the things that people can do today. It's actually sort of constantly looking for value-added use cases so that we can really deliver additional value and return for the users.

And in some cases, even help the users to make more money, right? And if we can do that, then there will be a lot of business models that we can unlock, right? So I think that's what we can also achieve with SOTA model. And at the same time, once we reach soda, we can actually start creating a lot of the other models, which can perform specific tasks for users at different levels of cost efficiency curve, still at the frontier curve, right? And that would actually help us to cater to the many different needs of intelligence for users. And that -- at each level, the cost will be different, but we will be able to generate a margin because we control the model, we control the inference cost, we control the compute. And that's, I think, what we are envisioned for our future generations and models to be able to achieve.

My follow-up question is on AI products economics. The new AI product drug rose from roughly RMB 8.8 billion in first quarter to about RMB 10.5 billion this quarter. Can you walk us through how you manage that investment, do you run these products to spending envelope or to return thresholds or to a strategic position and what signals whether usage revenue traction or unique economics would cause you to step investment up further, we'll begin shifting product from investment mode to harvesting mode.

Well, at this stage is actually very dynamic. And I think we would be investing prudently until the point that we actually see breakout opportunities, then we may step up the investment. So I think that is essentially the way we look at it, right. So it will be a certain percentage of our profit. But if -- clearly, we see that the pedal, it would actually generate a lot of returns then we may step the pedal. But the over -- we do believe, right, it is a business that Neo has to run for a long time.

So we'll be investing for the long run. And over time, we believe the economics would actually start coming in. And at some point in time, it would actually be able to turn into profit. I think more important is that today, if we just switch the model to just renting our compute, it will be actually not loss-making, it will be profitable. So I think we always have that fall back option right. So I think that's sort of something that we -- that's why we feel countable.

It's also the case that we dynamically reprioritize the spend within the budget or within the envelope. And so if you look at where the RMB 8 billion in the first quarter flowed in terms of user acquisition spending and so forth and which products it supported versus where the RMB 10.5 billion in the second quarter flowed there was actually a very big change because we identified that WorkBuddy was breaking out. And therefore, we are aggressively prioritized WorkBuddy while deprioritizing some of the other products in that new AI product portfolio.

And you can't assume there is an overlook at the back of our mind.

Thank you. We will take the last question from Gary Yu from Morgan Stanley.

I have one follow-up on the AI investment. I understand the priority or model training for WorkBuddy then maybe cloud. Where does Xiaowei fits in terms of inferencing capacity required to support Xiaowei when it's launched? So that's my first question. My second question is on management field out timing and visibility of monetization and ROIC for these new AI initiatives. And particularly, should we expect close to nettable earnings growth in the near term and when should we expect the operating profit, including AI investment to grow even faster than excluding the AI investment.

I think for Xiaowei, the envelope of investment on the cost side would be less than what we actually invested in [indiscernible] on an ongoing basis in the past, let's say, a year. So I think that is the way we think about it. So the cost would be quite manageable. But as the experience keeps getting better and better, the return will actually start flowing in and it would actually sort of outweigh that investment pretty quickly.

And in terms of guidance, I don't think certainly we are in the business of actually providing sort of that specific guidance right. I think we have talked a lot about how we think about the business and how we think about there is an envelope of investment that we will be adhering to it will be kind of disciplined in the same way as Tencent has always managed our business. But then if we clearly see great opportunities to build a very significant and profitable business for the future, then we would actually make the investment. And we also sort of have the comfort that if we actually just move on compute into the compute right now, we can generate revenue, profit and return very quickly. So that actually sort of is a thought back position anytime that we choose to do that.

We are now concluding the webinar. Thank you all for joining our results today. If you wish to check out our press release and other financial information, please visit the IR section of our company website at www.tencent.com. The replay of this webinar will also be available. Thank you and see you next quarter.

Good day, and good evening. Thank you for standing by. Welcome to Tencent Holdings Limited 2026 First Quarter Results Announcement Webinar. I'm Wendy Huang from Tencent IR team. [Operator Instructions]. And please be advised that today's webinar is being recorded.

Before we start the presentation, we would like to remind you that it includes forward-looking statements, which are underlined by a number of risks and uncertainties and may not be realized in the future for various reasons. Information about general market conditions is coming from a variety of sources outside of Tencent.

This presentation also contains some unaudited non-IFRS financial measures that should be considered in addition to, but not as a substitute for measures of the group's financial performance prepared in accordance with IFRS. For a detailed discussion of risk factors and non-IFRS measures, please refer to our disclosure documents on the IR section of our website.

Now let me introduce the management team on the webinar tonight. Our Chairman and CEO, Pony Ma, will kick off with a short overview. President, Martin Lau; and Chief Strategy Officer, James Mitchell, will provide a business review; and Chief Financial Officer, John Lo, will conclude with financial discussion before we open the floor for questions. I will now pass it to Pony.

Thank you, Wendy. Good evening. Thank you, everyone, for joining us. We start 2026 by making significant initial progress on our new AI products so as continue to utilize AI to grow our existing core business. They review model built by our revamped team of AI researchers on the architected AI infrastructure is a leader in its parameter size class, delivering practical utilities and cost efficiency and has been top ranked in open router token measure since April 28. Our productive AI agent solutions have attained early adoption, and we believe that our work body is currently the most widely used productivity AI agent service in China.

Our core businesses continue to grow their engagement, revenue and profit, providing the cash flow to fund our AI investments as well as use cases for future AI deployments. Looking at our financial numbers for the first quarter. Total revenue was RMB 196 billion, up 9% year-on-year. Adjusting for the impact on revenue recognition for our value-added services from the later Spring Festival this year compared to last year, total revenue would have increased 11% year-on-year. Gross profit was RMB 111 billion, up 11% year-on-year. Non-IFRS operating profit was RMB 76 billion, up 9% year-on-year. Excluding new AI products, non-IFRS operating profit was RMB 84 billion, up 17% year-on-year and non-IFRS net profit attributable to equity holders was RMB 68 billion, up 11% year-on-year.

Turning to our key services. For communications and social networks, combined MAU of Weixin and WeChat grew year-on-year and quarter-on-quarter to 1.4 billion. For digital content, Tencent Video solidified its leadership in animated series with animated titles ranked top 10 industry-wide in the first quarter of 2026. For games, Honor of Kings and Peacekeeper Elite achieved record highs in gross received during the first quarter of 2026, while newly released creator collecting game, Roco Kingdom World achieved breakout success. Tencent Cloud's AI agent solutions achieved rapid growth and healthy retention rate.

Now I will hand over to Martin for the business review.

Thank you, Pony, and good evening, and good morning to everybody on the call. For the first quarter of 2026, our total revenue was up 9% year-on-year. As Pony mentioned, our total revenue growth was impacted by the later timing of Spring Festival this year compared to last year, which shifted to more games-related revenue recognition to future periods. Adjusting for the timing of the Spring Festival, total revenue would have been up 11% year-on-year on a like-for-like basis.

By segment, VAS represented 49% of our total revenue within which Social networks subsegment was 16%. Domestic Games subsegment was 23% and international games was 10%. Marketing Services was 19% of total revenue, and FinTech and Business Services was 31%. Our gross profit was up 11% year-on-year in the first quarter to RMB 111 million. VAS gross profit increased 9% year-on-year and represented 54% of our total gross profit. Marketing Services gross profit increased 19% year-on-year, contributing 19% of total gross profit. And FinTech and Business Services gross profit increased 13% year-on-year, contributing 28% of total gross profit.

Now a bit of update on our AI initiatives. Over the last 6 months, we have made significant progress on our Hunyuan large language model, but I would say it's just getting started. We started the initiative by completely overhauling our foundation model team, centering around newly added elite AI researchers and engineers with deep expertise in large language models. Our new team is young, energetic and cohesive, enabling us to make progress quickly in this highly dynamic AI era.

In February, we reengineered the system and process for pretraining and reinforced learning from the ground up. We rearchitected the infrastructure to support robustness, scalability and efficiency across pretraining, data and reinforcement learning. On data, we expanded our data set significantly and strengthened our data collection, cleansing and synthesis capabilities with a focus on data quality. On training, we upgraded the process for pretraining and supervised fine-tuning, and we scaled up reinforcement learning. And for evaluation, we're moving away from chasing public benchmarks that can be gained. Instead, we evaluate our model through the latest Sams, human tests, product feedback and in-house tasks to see how the model actually performs in the real world.

In April, we launched Hunyuan 3 Preview, when we set out to build this model, the purpose was to build a cost-efficient and solid model for diverse applications and derisk scaling toward larger models. The core design principles behind Hunyuan 3 Preview was to deliver comprehensive intelligence and cost efficiency, optimizing it for real-world deployment. We moved beyond narrow expertise and towards comprehensive intelligence such as integrating reasoning, long context understanding, instruction follow, dialogue, coding and 2-use capabilities. And by codesigning inference with model, we're able to reduce costs significantly so that the intelligence is economical enough to be used at scale.

Hunyuan 3 Preview has delivered on these expectations. The model has already become a leading reasoning model in China and has proven effective in real-world software engineering and other productivity agent tasks. Internally, the model has been deployed across 131 widely used internal products, including Yuanbao, QQ and WorkBuddy, providing valuable feedback and iterative improvement vehicle design process. And externally, Hunyuan 3 Preview has been well received by users and developers in real applications. It has ranked first among all models available on open router by token usage since April 28 and continued its lead even after its free period ended on May 8.

While significant strides have been made with Hunyuan 3 Preview, we view this as merely just the first step for Hunyuan large language models. The next step is to scale up to larger models. Our Hunyuan team is already working on a larger parameter model, leveraging our infrastructure and learnings from Hunyuan 3 by aggregating bigger and better data sets and scaling more powerful reinforcement learning, we can strengthen the model's contextual understanding, enhance its agent capabilities in areas, including coding and increase the model's general intelligence.

Through codesigning and collaborating with other Tencent product teams, we are optimizing data set selection and focusing reinforcement learning for high-value use cases. Beyond foundation models, it has become increasingly evident that agent AI represents a breakthrough use case after AI chatbots have become popular. Their agents are more valuable in uplifting productivity from initial use cases supporting programmers in creating code, such as with our product CodeBuddy to now catering to a wider range of workloads and occupations such as with Claws and WorkBuddy. These breakthroughs were made possible by more powerful models and by the hardness infrastructure that allows models to utilize tools and act as interfaces that enable users to manage agents effectively.

Our platform inherently has many benefits of hosting AI agents as users can control AI agents through our communications and browsing interfaces such as Weixin, WeCom, QQ -- Yuanbao and QQ Browser in addition to third-party applications. Users can also choose which model to use from a wide range of models based on their own needs and preferences on token cost and performance. And in the future, AI agents will be able to access our Mini Programs ecosystem using Mini Programs codes as AI skills.

Tencent has established an early lead in agent AI deployment evidenced by the leading DAU of our product, WorkBuddy. While early in adoption cycle, CodeBuddy and WorkBuddy are already achieving strong organic growth and high retention rates among active users and paying users. The high time spent and high-frequency interaction with AI agents among early adopters act as a virtuous feedback loop to Tencent, enable us to identify and provide complementary software and services, which in turn drives increased AI agent usage among a broader enterprise and prosumer user base. As users utilize more AI agents for more complex tasks, paying user conversion increases, resulting in rapid growth in token usage on Tencent Cloud in recent weeks.

Now with that, I will pass on to James.

Thank you, Martin. Turning to business segments. Value-added services revenue was RMB 96 billion, up 4% year-on-year. Social network revenue was down 2% year-on-year to RMB 32 billion, reflecting decreased reported revenue from app-based game item sales in China arising from the late Spring Festival. Long-form video subscription revenue decreased 2% year-on-year due to fewer releases of top-tier drama series. However, we cemented our leadership in animated content with 8 of our self-commissioned series ranking among the top 10 across all video platforms in China during the quarter.

We believe Tencent Video possesses competitive advantages in creating animated series, including our ability to cross over IP from China literature and our games into animated IP and our use of technology tools such as Unreal Engine and generative AI for storyboarding and producing the animated content. Tencent Music subscription revenue increased 7% year-on-year, driven by growth in ARPU and subscribers.

For domestic games, gross receipts grew at a teens percentage rate year-on-year due primarily to Delta Force, Peacekeeper Elite, Honor of Kings and Valorant Mobile. However, revenue growth of 6% year-on-year lagged the gross -- receipt growth as later timing of the Spring Festival shifted some revenue recognition into the second half of 2026. International game revenue increased 13% year-on-year, mainly driven by Clash Royale, Wuthering Waves and Valorant.

Moving to Communications and Social Networks. Our Mini Shops transaction volume sustained a rapid growth rate. To better support merchants selling branded products, we introduced incentives, including preferential take rates for brands, product subsidies and prioritize recommendations. Branded merchants GMV more than tripled year-on-year in the first quarter, particularly in key categories such as FMCG and beauty. For consumers, frequent buyers can use our new coupon sharing feature to share discount coupons with friends via chats, benefiting from Weixin's virality. And for content creators, we upgraded the matchmaking mechanism so creators can more efficiently outreach to relevant merchants promote the merchant's products in the creators' video accounts and official accounts.

On the AI front, we have enabled Weixin and QQ to act as communication interfaces for controlling AI agents, allowing users to orchestrate agents from mobile for complicated task execution on PC and cloud. We scaled up the number of parameters and enhanced the algorithm for video accounts content recommendation model, enabling deeper understanding of users' interest to recommend more personalized and relevant content and total time spent on video accounts increased over 20% year-on-year.

For Mini Programs, we've upgraded the developer toolkit architecture so users can better leverage AI plug-ins, including CodeBuddy to create and debug Mini Programs. And over time, will enable Mini Program code to evolve into skills for AI agent used within Weixin. Total query volume on Weixin search increased over 25% year-on-year, benefiting from foundation model powered ranking and broadening AI search coverage to include image-based queries.

Moving to domestic games. During the first quarter, Honor of Kings achieved lifetime high quarterly gross receipts, benefiting from top-tier outfits inspired by Chinese things and Ancient Silk Road culture. For Peacekeeper Elite, peak DAU reached a lifetime high of 90 million and gross receipts increased over 30% year-on-year. The expanding user-generated content platform within the game, a new class-based extraction mode and IP collaborations with partners such as Ferrari contributed to the growth in users and gross receipts. Delta Force also achieved lifetime highs in average DAU and gross receipts for the quarter, benefiting from a Cosmic Guardian Skin, the Morphosis season featuring a revamped Space City map and crossover promotions.

Among newer games, Valorant Mobile has consistently ranked among top 10 mobile games industry-wide since its launch in August last year. And during the first quarter, we released distinctive weapon items such as Ignite Capsule, which contributed to strong gross receipts. Roco Kingdom World, a creature collecting open world game released on March 26. In its first month since launch, the game has achieved over 13 million average DAUs and is sustaining high user retention rates with its mobile version consistently ranked among the top 10 mobile games in China by gross receipts.

Taking a step back from these individual game titles, AI provides increasingly helpful tools, facilitating our game developers to deliver more content and enhanced experiences. Currently, AI for games is most beneficial in areas, including accelerating 3D asset production and animation, enriching player experiences with intelligent in-game guides and delivering more realistic graphics via AI rendering techniques. Among our international games, PUBG Mobile's gross receipts grew year-on-year in the first quarter, benefiting from Eastern mythology outfits, brand collaborations and anniversary events. For League of Legends, Riots conducted a substantial revamp of the team processes and technology in the last 2 to 3 years, which are now collectively resulting in a faster velocity of big new content releases, including the popular ARAM Mayhem constant team fight mode, a well-received new season in for Demacia and the Renant Reign Exaltede tier outfit for the Champion Viego.

As a result, League of Legends is experiencing a resurgence in DAU and gross receipts. Wuthering Waves new season For You Who Walk in Snow delivered a new map content and characters, contributing to the games gross receipts growth during the period. And after a consolidation period, Rothstar's DAU and gross receipts grew rapidly year-on-year, benefiting from new abilities for [ Bies ] and upgraded broadcast and an improved trophy system.

For Marketing Services, revenue grew 20% year-on-year to RMB 38 billion with notable growth from Internet services, e-commerce and gaming. Revenue growth improved from 17% year-on-year in the fourth quarter as we deepened collaboration with e-commerce platforms and as advertising demand picked up in response to increased inventory from video accounts. Our automated campaign management solution, AI Marketing Plus powered around 30% of total marketing services spending from advertisers with us in the quarter.

We upgraded our runtime advertising recommendation models with a unified transformer-based architecture. This upgrade provides deeper understanding of user context and the intent while balancing model complexity with system efficiency.

By inventory, video accounts ad impressions grew rapidly year-on-year, supported by increased total time spent video views and ad load. We released more inventory of rewarded ads, which deliver high click-throughs for advertisers. Mini Game and Mini Drama Studios increased their marketing spend within Mini Programs. Specifically for Mini Games, we've introduced an instant play advertising format, enabling users to play the game within the ad without needing a redirection, which reduces friction in the new user acquisition process. And through our mobile ad network, we've made more rewarded or incentivized ad formats available to third-party app developers, which unlocks higher price bidders and thus more revenue.

Looking at FinTech and Business Services, segment revenue was RMB 60 billion, up 9% year-on-year. FinTech services revenue growth is primarily driven by commercial payment volume by wealth management services. For commercial payment volume, year-on-year growth was faster than in the fourth quarter of last year, benefiting from an ongoing increase in the number of transactions, but also higher value per transaction in categories such as retail and dining services. For Wealth Management, average assets per user and number of users each increased year-on-year.

Turning to Business Services. Revenue in the first quarter grew 20% year-on-year, driven by increased demand and better pricing environment for our cloud services alongside rising technology service fees generated from mini shops e-commerce. For Tencent Cloud, AI-related demand contributed to increased revenue year-on-year across GPU, CPU and storage. We upgraded Tencent Cloud's AI agent solutions with proprietary security infrastructure, skill hubs and interfaces, contributing to rapidly increasing usage and initial token monetization.

Tencent Cloud's international business grew its revenue over 40% year-on-year as we expanded our global footprint and captured demand for our Platform-as-a-Service solutions, including media processing services and TDSQL cloud database. And now I'll pass to John.

Thank you, James. For quarter 1 2026, total revenue was RMB 196.5 billion, up 9% year-on-year. Gross profit was RMB 111.3 billion, up 11% year-on-year. Operating profit was RMB 67.4 billion, up 17% year-on-year. Interest income was RMB 4 billion, up 7% year-on-year, mainly driven by growth in cash reserves. Finance costs were RMB 3 billion compared with RMB 3.9 billion in the same quarter last year, primarily due to higher ForEx gains and lower average interest rate.

Share of profit of associates and joint venture was RMB 3.6 billion compared with RMB 4.6 billion in the same quarter last year. On a non-IFRS basis, share of profit was RMB 7.1 billion compared with RMB 7.6 billion in the same quarter last year. Income tax expense increased by 6% year-on-year to RMB 14.5 billion on non-IFRS financial figures. Operating profit was RMB 75.6 billion, up 9% year-on-year. Operating profit, excluding new AI products was RMB 84.4 billion, up 17% year-on-year. Net profit attributable to equity holders was RMB 67.9 billion, up 11% year-on-year. Diluted EPS was RMB 7.364, up 12% year-on-year, outpacing non-IFRS net profit growth due to reduced share count after our share buybacks.

Moving on to gross margins for Q1. Overall gross margin was 57%, up 1 percentage point year-on-year by segment. VAS gross margin was 63%, up 3 percentage points year-on-year, primarily driven by increased revenue contributions from internally developed games. Marketing services gross margin was 55%, down 0.5 percentage points year-on-year, reflecting higher cost of revenue, including AI-related equipment depreciation and associated operating costs as we increase AI investments to deliver more relevant content recommendations in the future.

FinTech and Business Services gross margin was 52%, up 2 percentage points year-on-year due to improved revenue mix within fintech services. On Q1 operating expenses, selling and marketing expenses were RMB 11.3 billion, up 44% year-on-year, reflecting increased promotional efforts to support the growth of our AI native applications and games, including new games. R&D expenses rose by 19% year-on-year to RMB 22.6 billion, primarily due to our increased investment in AI, which drove high equipment depreciation and associated operating costs as well as higher staff force.

G&A, excluding R&D expenses decreased by 24% year-on-year to RMB 11.3 billion, reflecting a high base in the prior year period, which included a of RMB 104 billion share-based compensation expense related to the restructuring of an existing commercial arrangement at an overseas subsidiary. At quarter end, we had approximately 113,000 employees, up 5% year-on-year, driven by headcount additions to gains in our technology platform, including AI-related headcount and down 1% Q-on-Q, mainly due to lower headcount at our independently operated subsidiaries and in-house tech support subsidiaries.

On Q1 non-IFRS operating margin was 38.5%, stable year-on-year. Non-IFRS operating margin, excluding new AI products was 43%, up 3.1 percentage points year-on-year.

To conclude, I will highlight some key cash flow and balance sheet metrics. Operating CapEx was RMB 31.2 billion, up 18% year-on-year and 84% quarter-on-quarter as we accelerated investment in server infrastructure. Nonoperating CapEx was RMB 0.7 billion. Free cash flow was RMB 56.7 billion, up 20% year-on-year, driven by growth in games, gross receipts and advertising billings, partly offset by higher server infrastructure and compute spending. On a Q-on-Q basis, free cash flow was up by 67%, reflecting seasonally higher game gross receipts and the timing of certain seasonal accounts payable settlements, partly offset by higher server infrastructure and compute spending.

Net cash position was RMB 146.9 billion, up 37% quarter-on-quarter or roughly RMB 40 billion, mainly driven by free cash flow generation, partly offset by share repurchase of RMB 7.9 billion and net cash outflows of RMB 7 billion related to investment in other corporations. Thank you.

Thank you, John. We shall now open the floor for questions. We will take the first question from Alicia Yap from Citigroup.

Thanks for taking my questions. Two questions. First, since the release of Hunyuan 3 Preview, I think management also mentioned so the model has been deeply integrated to a lot of the internal core products, so including the Yuanbao, [indiscernible] and WorkBuddy. Then can management share some details on the performance enhancements that you have observed in these workflows since the adoption? So then additionally, what is the road map of integrating Hunyuan 3 more broadly into WeChat workflows? Will Mini Programs, enterprises will be able to leverage these agent workflows to improve their productivity and maybe future monetization?

Second question is with agents increasingly potentially replacing the traditional click-throughs on the web pages and also the apps, could management share your view on the future advertising pricing and also the resulting impact on advertiser budget? So what type of digital content or the web activities are likely to be -- remain more resilient, continuing to capture more significant user engagement? Are we thinking ahead and strategically maybe positioning our ad formats to adapt to this potential shift in the ad spending? So any thoughts or insight you could share would be helpful.

Thank you, Alicia. In terms of Hunyuan 3, we have given a pretty comprehensive overview of Hunyuan 3. And as you can see from the prepared remarks, it's more intelligent and it's actually very strong in terms of reasoning despite being a smaller model. And at the same time, it has significant improvement vis-a-vis Hunyuan 2 on agent capabilities. So with that, when we actually integrate Hunyuan 3 into the different products, the performance was actually quite, I would say, quite encouraging. The different products have all expressed and marked improvement in terms of the performance because they actually sort of see it from the user end. And the total token usage is actually at least 10x compared to Hunyuan 2, so that's the clear indication that Hunyuan 3 is actually well designed.

And at the same time, because it benefits from a co-designing process with some of the major products, for example, Yuanbao and WorkBuddy, right? So that's why it's well received by the products. In terms of the integration into the Weixin workflow, I think it will be a step-by-step process. And Weixin itself actually sort of have been always using some part of their products, Hunyuan 2 and they upgraded already to Henyuan 3. And in some cases, they use different models and they evaluate different models and evaluate what's the best model to use for their users, right?

So as Henyuan 3 continue to be getting better and better, then they will be adopting more. Now in terms of Mini Programs, I would say for the enterprises, one benefit is actually that they would be using some of our Hunyuan-enabled products such as coding or such as CodeBuddy as well as WorkBuddy, right? If these companies are actually using or the users are using such products, then they would actually be able to benefit from the improved performance of Hunyuan 3 and at the same time, in the future, when we start integrating Mini Programs as skills, right, to allow agents to have the ability to use Mini Programs as tools, then that would actually sort of add more traffic to these Mini Program enterprises. So one is internal, right?

When they use our own agent products, they can improve their own productivity. And the other one is external. It can actually help their Mini Programs to be used by more users and more agents going forward.

Alicia, on your question on advertising, which is an interesting question. It's certainly more of an issue potentially for e-commerce companies than it is for us because users actively choose and desire to spend their time watching short videos or listening to music or consuming content or chatting with their friends versus generally speaking, when users spend time on e-commerce, it's because they're trying to find the lowest price. It's not because they necessarily enjoy that process.

So to the extent that AI agents play a bigger role in the future in facilitating price comparison, then it's possible that users will spend less time on e-commerce sites and be less exposed to ads than they are today, while the AI agents can scan infinite listings and therefore, not influenced by ads the way that human beings with a finite attention span are influenced. All of that said, there's been many prior iterations of price comparison services, including search engines and the big e-commerce companies are generally thrived despite the existence of those price comparison services. So I think it's premature for us to sort of have a definitive view at this point on how it will affect our friends in the e-commerce industry. But we don't see it as a primary risk for Tencent. Thank you.

We will take the next question from Kenneth Fong from UBS.

I have a question on the ROI on AI investment. If we look at the global peers, they have been allocating 80% to even 100% of their operating cash flow to AI CapEx compared to us, which we invest roughly 35% in the last quarter. But however, many of them have experienced decline in free cash flow, ROE as the business become more asset heavy. So could management share or provide more quantifiable guidance on the AI-related CapEx for this year? And what KPIs are being used to assess the value creation and return on this investment?

Kenneth, so we are seeing increased demand, both from internal products as well as from external users of our model for our AI-related services. And we had previously guided that we'll be increasing CapEx this year versus last year, and we're now more affirmative, more confident in that guidance. And we and you should expect a substantial increase in CapEx, especially in the second half of this year as more China designed ASICs become available to us month by month through the year. On the KPIs, they differ product by product and business by business.

At a high level, for our existing activities such as advertising and games, the KPIs would be more revenue and profit related. For our new AI products, the KPIs would be more capabilities, how intelligent is our foundation model and usage, how much token consumption is happening on WorkBuddy related. And then for Tencent Cloud, where until now, we actually haven't had sufficient GPUs to begin to service the external demand, the KPIs will be more revenue and market share related.

We will take the next question from Alex Yao from JPMorgan.

I'd like to follow up with Kenneth's question just from a slightly different perspective. When you allocate financial resource to CapEx and AI investment, how do you evaluate the AI infrastructure spend internally? What is the ROI framework or payback period that you are underwriting these investments against and over what time horizon?

I think we provided some thoughts on how we view the sort of quantitative or qualitative return on investments in the previous answer. And there are certain products where we're taking a very sticky financial approach and others where we're more focused on the benefits to our franchise over time. I don't know if you want to sort of iterate on the questions. I may not have caught the full meaning behind the question.

Thank you, James. I mean, ultimately, the investment community needs to understand who pays the AI CapEx from what budget and over what time period or horizon do we expect to tap into those new commercial opportunities.

I think that in the history of Tencent, we have generally sustained good returns, and you can quantify that by looking at our return on equity over the last couple of decades, which has been a consistently high return on equity. But we have not got there by limiting each new product, each new service to very near-term quantitative return on investment targets. We have got there by managing the portfolio as a portfolio and by managing products over their full life cycle, not over any specific quarter or 12-month period.

And so there's been many products within Tencent, whether it's our expansion into games, the launch of Weixin, movement into payments that went through lengthy incubation periods where they had no return on investment, but we were confident in the franchise value creation. And then over time, they had more lengthy harvesting periods where we've been able to drive very healthy returns on that sunk investment. And AI includes a range of sort of shorter cycle investments as well as longer cycle investments.

And so if we buy GPUs and we deploy them into our ad tech, then that's a relatively short-cycle investment. The GPUs yield better targeting, higher click-through rates and higher revenue and profit on a pretty accelerated basis. On the other hand, when we deploy GPUs into our Hunyuan foundation model, that's something which we view as important for our franchise and where we're taking a longer-term view. But again, we don't manage each product on a quarterly basis. We manage the portfolio and we manage the products on a full life cycle basis.

I think just to elaborate on what James is saying, right, there's sort of a range of different ways to look at this, right? And if you look at the model training, it's basically an investment for the future, right? And there's probably not going to be very immediate return. But over time, the capability accumulates and it actually helps unlock a lot of different businesses opportunities. And then when you look at the products that we are launching, right, be it Yuanbao, WorkBuddy, CodeBuddy, right, there's process in which you have free services, right? And then over time, you may have revenue -- the business-oriented revenue can come faster than the consumer-oriented revenues.

So there will be sort of a return cycle on that. And then if you look at the business revenue sort of be it -- or the cloud revenue in the sense of [ PaaS ] or rental of compute, then there's a clear ROI, right? You have a depreciation cost and you usually put on some kind of margin and then sort of you rent out. So that would be sort of having a clearer return. And then when we have advertising, as James pointed out, right, we usually see very good return from those investments. So I think for different computes, there's different ways to look at it.

We will take the next question from William Packer from BNP Paribas.

Firstly, with domestic gaming your biggest revenue and free cash flow driver, could you help us think through how generative AI is impacting that business today? Is it driving incremental monetization by faster content creation cycles? Or is that a delayed benefit? And are you seeing cost efficiencies benefit the margins today? Or do you need to invest the initial phase limiting any benefit? And I have a quick follow-up. Thanks for the commentary on the CapEx outlook. Could you talk through any implications for the share buyback in the second half of the year?

Yes. So why don't I address those? As you hypothesize for our game business, generative AI enables us to produce more content faster. And that content is, in some cases, to enhance the overall player experience. But in some cases, it results in direct monetization. For example, if the content is a virtual outfit. And so that's what we are doing, and that's what we are seeing. And we think that we're a China leader and to some extent, even more so a global leader in terms of deploying that capability and achieving that benefit. And the objective at this point is really faster content creation and incremental revenue generation.

We're not prioritizing margin expansion per se. It's more that as we deliver the revenue uplift that we're seeing and if we can keep headcount fairly stable, then I suppose mathematically, that combination would tend to result in higher margins over time, but that's sort of a happy output rather than the intention of the process. And then in terms of your question about capital returns, we will be stepping up our investments in AI in response to the increased demand that we're seeing.

However, we do have a very cash-generative business, as you can see from the first quarter results. We also have a very substantial investment portfolio, and we're accelerating the process of liquidizing some of that investment portfolio and that will enable us to sustain buybacks going through the rest of this year. And at this point in time, we believe our share price is somewhat dislocated. And therefore, it's an opportune time for buybacks, a particularly opportune time for buybacks.

Next question comes from Robin Zhu from Bernstein.

If I could -- I have a couple of questions, so one, in terms of the changes that we've made to our data pipeline and training RL and so on. Do you feel now that having seen the release of Hunyuan 3, we're now on a more sustainable upward trajectory where we can deliver major updates, one major update a year, several smaller ones in between like some of the other labs. Are we there? Or is that still more of a work in progress?

And then second, just on the kind of philosophy of some of the AI product investments. I think one of the tensions in the U.S. has been -- I think OpenAI has been the big DAU player, whereas Anthropic has kind of gone after a small pool of high-intent power users, highly willing payers effectively. Just curious on -- I mean, Tencent obviously has historically been the former, but just curious your thoughts on kind of the relative merits of going down one path versus the other. And to what extent does the current kind of tokenizing phenomenon play into that pool?

In terms of the production pipeline, I think we have gone in pretty at length to talk about sort of how we felt it's actually making very good progress. If you look at Hunyuan 3, we have revamped the entire team, the production process, the infra and all the different major modules in producing great models, right, including the data pipeline, as you point out, the pretraining, the post-training, the RL as well as the eval. So -- and we have deliberately actually built a smaller model to basically validate all these different points, right? And the combination of this, right, when it's all integrated into Hunyuan 3 Preview is that it produces a pretty competent model at its size.

And we clearly see in each one of these modules, there's a lot of work that we could be doing. So I think we're happy with the results. To some extent, we are actually surprised by the speed at which it's done and the fact that it's actually proved to be useful, right? For a long time, I think a lot of models would actually come up pretty high in terms of the benchmarks. But then when it's actually rolled out to different products, people complain. And when you put the model to the developers and the user, right, people will use it, right?

So I think if you look at how this is received in the actual use cases, it's actually better than our expectation by quite a bit. And so with that, I think it builds a very solid foundation for us to scale the product -- the model to the next level. In terms of how we think about the different products, we felt this is actually sort of a very early stage in terms of AI diffusion, right? And we would see many different products coming up going forward. Initially, it was chatbot and everybody felt chatbot is actually the king of the product. And then suddenly, you have a coding that came up and this becomes sort of even more eye-catching and less significant use case because it's very high value, right? And now we are seeing sort of Agentic capability proliferating right?

And I think that would actually allow AI to be diffused to different industries, and you have many different agents coming up, which can help you to do work, right? And there's going to be new products coming up. So I think that would continue to propagate. And I think to some extent, right, you actually have to -- in the AI world, you actually have to find a high-value use case as opposed to sort of just purely focused on DAU because the difference between the AI revolution and Internet is that this is about intelligence and intelligence manifest its value in sort of how much people are willing to pay for it.

And at the same time, the intelligence is not free, right? In the Internet world, you basically sort of have mostly existing information. And then you also create some new information and content, but then that's a fixed cost and then sort of the variable cost for delivering is actually very small, right? You only have to pay for bandwidth and the compute sits on people's devices, right? And as a result, you can almost like go for infinite scaling. But in this case, right, every single delivery of a DAU actually cost you quite a bit.

And as a result, you can't just apply the same logic as Internet and apply it to AI. And I would say the ability to find high-value use cases is going to be as important, if not more important than just sort of blindly get a lot of use -- DAU and user time. So I think that is one important distinction. And as we think about it how to deploy our product and how to codesign our product with the models. So these are the kind of new considerations that we have to put into play.

We will move to the next one, Alex Liu from Bank of America.

So I have 2 questions. So I appreciate the sharing on the Agentic AI strategy. I'm especially interested in the context that Tencent's AI agents could access the Mini Program ecosystem and use Mini Program code as AI skills. Just wondering on that, is there any time line we should expect for this to materialize? A follow-up would be related to the last question. Given the tight supply of computing resources right now, I was wondering how is management balancing the pace of rolling out additional AI features such as leasing agent against the current pretty tight compute capacity on hand.

Well, on Mini Program, I think this is something that will be coming. I think we need to figure out sort of what's the best way of presenting these and how to allow Mini Program owners to actually sort of actively engage this. So there's -- we have a timeline. We're not going to be able to share with you with a definitive answer because there's a lot of design that needs to come into place, right? But at some point in time, I think it's a concept that our ecosystem can actually help each other out, and this is one unique advantage that we have.

And over time, a lot of potential ecosystem resources can be actually turned into skills for agents. And over time, agents would actually sort of have their own identity and be able to get accounts in some of the services, too, right? So I think that's a unique advantage that we have and we'll be providing that over time.

And on your question about balancing between the various AI products we would like to develop internally. The reality is we've already made the choice and paid the price in that we have prioritized a multiplicity of internal services ahead of Tencent Cloud. And so I think most big tech hyperscale companies with cloud businesses have one flagship internal use case where they're allocating a large number of GPUs. We have multiple flagships. We have the Hunyuan foundation model. We have agentic developments within Weixin. We have Yuanbao support.

We have the AI deployment for advertising for games, now also for the WorkBuddy and CodeBuddy use cases. And the reason why we have been able to support all of these at once is because we have not been active in leasing out GPU capacity in Tencent Cloud. Now looking through the rest of this year, as the supply of China design GPUs progressively ramps up, then we'll be remedying that situation, and we will be making more capacity available in Tencent Cloud and consequently driving up Tencent Cloud's rate of expansion. But that's where the trade-off has been made that we have been consciously late to monetize the AI opportunity through Tencent Cloud because we've been simultaneously supporting a number of AI initiatives internally.

We will take the next question from Charlene Liu from HSBC.

I have 2 questions. First is on monetization. We're seeing Doubao starting to explore subscription models for their 2C users. I would like to understand how big the management thinks that the 2C subscription market looks like in China? And I guess, subscription aside, are -- as and Mini Programs are shop key monetization avenue for 2C AI or there are more? And how much upside do you expect from Ads and Mini Programs? That's the first question.

The second question is on compute power bottleneck. The U.S. players obviously have sort of moved on to working on resolving bottleneck issues or shortages in CPU and networking chips beyond GPU. And has these issues begin to service? Do we anticipate it to? And what are the management's plans to resolve them?

In terms of the 2C monetization, I would say it's actually not easy, right? If you look at global standard in the Western market when the paid service is actually very well penetrated and the living standard is actually very high. So the subscription price in the Western market is multiple times of what the equivalent service in China is like, be it music service or be it video service. The paying penetration is probably in the single digit, right? And when you sort of applied it to China, I think the subscription model is not going to be that big for the China market.

You use that as a standard and then sort of start to read across for China, then it will not be that much. And at the same time, it's necessary, right, for the reason that I talked about, it's not like Internet services in which you can have very low cost of scaling your services, right? Every single user actually sort of cost you something in terms of variable cost. And I think the more important implication is that when you have to have payment to support a service, then most likely the service is not going to be a winner take-all business.

It would basically sort of be supporting multiple players who would have a share of the market and each one of them would sort of have some kind of users and some share of subscriptions. And beyond that, right, when we look at e-commerce or advertising as a way to monetize, I think it's also very early for even the U.S. players where the eCPM is actually much higher, right? The leading player has not been able to roll out very robust advertising model. And so I think it will be for the longer term, and it will be supplement to probably a subscription model.

So I think that's why I said in the world of AI, when you apply the compute and apply the model to different use cases and different applications, you actually need to think about what is actually the high-value use case so that you have the best return on your limited compute in order to achieve the best results.

And in terms of your question about the various bottlenecks between GPU, CPU, networking and so forth. To recap that the reason why there's been a GPU bottleneck that's been much more pronounced in China than elsewhere is a combination of policy restrictions on certain foreign design GPUs being brought into China and then the China design GPUs facing limited fab capacity within China. And as a result, the country has really been short of GPU or ASIC capacity. And that's now being addressed because the China designed ASICs are seeing more supply from fabs within China as well as more supply from fabs in neighboring countries.

But by contrast, we haven't faced those sort of artificial additional constraints, CPU or networking chips. We've been a big buyer of CPU and networking chips for many years before GPUs became such a big presence in data centers. We have very long-term relationships with the companies that supply the CPUs and supply the networking chips.

And on their side, while one might think that these suppliers would be sitting back and just selling at the highest possible price into the spot market, that's not actually the reality. The smart suppliers are taking very conscious 3- to 5-year forward views and negotiating long-term agreements in order to give them certainty of their revenue outlook over the next 3 to 5 years. And when they're deciding with whom to sign those long-term agreements, they're looking to work with a number of partners, not just a single partner, and they're looking to work with partners who have been there for many years already and will be there for many years to come and ideally with partners whose demand they believe will grow substantially over time.

And happily, we fulfill all of those criteria. We've been a big customer for the Intel and AMD and so forth for many years. We've been progressively growing our volume with them for many years, and they believe it will continue to progressively grow our volume for many years to come. So on the procurement side, I'd say that the challenges are more around GPU and those challenges are now being addressed. And then we've been able to secure a good supply of CPU and networking chips.

We will take the next question from Ronald Keung from Goldman Sachs.

So 2 questions. One is on the consumer AI agent side. So compared with a potential kind of Weixin agent that we've been talking about, which is at the app level, knowing that Weixin is a super app, but how does management view long-term potentials or potential disruptions from operating system-level agents, noting agents from iOS or Android or mobile phone by phone makers. So how would we see that potential or disruption or threat?

And then second, on advertising, we've seen a very good reacceleration. Noting that we are very patient on ad load versus peers, but with a slight kind of hedge up of ad load in the first quarter, I'm just thinking, is there any room for any thinking or change to have a potential further revenue acceleration for ads and reason, I would say, thinking bigger advertising profits could drive more reinvestment into AI. So would love to hear your thoughts.

I think from an operating system perspective, right, you mix in a number of different things, right? There is a real operating system, which is iOS and Android, right? And there are -- and then you log in sort of your other applications, which try to pretend to be operating systems. So I think if you are operating system like iOS or Android, then you actually want to make sure that the ecosystem is actually well protected and well curated and given whatever that you actually allow applications to do, right, you actually want to have that balance, right?

You can have an agent which try to provide services to your users, but then you actually need to have the permission, right, of the different applications. Otherwise, as an operating system, you are essentially dropping different apps. And that's not the best way of managing an operating system. So I think operating system has existed for a long time and the principle of an operating system is actually -- it's very neutral, and it actually provides a level playing field for all the apps. And in the future, all the agents to be working with the operating system.

But if you say, there's another app which sort of try to become an operating system like a service and try to sort of invade other apps, I think that's a real competition, and that's not something which any app would actually allow. And I think the operating system itself, which should try to sort of stop that from happening as well. So I think if you're talking about agents, which will sort of be an app trying to compete with other app, I think that's one level of right? And I think operating the system will always try to be quite impartial and try to maintain a healthy ecosystem for everybody to be involved in order for it to be a successful ecosystem or operating system.

And in terms of the advertising revenue, actually, our ad load on video accounts is still the lowest in the industry at 4% to 5%. So there's clearly a substantial headroom for us to increase the ad load. As to whether -- and to what extent we'll sort of feel the need to do so, we are in a position where we have multiple revenue growth drivers beyond advertising. For our game business, the jump in deferred revenue in the quarter provides us with a sort of tailwind to the reported revenue growth over the coming 3 quarters.

For our cloud business, we've talked about how bringing on stream more GPUs in the second half of the year should facilitate revenue growth trends for cloud. For our fintech business, for many quarters, we've been struggling with a situation where volume growth was positive, but pricing was negative. And now volume growth remains positive and pricing move to a more neutral start. So we feel that across our portfolio of businesses, there are certain positive things playing out. And we'll continue to manage it as a broad portfolio, and we'll continue to manage the ad load within video accounts in a way that we think is conducive to both supporting the overall growth of our business metrics, but also to supporting growth of time spent and engagement within the video accounts product itself.

We will take the next question from Ellie Jiang from Macquarie.

I have 2 questions. Number one is, if you look at the WorkBuddy current traction, it does seem like we have been gaining very early leadership, especially in the productivity agent space. So within the 20% growth in business services this quarter, could you shed some light on what percentage of this would be kind of reoccurring Agentic revenue, i.e., be kind of MaaS or SaaS related versus the traditional cloud revenue as well as the others? And specifically, do you have any internal ARR target for these Agentic workflow products by the end of fiscal year '26 and in the next kind of 2, 3 years?

Yes. The upturn in sort of productivity AI is really something that's happened not in the last few quarters or even last few months, but last few weeks. And I think that's true globally actually, that really -- it's since late in or since the end of the first quarter that the Agentic AI has broken through in terms of its ability to create code, in terms of its ability to make people more productive. And so in the first quarter, the business services growth was not a function of that token consumption. The token consumption has been more recent than the end of the first quarter. In terms of ARR targets and so on, by extension, this is all changing so quickly. That we could set a target today, and we'd be out by an order of magnitude 12 months from now in either direction because the usage demand is so dynamic.

So at this point, we're less focused on hitting certain dollar ARR numbers and more focused on having the right products and the right products includes the right product at the model level where Hunyuan 3 is very good in terms of many agentic capabilities. And the next iteration will be substantially better later this year and also at the product level in terms of CodeBuddy and increasingly WorkBuddy being the right interface for users to access and extract the most intelligence from these foundation models. So right now, that's a priority.

We will take the last question from Thomas Chong from Jefferies.

My question is about AI on the content side. Given that we have seen some disruptions coming from AI in the online video space, should we expect Tencent Video? We also have expecting AI drama to be a blockbuster content in the coming years? And how should we think about all the content cost and the business model going forward? And my second question is AI on the fintech segment. Given the risk management is substantially enhanced with AI, how should we think about the online lending and wealth management outlook with AI?

But again, the landscape for AI has been so dynamic. Our own position has changed so much in the last few weeks, in the last few months that it's difficult to speak very definitively. I think when you talk about AI disruption in content creation, you may be alluding to mini videos or mini drama series rather than the long-form drama series that is historically Tencent video strength.

On the long-form side, then what we're seeing is that there is a certain double-digit percentage of the market that likes animated content. And now as a result of the confluence of tools such as Unreal Engine and capabilities such as generative AI for video, it's becoming increasingly feasible to create the same 3D assets for games and for animated content, animated linear video content and both become a very good best-in-class products within that particular categories. And so that's something where Tencent is a natural leader because we have our big content IP operations.

We have our game business. We have our AI technology capabilities. We have particular strength in certain multimodalities within AI. And so as Pony mentioned in the opening remarks, we've actually become a very clear industry leader now in the business of producing animated TV series and AI enables us to do that faster, cheaper, better. It also enables us to bring far more IP into linear video format that was previously sort of stuck in novel format or in game format. And so expand the funnel, expand the audience. So that's on AI for content.

And then on AI for fintech Financial services represents a very big part of global GDP. It represents a very big part of our revenue. It's an industry that is inherently very data heavy. And so it's naturally an industry that should and will lend itself over time to uplift in productivity from AI. And if you think about the industries that are already being uplifted by AI, such as coding, such as advertising, then financial services is actually very logical to be uplifted in the near future, too, because it shares certain characteristics with coding with advertising and so forth.

And so to give one example, on the lending side, then credit scoring has historically been more of an art than a science, and there's been this universe of data available, but only a small subset of that universe is actually fed into the model effectively versus now with transformer-based models, you can sort of take the totality of data available and see what is predictive and improve your loan extension on the basis of that uplift in predictability. So I think it's an area that many companies will be investing a great deal of time and energy and where we'll be participating as well.

Thank you. We are now ending the webinar. Thank you all for joining our results call today. If you wish to check out our press release and other financial information, please visit the IR section of our company website at www.tencent.com. The replay of this webinar will also be available soon. Thank you, and see you next quarter.

Good day, and good evening. Thank you for standing by. Welcome to Tencent Holdings Limited 2025 Fourth Quarter Results Announcement Webinar. I'm Wendy Huang from Tencent IR team. [Operator Instructions] And please be advised that today's webinar is being recorded.

Before we start the presentation, we would like to remind you that it includes forward-looking statements, which are underlined by a number of risks and uncertainties and may not be realized in the future for various reasons. Information about general market conditions is coming from a variety of sources outside of Tencent. This presentation also contains some unaudited non-IFRS financial measures that should be considered in addition to, but not as a substitute for measures of the group's financial performance prepared in accordance with IFRS. For a detailed discussion of risk factors and non-IFRS measures, please refer to our disclosure documents on the IR section of our website.

Now let me introduce the management team on the webinar tonight. Our Chairman and CEO, Pony Ma, will kick off with a short overview; President, Martin Lau, will provide a strategy review; Chief Strategy Officer, James Mitchell, will provide a business review; and Chief Financial Officer, John Lo, will conclude the financial discussion before we open the floor for questions. I will now pass it to Pony.

Thank you, Wendy. Good evening. Thank you, everyone, for joining us. In 2025, we achieved high-quality growth through our evergreen products and services, increasingly supported by applying AI capabilities. We expanded our evergreen game portfolio with the breakout success of Delta Force and reinforces our existing evergreen games such as Honor of Kings and Peacekeeper Elite.

AI contributes meaningfully to game content development, user engagement and marketing efficiency. Video accounts total time spent increased over 20% on upgrade recommendation algorithms and enriched content ecosystem. Our marketing services revenue growth outperformed the industry, benefiting from our upgraded ad tech model and newly introduced automatic campaign solution, AI Marketing Plus.

For FinTech, we sustained healthy revenue growth by deepening cooperation with the licensed financial institutions while maintaining a prudent risk management. In cloud, we achieved profit at scale due to increased enterprise demand for our industry-leading PaaS and SaaS products and supply chain optimization. Internationally, our International Games business surpassed USD 10 billion in annual revenue for the first time, driven by sustained growth of evergreen games and rapid expansion of content-driven games.

Our Cloud revenue accelerated in international markets as we expand partnership with key clients and drove a higher adoption of our flagship cloud products. The robust operating leverage and cash flow generated by our core businesses enable us to step up investment in AI. During the year, we upgraded our team with top-tier AI talent and build processes for improving foundation model intelligence in a systematic way. We began deploying new AI capabilities in services, including Yuanbao and Weixin and cloud-type products.

Looking at our financial numbers for the fourth quarter. Total revenue was CNY 194 billion, up 13% year-on-year. Gross profit was CNY 108 billion, up 19% year-on-year. Non-IFRS operating profit was CNY 70 billion, up 17% year-on-year and non-IFRS net profit attributable to equity holders was CNY 65 billion, up 17% year-on-year. Now I will hand over to Martin.

Thank you, Pony, and good evening and good morning to everybody on the call. I will share with you in this coming section on how we think about AI as a transformational force, starting with how resilient our existing businesses are in the context of AI, moving on to how we are deploying AI in our existing businesses to strengthen them, then discussing brand-new products and opportunities made possible by AI and how we are investing in order to capture them.

So first of all, I would like to talk about our key franchises are very resilient in the age of AI. As we know, AI will affect every part of the technology industry, but some products and services are inherently more resilient than others.

We believe that some of the characteristics of resilience would include network effects arising from consumer-to-consumer, consumer-to-content creator and consumer-to-business interactions in descending order of strength. That's number one; number two, deep supply chain integration linking the words a bit with the world of atoms; number three, stringent regulatory and licensing requirements; number four, scarce or unique resources, including physical and intellectual properties; number five, take rates that are low compared to value provided or cost of switching; and number six, private data that is closed and interactive in nature.

Using these criteria, then we look across our major existing businesses. Our conclusion, which is supported by usage trends is that each one of them has got a high degree of inherent resistance. In particular, for our communication services, including Weixin, QQ and Tencent Meeting, people use them to connect and interact with other people, largely their families, friends and colleagues and business partners. We believe this need for human interaction, together with the network effect and closed nature of the data arising from these interactions have resulted in communication services being extremely sticky in the face of competing non-AI services in the past and will continue to be resilient versus AI-based services in the future.

Then moving on to our games. They are also very resilient as our multiplayer games, especially PvP games also enjoy network effects. And similar to sports, they are team-based in nature and players play with and against other players and just as people prefer to participate themselves or watch the teams they support compete in sports rather than watching AI sports. Game players continue to enjoy the interaction with other humans that our games provide. Our games also cultivate strong IPs. While AI will enable more games to be made faster, the game industry is already in a position of excess supply with 200,000 new games on mobile and 18,000 new games released on steam every year. The limiting factor is that new games need to be high quality and more innovative than the best existing games, which in turn requires human creativity on top of cutting-edge technology. Game is a natural beneficiary of AI proliferation, also when people have more time at hand.

Our FinTech services is also resilient as it depends on difficult to secure and retain licenses, which are limited in nature and also set the boundary on how innovations can be introduced in an industry. We have also invested decades building a payment network of difficult to replicate rails into partner banks, merchants and connecting them with more than 1 billion consumers, which brings its own network effects. And our mobile payment take rates are already among the lowest in the world, which we believe makes competing with us on price highly uneconomical.

Then we want to demonstrate that we are a leader in strengthening our core businesses with AI. When generative AI first emerged, we prioritized leveraging AI to reinforce our core businesses on the view that if we can strengthen them, we will be in a better position to invest in new products made possible by AI. And we believe that in each of our core businesses, we are now at the forefront of their respective industries in China and often globally in utilizing AI with positive initial results demonstrated by user engagement and revenue trends.

In games, we are deploying generative AI to accelerate in-game content production, enabling us to produce more content within our big games. We're using generative AI to facilitate new user acquisition and existing user retention through measures such as targeted ads and personalized daily highlight reels. We're enriching the core gameplay experience with AI features such as virtual teammates in PvP games and realistic nonplayer characters in PvE games. These initiatives are one reason why Tencent's games are more and more evergreen and our revenue growth of 22% in 2025 outperformed the 7% growth of the global games industry.

For marketing services, we scaled up our advertising foundation model to provide more relevant ads to more targeted users, boosting ad conversions for advertisers and providing better user experiences at the same time. We provide generative AI-powered ad creative solutions, enabling advertisers to create more ads, which are more relevant to smaller set of users and more efficiently. We introduced our automated ad campaign solution, AIM+, under which advertisers can automate targeting, bidding and placement, improving their return on marketing investments and increasing their budget allocation to us. These initiatives contributed substantially to Tencent's Marketing Services revenue growth of 19% in 2025, outstripping the overall China ad industry growth of 14%.

For Video Accounts, deploying a longer sequence AI model, which captures more of a user's signals to enhance content recommendation is boosting user growth, engagement and content distribution. Total time spent on video accounts increased more than 20% in 2025, and video Accounts is now the second largest short video service by DAU in China.

For digital content, we utilize AI in content production, improving production workflow efficiency and providing visually compelling special effects. AI also helps in content distribution through more intelligent content recommendations across music videos and literature. We're using AI in enterprise software to provide features such as AI agents that can take notes on and summarize concurrent meetings for users and AI agents that generate intelligent summaries of customer service history for merchants. Our enterprise software products, WeCom and Tencent Meeting are leaders in their categories in China in terms of usage and revenue.

For FinTech, we utilize lightweight AI models to enhance credit scoring processes and facilitate fraud detection, contributing to us sustaining better than industry nonperforming loan rates. Now that our core businesses are benefiting operationally and financially from integrating AI, we believe we are in a position of strength to add development of new AI products to our priorities. At the foundation model layer, we see substantial opportunities from combining a strong foundation model with configuration for core user cases such as chatbot, coding, multimodal and agentic applications. Although we're not the first mover in large language models, having already revamped our team, improved our data quality and rebuilt our AI infrastructure for pretraining and reinforcement learning. We're now iterating more intelligent models at a faster pace. HunYuan 3.0 is in internal testing and currently represents a bigger step-up in capabilities versus HunYuan 2.0 than 2.0 versus 1.0.

For multimodal capabilities, our 3D text-to-image and world models are early category leaders and will increasingly benefit from leveraging our proprietary data and abundant use cases. Some observers in China tech are single-mindedly focused on AI chatbots as the only means for bringing AI to users. We believe this mindset is overly simplistic because AI can help people in a multitude of ways beyond powering an information advice app. We believe that AI chatbot applications are largely competing with search applications rather than with every other application.

For Yuanbao, our own AI chatbot app, we are focused on finding product market fit and use cases which belong in chatbot AI app. We're rapidly iterating Yuanbao to enhance its user experience by providing better search integration, improved speech recognition, easier access to multimodal capabilities and exploration around group chat, which we believe will increase usage and user retention of the app. In the coming months, as we deploy HunYuan 3.0 in Yuanbao, we believe the core user experience will step up further.

In addition, we have also integrated AI to enhance a range of existing user experiences within Weixin, including content consumption, information retrieval and merchandise recommendation and customer service. We're building AI agents, which autonomously interact on behalf of users within Weixin functionalities, especially mini programs. The excitement around clawbots illustrates that people recognize AI can unlock computer use capabilities to improve their daily lives, but also illustrate the risks around unleashing unsupervised AI. We want AI agents in Weixin to deliver AI productivity that's beneficial to the general public as well as early adopters and which will boost ecosystem activity and naturally generate revenue.

AI agents are currently powered by a multiplicity of foundation models, and we expect that users at the application level will continue to have access to a range of models. However, improving the performance of HunYuan will enable us to offer new unique to Weixin agentic capabilities. So the Weixin and HunYuan teams will work increasingly closely together going forward.

Speaking of clawbots, we have introduced a number of AI tools for enhancing productivity, including WorkBuddy, Qclaw and Tencent Cloud Lighthouse, and we provide downloadable skills to easily put these tools to use from our SkillHub. Clawbots are upgrading AI from thinking to doing via autonomous workflows and continuous task execution. Users control this new generation AI tools through command line interfaces in their existing communication apps, which generally means Weixin and QQ in China as it is efficient for users to interact with digital agents in a place and format where they are already interacting with human context.

The new AI products that I described above require substantial and increasing investment, which we believe will generate significant return for us over the long run. Our spending on our 2 biggest new AI products, HunYuan and Yuanbao, was CNY 7 billion in the fourth quarter of 2025 and CNY 18 billion for the full year. These figures are only for HunYuan and Yuanbao and exclude AI initiatives supporting our existing products and services as well as exclude costs arising from providing GPUs to external customers via Tencent Cloud.

We expect to more than double these investments in HunYuan, Yuanbao and other new AI products in 2026, which we intend to fund from increasing earnings from our core businesses. In this transformational period, we are breaking out our investment in new AI products because we view these strategic investment conceptually similar to investment in affiliates or to CapEx. These are upfront investments required to build the necessary foundation to unlock new value as opposed to ongoing operating expenses. As such, we believe the impact of these investments should be viewed separately for the profits generated by our existing businesses. Over time, we're confident that monetization will follow usage for these new AI products.

Lastly, I would like to present a case study on Tencent Cloud as the latest example on how we develop our services into market leaders with economic returns over time, and that would follow games, payments and long-form video. And we expect it will be the same for our new AI products.

Tencent Cloud was a relative late entrant in cloud services. However, we committed to a patient and long-term investment strategy, believing that it had scale from the start due to Tencent itself being the biggest single end user for a range of technology infrastructure in China and that it could provide differentiated services arising from Tencent's unique insights, ecosystem and capabilities. For example, we believe that we were the first cloud service provider in China to fully recognize the stepped-up capability of AMD's recent generations of CPUs, becoming AMD's largest partner in the country and that our cloud video streaming service is the industry leader in terms of streaming quality.

After a period where Tencent Cloud prioritized the revenue growth somewhat misguided by other industry participants, in 2022, we aggressively restructured Tencent Cloud to focus on high-quality services rather than chasing high revenue but low value-added activities such as reselling and customizing projects. This pivot cost us several quarters of revenue growth, but it enabled Tencent Cloud to achieve operating profit breakeven in 2024, up from significant losses in prior years. During 2025, although Tencent Cloud continued to face revenue headwinds due to limited availability of GPU for external customers as we prioritize our internal needs, it grew revenue and sharply improved earnings, achieving CNY 5 billion adjusted operating profit.

In recent months, we're seeing a better pricing environment, especially for memory and CPU, which along with robust AI demand and overseas expansion are allowing Tencent Cloud to grow revenue at a faster rate. Moving through the year, we have ordered a substantially higher volume of compute, which should also facilitate revenue growth. Overall, we think Tencent Cloud is becoming another example of how Tencent competes on our own terms and pace and how our incubation investment cycle works. We view the initial losses in Tencent Cloud as a fixed sum of cash investment necessary to incubate a successful new business, but ultimately generating good economic returns. And we view the initial investment in new AI products, code-named MAP in the same way. With that, let me pass to James.

Thank you, Martin. For the fourth quarter of 2025, our total revenue was up 13% year-on-year. VAS represented 47% of our revenue within which the social network subsegment was 16%, domestic games 20% and international games 11%. Marketing Services was 21% and FinTech and Business Services 31%. Our gross profit was up 19% year-on-year to CNY 108 billion. VAS gross profit increased 21%, Marketing Services increased 22% and FinTech and Business Services increased 17%.

Turning to business segments. Value-added service revenue was CNY 90 billion, up 14% year-on-year. Our social network revenue grew 3% year-on-year to CNY 31 billion, driven by increased revenue from video accounts live streaming and from music subscriptions. Music subscription revenue increased 13% year-on-year on ARPU and subscriber growth. Long-form video subscription revenue increased 1% year-on-year as video subscribers grew slightly year-on-year, benefiting from the drama series Love's Ambition, the variety show Natural High: Season 3 and the animated series Renegade Immortal. Each of these ranked first by video views in their respective genres across all video platforms in China for the quarter.

Domestic games revenue grew 15% year-on-year, primarily driven by Delta Force, the Valorant franchise and Wuthering Waves. International games revenue increased 32% year-on-year, primarily driven by Supercell's titles, PUBG Mobile, and Wuthering Waves.

Moving to communications and social networks. We strengthened Weixin's commerce experience by upgrading features for users and tools for merchants in the mini shops. The upgraded e-commerce gateway page allows users to check their shopping carts, see what friends are recommending and receive notifications from their favorite shops and generated substantial GMV during the quarter. Through the new likes for Discounts feature, users can discover products liked by friends and receive and share discounts via the e-commerce gateway page, chats and moments.

For Mini Programs, total user time spent increased over 20% year-on-year, driven by workplace productivity tools, mini games and novels. We added Tencent CodeBuddy to our developer toolkit, enabling developers to create mini programs using natural language input, and we provided developers of AI native mini programs with free compute resources.

For domestic games, Delta Force sustained among the top 3 games in the industry in the quarter. In February 2026, the game surpassed 50 million peak daily active users and achieved lifetime high monthly gross receipts. Delta Force leverages AI coding for development efficiency and deploys AI-powered companions to enhance user engagement. Valorant PC increased its gross receipts more than 30% year-on-year and achieved record high average DAU in the quarter, benefiting from the Flowers Meets Magic Mystbloom skins, limited time roads and eSports events.

Valorant Mobile was the most successful new mobile game industry-wide by gross receipts in 2025, bringing a PC quality shooting experience and a distinctive art style that appeals to younger players. The game achieved lifetime high gross receipts in February as we released outfits to integrate traditional Chinese aesthetics with contemporary design. In January, we launched Assault Fire: Future, a multi-platform FPS game built on Unreal Engine, which has attracted several million DAUs.

Among our international games, Clash Royale ranked the third largest mobile game industry-wide by DAU in the fourth quarter. Its average DAU and gross receipts more than tripled year-on-year, reaching lifetime highs. The game launched 10th anniversary events in March, including a limited time PvP mode with random modifiers powering our players' cards, providing a more dynamic competitive experience. Wuthering Waves won the Players' Voice Award at the Game Awards ceremony in 2025. In the fourth quarter, the game posted rapid year-on-year growth in gross receipts and DAU, driven by a new storyline, urban ruin maps and new characters.

Warframe launched a major update, the Old Peace featuring a new storyline, 2 new game modes and new Warframe Uriel, and its average DAU and gross receipts reached lifetime highs in December 2025. For Marketing Services, revenue increased 17% year-on-year to CNY 41 billion. We experienced rapid growth from the Internet services and local services categories, partially offset by slower growth from the e-commerce category due to platforms temporarily shifting budget from marketing to subsidies and also from the financial services category due to the impact of policy changes affecting online lending during the quarter. Growth drivers included improved ad targeting, expanding our closed-loop marketing services and tailoring ad formats for specific advertiser use cases such as ads that are playable previews of the mini games being advertised.

Entering 2026, we have deepened collaboration with e-commerce platforms, facilitating their merchants advertising within Tencent, and we've increased the inventory for rewarded video ads and video accounts, which have contributed to faster year-on-year marketing services revenue growth in the first quarter-to-date versus in the fourth quarter of last year.

At a product level, Video Accounts total time spend increased due to upgrades to the content recommendation algorithm, enabling faster growth in ad impressions, while our ad load remained lower than peers. Better conversion rates contributed to more marketing spending for Mini Shops merchants. For Mini Programs, consumers engaging more with Mini Games and Mini Dramas attracted more marketing spend from the Mini Game and Mini Drama Studios. And Weixin search overall query volume grew at a rapid rate due to AI enhancements to search results, driving growth in commercial query volume, while search pricing also increased.

On FinTech and Business Services, segment revenue was CNY 61 billion, up 8%. We grew FinTech services revenue by a single-digit percentage year-on-year and FinTech gross profit at a higher rate, driven by Wealth Management and Commercial payment services. Commercial payment volumes sustained positive year-on-year growth, supported by a higher number of transactions and a narrowed decline in value per transaction. For Wealth Management, which is the second biggest contributor to FinTech revenue, average assets per user and number of users each increased year-on-year.

Turning to Business Services. Revenue in the fourth quarter grew 22% year-on-year, driven by higher cloud services revenue and increased technology service fees generated from higher Mini Shops e-commerce transaction volumes. Our cloud services revenue accelerated its year-on-year growth rate due to increased demand and a better pricing environment amid tight supply of memory and CPU industry-wide. Revenue from our cloud media services grew notably as short video platforms and AI video generation services are increasingly using our media processing solutions for streaming video and audio from processing in the cloud to play back on device, reflecting our industry-leading streaming quality and our competitive pricing. And now I'll pass to John.

Thank you, James. Hello, everyone. For quarter 4 2025, total revenue was CNY 194.4 billion, up 13% year-on-year. Gross profit was CNY 108.3 billion, up 19% year-on-year. Other gains were CNY 1.3 billion compared with other gains of CNY 2.5 billion in the same period last year due to lower subsidies and tax rebates.

Operating profit was CNY 60.3 billion, up 17% year-on-year. Interest income was CNY 4.8 billion, up 22% year-on-year, driven in part by growth in cash reserves. Finance costs were CNY 3.6 billion compared with CNY 2.5 billion in the same quarter last year, primarily due to ForEx loss this quarter versus ForEx gains in the same quarter last year. Share of profit of associates and joint venture was CNY 6.8 billion compared with CNY 9.3 billion in the same quarter last year. On a non-IFRS basis, share of profit was CNY 9.1 billion, up from CNY 7.7 billion in the same quarter last year, with the increase from improved performance of certain domestic associates due to operational efficiencies and business growth.

Income tax expense increased by 7% year-on-year to CNY 12.5 billion. On a non-IFRS basis, diluted EPS was CNY 6.96, up 18% year-on-year, outpacing non-IFRS net profit growth due to reduced share count after our share buybacks. On Q4 non-IFRS financial figures, operating profit was CNY 69.5 billion, up 17% year-on-year. Net profit attributable to equity holders was CNY 64.7 billion, up 17% year-on-year.

Moving on to gross margin for the fourth quarter. Overall gross margin was 56%, up 3 percentage points year-on-year. VAS gross margin was 60%, up 4 percentage points year-on-year, primarily driven by greater contribution of internally developed high-margin games. Marketing Services gross margin was 60%, up 2 percentage points year-on-year as AI-powered marketing services drove strong growth in high-margin revenue streams, particularly Video Accounts and Weixin Search. FinTech and Business Services gross margin was 51%, up 4 percentage points year-on-year, benefiting from growing scale of cloud services and improved revenue mix in FinTech services alongside enhanced cost efficiency.

On quarter 4 operating expenses, selling and marketing expenses were CNY 13 billion, up 26% year-on-year, reflecting increased promotional efforts to support the growth of our AI native application and games. R&D expenses rose by 20% year-on-year to CNY 23.8 billion, primarily due to higher staff costs and increased depreciation expenses driven by our AI investments. G&A, excluding R&D expenses, increased by 8% year-on-year to CNY 12.5 billion due to higher staff costs. At quarter end, we had approximately 116,000 employees, up 5% year-on-year or 1% Q-on-Q, primarily reflected headcount additions to gains in our technology platform, including AI-related headcount.

Our fourth quarter non-IFRS operating margin was 36%, up 1 percentage point year-on-year. For fourth quarter, operating CapEx was CNY 16.9 billion, increasing 41% quarter-on-quarter as we accelerated investment in server infrastructure. Year-on-year, operating CapEx decreased by 51%, reflecting concentrated CapEx spending in the fourth quarter 2024, leading to a high base effect. Nonoperating CapEx was CNY 2.7 billion, up 60% year-on-year due to higher facility-related investments. Free cash flow was CNY 34 billion, increasing over 6x year-on-year, reflecting stronger operating cash flow generation this quarter as well as lower CapEx spending versus Q4 '24, as I mentioned earlier.

On a Q-on-Q basis, free cash flow decreased by 42% due to seasonally lower game gross receipt and seasonal settlement of certain accounts payable. Net cash position was CNY 107.1 billion, up 5% quarter-on-quarter or CNY 4.7 billion, mainly driven by free cash flow generation, partially offset by share repurchase of CNY 19.6 billion and net cash flows of CNY 6.9 billion, primarily relating to investment in other corporations.

For the full year of 2025, we repurchased 153 million shares with a total consideration of HKD 80 billion. Our weighted average number of shares for calculating 2025 diluted EPS decreased by 2% year-on-year. Given we see high return opportunities from investing in AI, we will likely buy back lower value of our shares versus 2025 to fund investment in AI while increasing our dividends. Subject to the shareholders' approval at the upcoming AGM, we are proposing an annual dividend of HKD 5.3 per share, reflecting an 18% year-on-year increase. This dividend will be payable to shareholders on the 1st of June 2026. Thank you.

[Operator Instructions]

So the first question comes from Kenneth Fong from UBS.

I have a question on the AI front versus the margin. In our prepared remarks, we expect the increased profit from our existing business to more than cover incremental AI investment. I understand we need to look at this AI long-term investment separately. But as OpEx continue to increase into this year, how should we think about the profit margin or the gap between revenue and profit growth into 2026? And my second question is also on AI, how we strategically prioritize given the ongoing constraint in GPU and AI talent? As we previously emphasized, prioritizing internal AI deployment given the recent market development, as management views shift, how we prioritize allocating resources or KPI that we monitor? Is that the development of a SOTA large language model or user engagement or token growth i.e., B2B solutions?

Kenneth, why don't I start and then Martin may complement. So I think it's implicit in our opening remarks that it is possible that our revenue would grow faster than our profit in 2026 due to the step-up investment in new AI products. And if that's what eventuates, we're very comfortable with that outcome because we can see that these new AI products represents an opportunity for us to expand our footprint and deliver new value to users. And we can also see from the user enthusiasm around some of these products that there's a very good opportunity for product market fit.

In terms of your second question around resource constraints on talent and GPUs, then as far as talent is concerned, we've already been staffing up quite aggressively some very excellent quality talent from the world and from China for the HunYuan team, and we'll continue to make selective hires, but we actually feel we have really a state-of-the-art team, AI talent team already in place.

And we've been able to put it in place not only through compensation as an incentive, but also through creating the right culture for the team through allocating the roles of the team versus each other and the role of the team within the rest of Tencent appropriately through the best leaders of the team in turn attracting the best joiners to the team in terms of provisioning the team with ample compute and in terms of being able to offer the team use cases for the AI products they create that are somewhat differentiated and unique to Tencent. So that's on talent where I think that we were facing a situation of scarcity and we're now much more comfortable with the setup, although we'll continue to recruit selectively.

In terms of GPU constraints, then we've been quite actively provisioning more compute, and that will be coming on stream progressively and increasingly quickly through this year, especially the second half of the year. And that additional compute comes from leasing capacity. It comes from us purchasing higher-end imported GPUs, which are now becoming available again, and it comes from us purchasing the increasing quantity of domestically China designed GPUs. And then in terms of utilizing the compute for different use cases, the priority right now is HunYuan and our new AI products more generally, the core products are inherently distributed in nature, and they can themselves source compute from local devices, from multiple clouds, from Tencent Cloud, but they're sort of somewhat agnostic in terms of the sourcing of compute. So we are focusing our compute on HunYuan as the core foundation model and then on the new AI products.

[Operator Instructions]

Next question comes from Robin Zhu from Bernstein.

I guess if I could get your thoughts on -- clearly, we're heading into this AI cycle of investment. How should we think about your assessment of ROI and the timing of returns and how you prioritize building versus renting and which parts of the AI stack you think are most critical to be best-in-breed versus areas where you think eventually these things will be commoditized as AI continues to move forward?

Okay. Well, I think from an ROI perspective, we have already seen very good ROIs when we apply AI into our existing businesses, right? So if you look at the breakdown of our financials, if you look at the financials on a combined basis and then sort of we break it out and saying, these are the financials with existing businesses plus the investment into AI for supporting these businesses, right, the growth is actually quite strong. And if you exclude the investment in new AI products, then the operating leverage is clearly there. So I think that's sort of level #1, right.

And then level #2 is an investment into new AI products. On that front, I think we would be seeing new investments first, right? There's not that much of a revenue, especially in the context of China, unlike in the U.S. where you can actually get consumers to pay subscriptions and you can get companies to pay for coding agents at a very high cost. In China, those are not sort of that available. So I think these will present themselves as investments upfront. But then over time, we believe we'll be able to generate revenue from these new AI products, and they would generate very attractive return for us over time.

We quote Tencent Cloud as an example in which we initially actually have to invest in the business in terms of incurring losses. But over time, right, it actually turns into a profitable business, and we believe AI will be like that. There will be a timing difference in terms of the investment and then the return for these new AI products. In terms of building versus renting, I think if we can buy, right, I think given how strong our balance sheet is, we would actually prefer to buy because then we don't necessarily need to pay the additional margin for leasing. But I think given the constraints in the supply chain and all the different regulations, sometimes we just have to rent. And I think we would do that if we need to secure compute.

What was the last question? Last bit of the question? Did I answer all your questions?

The last question was, if we think about the AI stack between kind of the models, the orchestration layer, the application layer and so on, which parts would you say are most critical for Tencent to be best-in-breed versus areas where we think these will be commoditized and it's okay just to have something?

I think at this point in time, it's actually very dynamic, right? In a fast-moving market, I think it's very difficult for someone to say that there will be one layer more important than the others. So I think we have the resources, we have the people, we have the team to actually invest in all these layers. And especially the teams are actually very different. And for HunYuan, actually, we have to build the team from scratch once again. And now it's actually sort of as James said, we have a very strong core team, and we have a very strong capability to keep attracting top talent.

But then if you start getting into the application layer, right, it's actually playing into our strength, right? Because then suddenly, you don't even need to have that model capability, but it actually plays to our strength in terms of product capability and orchestration capability connection, which is our strength, ecosystem is actually our strength and all the infrastructure services like security is also something that we have invested for a very long time. And the ability to go across devices such as mobile and PC, right, it's actually our core strength, too, right? So I think that actually is really moving into our territory of strength. So we will actually have to and also invest in all these capabilities and the dynamics of the market will play out itself. And hopefully, we will become best of breed in all layers.

We will take the next one question from Ronald Keung from Goldman Sachs.

I want to ask about the AI agent agent potential. With the recent launch of Qclaw, WorkBuddy, and we saw the SkillHub as well, how should we view parallels of, let's say, Android versus what we are seeing now for [ OpenClaw ] in this agentic opportunity and our positioning within? So you mentioned about Tencent Cloud in that opportunity. And how do you plan to differentiate other parts of the stack, for example, models?

I think claw is actually a very exciting concept right now. And it actually sort of presents a decentralized model or decentralized regime for how AI works in this world, right? So there's some parallel to sort of how the Internet evolves, right? In the very beginning, when Internet first appears, right, there seems to be sort of there is one entry point, which is the browser and then there's sort of one distribution point, which is the search engine.

But over time, there are different services which evolve, right? And then when mobile Internet comes, suddenly you see sort of a multitude of applications coming up, right? And within the applications, there are applications which are completely mobile native, mobile-centric, mobile first. And then there are also mobile applications that were the PC Internet champions who actually migrate onto the mobile Internet world, right? And I think this is how we felt the claw is, right?

For some time, right, the AI seems to be sort of -- everybody is trying to fight to become the AI AGI hegemon or monopoly, right? There seems to be a point in which like people said, if there's one model, which is AGI, then it would rule over everybody, right? But the reality is not, right? You have multiple models becoming very strong, and they specialize in different kinds of activities, right, one in chatbot, the other one in coding and the other one in multimodal and you also have open source, which are pretty good. And you have a lot of other models, which is sort of fast followers, too.

And then there was a time in which in the 2C world, there seems to be the chatbot being sort of the single entry point. But now with claw, you can see it opens up a completely decentralized regime where many companies can have their own claw and the claw can be using all kinds of different models, right? And it's supported by the infrastructure of cloud. And each one of the claw has to figure out its unique value proposition, right, to win the heart of the users. And the claws also make use of not just the cloud, not just a unique model, it also sort of also make use of the tools available to them on the devices and utilize the file system, right?

So it becomes a much more exciting decentralized world. And we felt we -- there's a lot of opportunities for us in terms of building products to cater to people's needs. So that's why there's Qclaw, there's also WorkBuddy. And in the future, I think a lot of existing apps will try to come up with their own claws, right, and their own AGM capabilities and different models will also sort of try to compete to win the hearts of these claws. So it becomes a much more exciting world and decentralized world for everybody to have some participation. And we just need to, as I said, right, build expertise in the different layers in the model layer, in the product layer, in the infrastructure layer and each layer would have to sort of have their own specific value proposition to win its own usage.

We will take the next question from Ellie Jiang from Macquarie.

I actually have a follow-up just on [ just now's ] question towards the agentic era. How would management evaluate Tencent's value propositioning in this new agentic era? And since we are putting HunYuan alongside with the other LLMs kind of towards the consumers and consumers, how do we potentially prevent from the other LLMs diluting our own foundation models value in the longer term?

I think that in terms of Tencent's unique value proposition or what we can bring to users in the claude era, there's a few sort of inherent attributes that we possess, which we think are very suitable for the agents, the deployment of claws. And Martin has touched on them, but one of those attributes is that we're a company whose capabilities span across PC, mobile, cloud. We're a company whose capabilities span across applications and the worldwide web, just as the agentic claws span the devices and span the sort of domains.

We're a company that operates a number of centralized apps, but also hosts some extremely decentralized yet vibrant ecosystems, most notably the mini program ecosystem. And so one framework you could think about is that in prior years, the arrival of the mobile Internet really sort of turbocharged the application experience vis-a-vis the more centralized app experience vis-a-vis the more decentralized worldwide web experience. And now with these agentic capabilities and claws, then there's an opportunity for decentralized experiences such as mini programs to be turbocharged and themselves develop far more powerful capabilities than they enjoyed in the past.

So that's why we think there's inherently a natural fit between our capabilities and our interest and the deployment of these agents or claws. And that's why we're seeing -- one reason why we're seeing consumers and prosumers enthusiastically adopting our own agent and claw services.

In terms of the part of your question about preventing other large language models diluting our models' value, I may not sort of understand the premise correctly, but I don't see that happening. If you use these claws, then you go into them and you have a choice, do you want to use model A, which is very high performance and high price per token or model Z that's medium performance and very low price per token or models B through Y in the middle, and that's part of the appeal of the claws and HunYuan is one of those models that is available. And we believe with the capabilities of the HunYuan team now in place that going forward, HunYuan will get better faster, and therefore, consumers will naturally increasingly opt to use HunYuan.

But I don't think it will be a monopoly situation that the claws that are successful will be claws that continue to allow consumers and prosumers to make their own choice along the price performance curve and different models will sit at different places on the price performance curve. And we want to be one of those, but we don't intend to be the only one of those.

We will take the next question from Alicia Yap from Citi.

I have a question related to the physical AI. So considering the proliferations of the productivity-focused AI agent across enterprises, especially the traditional industry, do you believe this will accelerate the demand for the usage of the world models like the 3D models that you have? And also what is management's assessment of Tencent's capability and also the competitive strength in the future physical AI era?

Alicia, I think your point is a reasonable one that there is already computer-aided design capabilities and one would naturally expect AI to supplement and eventually supercharge those abilities. And that's important in industrial design. It's important in architecture. It's actually very important and increasingly important in video games. And we believe we can see that we're in a somewhat uniquely good position to provide the data to train the models to in turn supply those 3D tools because of the breadth and depth of 3D graphical assets within our video games. But it's ultimately a sort of a big niche, and it's one that we are well positioned to address, but I wouldn't say it's the biggest opportunity ahead of us. There's many larger, more immediate opportunities.

We will take the next question from John Choi from Daiwa.

I have a question related to games and AI disruption. Have you seen -- already starting to see some headcount and game development costs being impacted? And how do you think AI will impact the quality and also the overall cost side? And how should we expect Tencent to prepare this? Would also distribution and publishing be more important going down the road as we see more increased number of games? And also, if you look -- AI lowers the development entry barriers, are we going to see a meaningful increase in the supply of the game studios in terms of the overall quantity of the games going down the road?

Yes. Thank you for the question, John. So I don't know if any of you attended the Game Developers Conference last week, but it is the sort of premier event each year for game developers. And as you would expect, there was a number of well-attended presentations about the use of AI within creating games.

And I think a couple of broad observations. One is that those presentations were pretty exclusively focused on how to use AI to upgrade content within existing games to accelerate the content creation, improve the content creation within games, but that there is not yet the capability to create games completely from scratch using AI for a number of reasons that we can get into.

And then the second observation is that many of the best attended presentations were by our colleagues within Tencent's Interactive Entertainment Group. And they talked about how AI can be deployed in games for graphics, AI can be deployed in games for gameplay, AI can be deployed in games for user companionship and so forth. And we believe that we're at the forefront of the industry in this regard and the feedback from many of the people, the developers who attended the game developers conference was consistent with that belief.

In terms of the second half of your question about whether AI will result in a flood of new games and therefore, elevate the importance of publishing versus development, then the sad reality of the game industry is that it's perpetually in an oversupply situation. Every year, as Martin mentioned, there's 200,000 new games on mobile. There's 18,000 new games on Steam. So whether that number goes from 200,000 to 2 million to 2 billion to 2 trillion has sort of diminishing incremental impact.

The key is really making and then extending and rendering evergreen the best games. And in order to do that, you need the best human beings supplemented by the best technology. And we think that, therefore, the value balance between development and publishing will remain where it is today and the critical success factors will continue to favor the best developers in the industry.

Just to add a couple more points, right? Number one, when you talk about sort of AI disruption for games, right, that basically sort of imply it's actually best for the gaming industry. But I think sort of gaming is actually one of the industries that will benefit from AI, right? Because when AI proliferates, I think people would have more free time at their hands and the demand side would actually increase significantly for the gaming industry, which I think is a rare certainty in the sort of phase of AI proliferation.

And number two is the availability of great tools will be available to new developers, but it also sort of will be available to very organized teams and highly talented developers that are already running big evergreen games, right? And I would say sort of when a tool is actually available, it's going to overly benefit the people who have the resources and who have already got all the gamers around the platform and they can actually better use these tools to increase the amount of production and make games even more evergreen, right? So I think that's an advantage for players who have evergreen games and are also extremely fast and agile in embracing technology.

And finally, right, when there's a multitude of innovations, a lot of times, I think what we saw in the gaming industry is like an idea comes around and then it's not perfect and it gets sort of iterated and polished over time. And I think the process would actually, again, be speeding up if a lot of these games who have a lot of users look at these innovations and can iterate faster and incorporate these new experiences into their existing games and make games essentially into platforms. And I think that's a unique opportunity that we would see over time as well.

We will take the next question from Alex Yao from JPMorgan.

I want to follow up on the AI cloud side of the business, given very strong demand for AI compute, but on the other hand, also price inflation for the server -- AI servers due to the rising cost of DRAM and HBM. Can you guys help us understand Tencent Cloud's pricing power and also philosophy to value capture in such a very dynamic environment? Or put it another way, do you want to fully pass through the cost inflation to your customers or partially subsidize the cost inflation and then gain more market share or even potentially more than fully pass through the cost inflation to capture more profit?

Thank you for the question, Alex. So first of all, I'd start by saying that clearly, there is a surge in demand for sort of AI compute, but it's not only for AI compute. When people utilize the agentic tools that we have been discussing, they're using them and they create software. And that software then primarily needs to be executed. And when it executes, most of it is not executing on GPU, it's executing on CPU. And then it creates -- as it executes, it creates memory demand.

So it's not just GPU, DRAM, HBM where we're seeing demand picking up. It's also CPU, it's regular RAM, it's SSD, it's hard disk drive. It's across the board, there's a pickup in demand. And in terms of how the industry and our addresses at an industry level responds with pricing, then for years, the industry has suffered because the cloud services providers in China were operating at very low margins. And one of the reasons they operated at very low margins was because if there was a new entrant or if the customers wanted to source infrastructure directly, they were able to telephone the supplier and order the infrastructure that they wanted from the supplier of CPU or GPU or DRAM.

That's no longer the case. Now the supply is booked out months, quarters, in some cases, years in advance. The supply is prioritizing the biggest, most regular customers, which are the hyperscalers such as ourselves. And therefore, the customers, the smaller cloud providers no longer have certainty that they can source supply, and they need to come to the hyperscalers. And the hyperscalers have been operating at low margins. And so when the demand picks up, then we almost sort of as an industry, have no choice but to pass through higher prices. And you have seen a number of price increases in China Cloud in the last 24 hours as a result.

In terms of how we sort of value capture in this dynamic environment, then one broad principle is we seek to deliver more value through enrichment. And so enrichment means that at a minimum, if you have compute, you can rent it out bare metal and you get a certain low price and low margin. Preferably, you rent it out -- you subdivide it and virtualize it into tokens and then you get a higher price and higher margin per unit of compute. And ideally, you bundle it into Platform as a Service or Software as a Service, and then you can get the best pricing and the best margins.

And so that's part of the journey that we have been on, and that's part of how Tencent Cloud has moved from very substantial losses 4 years ago to pretty substantial profits last year, and we'll continue on that journey of moving from bare metal to token to platformization and to software.

We will take the next question from Gary Yu from Morgan Stanley.

I have one question regarding the comment quite a few times that we mentioned that we are not a first mover or we are even a latecomer in AI. In the U.S., we have also observed that it's becoming very difficult for some of the latecomers to catch up, even for those that have very high resources in terms of compute, talents and data. So how does management get comfortable and confident that we won't be following the same path in terms of lagging behind, not able to catch up and around areas on compute modeled applications?

Yes. I think that's a very good question. And I think if you are playing just one game, then basically, it's hard to sort of catch up on one game, right? But then if you view AI as sort of a multiple of different games, then there are new opportunities, new frontier that's opened all the time, right?

So I think when -- it's already happening, right? If you look at the model, right, in the very beginning, everybody felt it's the chatbot and then coding comes around and then multimodal come around. And then sort of when everybody felt, oh, that's pretty much and sudden sort of claw came around, which basically further decentralized the whole AI landscape. So in the future, we actually felt there will be just like apps, right, there will be a lot of different permutations of how AI will be packaged from model to the product to agent and existing services will be having sort of different agent capabilities. There will be new agent capability coming around on mobile, on PC.

So it's very early days in the whole AI development world. So that's why just within a short period of time, you can see there are already a lot of proliferations and there will be more and more coming. So that's why it's actually important to have some fundamental capability, right? And we do have a lot of them in terms at the application layer, be it Weixin and be it our ecosystem of having communication and presence on PC and mobile and a lot of infrastructure capability, including security and cloud and payment. And all these elements can be packaged together in the new race of AI.

So it's not sort of one race. It's actually sort of a world of many, many races. And I think that will increasingly manifest itself. And as a result, there will be a lot of opportunities for different players to come up and innovate from behind. So I'm not sort of very worried about being late, but I'd be worried about if we're not innovating fast enough, which I think we -- as we restructure our HunYuan team and as we started to invigorate all our product teams to start innovating with products. And I think that's actually happening in a very exciting way for us.

We will take the next question from William Packer from BNP.

Press reports suggest Apple is planning to cut App Store commission rates by 5% for apps and 2% to 3% for mini games in March in China. Tencent is a potential major beneficiary. To what extent should we expect these cuts to flow through to Tencent's gross margin? Or would they be shared with other stakeholders such as consumers, gaming partners or perhaps tax revenue?

Will, so happily, in this case, the press reports were based on the sort of objective reality of an Apple formal announcement. And so this is not a speculative hypothetical. It's an actual development that takes effect in the last few days.

And in terms of the flow-through, then there should be a good flow-through. When we have game development partners and we're the publisher of those games, which is now quite a small minority of our game revenue, then in the overwhelming majority of cases, the revenue share is calculated based on the gross revenue, not on the revenue net of the app will take. And so that flows through to us.

If by taxes, you're referring to us paying a teens percentage corporate income tax on this incremental profit stream, then I suppose that's correct, dependent on the extent to which we reinvest this incremental profit stream into new AI products. I think that -- you talked about one part of the Apple announcement, which is the sort of quantitative part that moves from 30% to 25% and 15% to 12%. But for us, actually, the more important aspect of the Apple announcement looking forward was that Apple stated that it would effectively offer developers in China equivalents with whatever the lower rate is that developers elsewhere in the world are paying to App Store.

And so our view is that with the evolving industry trends, it's a sort of matter of time for the tolls that App Store collects to normalize downward in different parts of the world. And with this declaration, Apple has stated that as the take rates move down in different parts of the world, so the take rates will move down in China in synchronicity. So we believe that this is a very positive first step, but it is a first step on a multistep positive journey.

Thank you. We will take the last question from Alex Liu from Bank of America.

My question is really just on AI chips. So we're seeing a growing number of your tech peers are prioritizing the development of in-house chip design capabilities. So I'm just curious where in-house chip development fits into Tencent's own AI priorities?

Thanks for your question. I think at this point of time, it's not the most critical thing that we'll be focused on. So if you look at the chip, there's a difference between training chip and inference chip, right? And for training chip, it's actually very, very difficult to design and manufacture and you actually want to have access to the most state-of-the-art training chips to the extent possible and in the most flexible way so that you can actually sort of keep training for the best model.

And then if you're talking about inference, right, I think inference, it's mostly for cost. And I think for cost at this point in time, there's actually a lot of different supplies in China, which is actually very different from, let's say, in the training space, right, where there's essentially 1 or 2 players who can actually command a very, very high margin, right? In the inference world, people basically are earning much lower margin, and there are many more solutions and options.

So I think the key for us is actually sort of leverage the best training chips to train the best model at this point in time, and there's a lot of value in being focused. And when it comes to the inference part, right, over time, I think the market would actually sort of play out in such a way that I think the margin in the inference chips will be actually quite manageable. At this point in time, we are very focused on leveraging the best chip to train our model. Our HunYuan 3.0 is going to be much better than HunYuan 2.0, and that's actually just the starting point.

I think over time, we'll be able to iterate the training of our model faster, and I'm very confident that if we focus on that, we'll reach SOTA at some point in time. And I think that's actually the most important thing for us. And the next important for us is actually really unleashing the power of our product development capability and integration and connection capability in order to design the most exciting AI products for users. I think when those are done, right, then we think about how do we try to reduce the cost of inference.

Thank you, Martin. We are now ending the webinar. Thank you all for joining our results today. If you wish to check out our press release and other financial information, please visit the IR section of our company website at www.tencent.com. The replay of this webinar will also be available soon. Thank you, and see you next quarter.

Good day and a good evening. Thank you for standing by. Welcome to Tencent Holdings Limited 2025 Third Quarter Results Announcement webinar. I'm Wendy Huang from Tencent IR team. [Operator Instructions]. And please be advised that today's revenue is being recorded.

Before we start the presentation, we would like to remind you that it includes forward-looking statements, which are underlined by a number of risks and uncertainties and may not be realized in the future for various reasons. Information about general market conditions is coming from a variety of sources outside of Tencent. This presentation also contains some unaudited non-IFRS financial measures that should be considered in addition to, but not as a substitute for measures of the group's financial performance reported in accordance with IFRS. For a detailed discussion of risk factors and non-IFRS measures, please refer to our disclosure documents on the IR section of our website.

Let me now introduce the management team on the webinar tonight. Our Chairman and CEO, Pony Ma, will kick off with a short overview. President, Martin Lau and Chief Strategy Officer, James Mitchell, will provide business review; and Chief Financial Officer, John Lo will conclude the financial discussion before we open the floor for questions.

I will now pass it to Pony.

Okay. Thank you, Wendy. Good evening. Thank you, everyone, for joining us. During the third quarter of 2025, we achieved solid revenue and earnings growth. reflecting healthy trends across games, marketing services and fintech and business services. Our strategic investment in AI are benefiting us in business areas such as ad targeting and game engagement as well as efficiency enhancement areas such as coating and game and video production. We are upgrading the team and architecture of our June foundation model, whose imaging and 3D generation models are now industry-leading -- capabilities continue to improve, our investment in growing Tien Pao adoption and our efforts in developing get AI capabilities, we think we seen will gain further traction.

Looking at our financial numbers for the third quarter. Total revenue was RMB 193 billion, up 15% year-on-year. Gross profit was RMB 109 billion, up 22% year-on-year. Non-IFRS operating profit was RMB 73 billion, up 18% year-on-year. and non-IFRS net profit attributable to equity holders was RMB 71 billion, up 18% year-on-year. Turning to our key services, core communication and social networks combined MAU of resin and WeChat grew year-on-year and quarter-on-quarter, RMB 1.4 billion.

For digital content, T&D is paying -- ARPU solidifying its leadership position in music streaming. For games, Delta Force is now the top 3 game in China by gross receipts while Valorant successfully expand from PC to mobile. And in AI, we enhanced -- large-language models, compacts reasoning capabilities, especially in coding -- our full length image generation model is ranked first globally at 2 imaging models by aeroplane arena. And our 3D model is the top generative model of parting base.

I will now hand over to Martin for business review.

Thank you, Pony, and good evening and good morning to everybody. For the third quarter of 2025, our total revenue was up 15% year-on-year. VAS represented 50% of our total revenue, within which social networks subsegment was 17%. Domestic game subsegment was 22% and international games was 11%. Marketing Services was 19% of total revenue and FinTech and Business Services was 30% of total revenue.

For the quarter, our gross profit was up 22% year-on-year to RMB 109 billion. VAS gross profit increased 23% year-on-year to RMB 59 billion, representing 54% of our total gross profit. Marketing Services. Gross profit increased 29% year-on-year to RMB 21 billion, contributing 19% of total gross profit. And FinTech and Business Services gross profit increased 15% year-on-year to RMB 29 billion contributing 27% of total gross profit.

Turning to business segments. Value-added services revenue was RMB 96 billion, up 16% year-on-year. Social networks revenue was up 5% year-on-year to RMB 32 billion, driven by increased revenue from video accounts, live streaming service, music subscriptions and mini games, platform service fees. Music subscription revenue increased 17% year-on-year, boosted by growth in ARPU and subscribers. Music subscribers grew 6% year-on-year to RMB 126 million. Long-form video subscription revenue decreased 3% year-on-year. ARPU was stable our video subscribers declined 2% year-on-year to RMB [ 114 ] million due to the delay of drama series, Lost Ambition. Following its release at the end of the quarter, finally, Lost Ambition ranked among the most viewed drama series in China year-to-date.

Domestic games revenue grew by 15% year-on-year, primarily driven by Delta Force, Honor of Kings and Valorant. International games revenue increased by 43% year-on-year or 42% in constant currency, which is an unusually rapid rate due to recognizing revenue upfront on top of -- on copy sales of Dying Light, the beast and also due to the consolidation of recently acquired studios.

Moving to communications and social networks. For Mini shops, we're systematically building a more vibrant transaction ecosystem, resulting in continued rapid growth in GDP. With enhanced mini shop merchandise recommendations and thus, sales conversions by leveraging foundation model capabilities to better understand users' interests based on their content consumption with innovation. We rolled out new features to enhance merchandise discovery invasion.

For example, we added gifting capabilities in Weixin order and car page, leveraging Weixin social graph. We also upgraded the image search feature innovation, which users can use to scan objects, identify them and then shop for them in new shops. We also enhanced AI features in Weixin to provide new services to users and to promote greater usage Yambao with encouraging results. At Yambao feature in video accounts and official accounts comment boxes, summarizes content and also encourage users to ask follow-up questions and users like that feature a lot. We also enriched the Tencent News Feed in Weixin with Yambao generated content and facilitated user exploration of news-related topics, via the Yambao app.

Now with that, I'll pass on to James.

Thank you, Martin. For domestic games, Honor of Kings gross receipts grew year-on-year, benefiting from collaborations with the China Literature IPs, Node of the Mysteries and Fox Spirit Matchmaker. The game achieved 139 million daily active users during its tenth anniversary event in October, which featured Hero and Minion outfits inspired by Bronze Age -- artifacts. Delta Force ranked among the top 3 games industry-wide by gross receipts in the quarter, achieving over 30 million daily active users in September including over 10 million daily active users on PC, driven by new season content, extensive first anniversary events and a globally sports tournament.

We released Valorant Mobile on August 19 and it's become China's most successful mobile game launch year-to-date based on its first March DAU and gross receipts. Valorant PC continued to grow and achieved record high DAU and gross receipts in September, benefiting from esports themes weapon items. The mobile launch resulted in Valorant's combined monthly active users more than doubling from July's level to over 50 million in October.

Among our international games for Clash Royale Supercell released new auto chest mode merged tactics and extended its Trophy Road achievement system to 10,000 trophies in higher player engagement monthly daily active users and gross receipts achieved all-time highs in September. Gross receipts increased more than 400% year-on-year during the third quarter. Gross receipts of Poppy Mobile also grew year-on-year in the third quarter, benefiting from ancient Egyptian themed outfits and innovative acute with emo sound effects in a 2-player glider and collaborations with transformers and Lotus cars.

Our Polish subsidiary, TAC land released a new game in its Dying Light series called Dying Light: The Beast, which has achieved a very positive average user review score on steam and which contributed to our international game revenue growing unusually quickly during the quarter due to the upfront revenue recognition of copy sales. The Marketing Services revenue increased 21% year-on-year to RMB 36 billion, underpinned by ad spend growth from all major advertiser categories. Impressions grew year-on-year as we enhanced engagement and increased at load across video accounts, mini programs and -- Search. Average CPM increase year-on-year as we upgraded our at -- foundation model with more parameters and captured additional closed loop marketing demand.

We introduced our automated ad campaign solution, AI marketing us through which advertisers can automate targeting, bidding and placement as well as optimize our creation improving their return on marketing investment. By inventory, video accounts and rich content and transaction system and its upgraded recommendation algorithms through stronger user engagement. Increases in DAU and time spent per user contributed to ad impression growth. advertisers increasingly adopted our marketing tools to drive traffic to their short videos, live streams in many shops.

For many programs, increases in activations and time spent, attracted ad spend for many drama and mini games to promote their contact. And fruition search increases in commercial query volume and kick-through rates contributed to notable revenue growth. We improved the relevance of search ads by upgrading our large language model capabilities and optimize some sponsor results to better match user queries.

Looking at FinTech and Business Services. Segment revenue was RMB 58 billion, up 10% year-on-year. FinTech services revenue grew by a high single-digit percentage, primarily driven by commercial payment services and consumer loan services. For commercial payment volume, the year-on-year growth rate was faster in the third quarter than the second quarter. online payment volume continued to grow robustly, while off-line payment volume improved, particularly in the retail and transportation categories.

For consumer loan services, our nonperforming loan rates remained among the lowest in the industry and improved year-on-year, reflecting our prudent risk management practices. Turning to Business Services. Despite supply chain constraints on sourcing GPUs, revenue grew at a teens rate year-on-year in the third quarter, benefiting from higher cloud services revenues and increased technology service fees generated from rising mini shop e-commerce transaction volumes.

Revenue from our cloud storage and data management products, namely Cloud Object Storage, TC House, and factor GB grew notably year-on-year due to increased demand, including from -- automotive and Internet companies. And for WeCom, we launched an AI summarization feature generate project recaps and provide advice at some users e-mails and conversations to hand some project collaboration efficiency.

And I'll now pass to John for the financial review.

Thank you, James. For the third quarter of 2025, total revenue was RMB 192.9 billion, up 15% year-on-year. Gross profit was RMB 108.8 billion, up 22% year-on-year. other gains were RMB 0.5 billion compared with gains of RMB 3 billion in the same period last year, mainly due to lower subsidies and tax rebates as well as provisions paid for some receivables during the quarter.

Operating profit was RMB 63.6 billion, up 19% year-on-year. Interest income was RMB 4.3 billion, up 7% year-on-year, driven by growth in cash reserves. Finance costs were RMB 3.8 billion, up 6% year-on-year due to forward movements and high interest expenses. Share of profit of associates and JV was RMB 7.8 billion with RMB 6 billion in the same quarter last year. On a non-IFRS basis, share profit was RMB 10.3 billion, up from RMB 8.5 billion in the same quarter last year, driven by associated company specific factors, including this growth and improved operational efficiency.

Interest expense increased by 10% year-on-year to RMB 9.8 billion, mainly driven by operating profit growth. on IFRS basis. Diluted EPS was RMB 7.575 per up 19% year-on-year, outpacing non-IFRS debt group for growth due to reduced share count after our share buyback. Our weighted average number of shares, which we use for calculating quarterly diluted EPS decreased by 1% year-on-year.

On non-IFRS financial figures, operating profit was RMB 72.6 billion, up 18% year-on-year. Net profit attributable to equity holders was RMB 7.6 billion, up 18% year-on-year. Moving on to gross margins. Overall gross margin was 56%, up 3 percentage points year-on-year by segment as gross margin of 61%, up 4 percentage points year-on-year, mainly driven by greater contributions from certain internally developed high-margin games. Marketing Services gross margin was 57%, up 4 percentage points year-on-year due to higher contributions from high-margin revenue streams, including video accounts and Weixin search.

FinTech and Business Services gross volume was 50%, up 2 percentage points year-on-year due to improved revenue mix within fintech services. On third quarter operating expenses. Selling and marketing expenses were RMB 1.5 billion, up 22% year-on-year, reflecting increased promotional efforts to support the growth of AI native applications and games. R&D expenses rose by 28% year-on-year to RMB 22.8 billion, primarily due to higher staff costs and increased infrastructure investment to support our AI initiatives.

G&A, excluding R&D expenses increased by 2% year-on-year to RMB 11.4 billion. At quarter end, we had approximately 11,000 employees, up 6% year-on-year or 3% Q-on-Q, primarily reflecting headcount conditions for both games and our technology platform, including AI-related accounts. Our third quarter non-IFRS operating margin was 38%, up 1 percentage point year-on-year.

Operating CapEx was RMB 12 billion, down 18% year-on-year, primarily due to supply changes. Nonoperating CapEx was RMB 1 billion, down 59% year-on-year, reflecting higher base last year relate construction. Free cash flow was RMB [ 38.5 ] billion, largely stable year-on-year as operating cash flow growth was offset by higher CapEx payments.

On a quarter-on-quarter basis, free cash flow was up 36% due to higher gains gross ratio. Net cash position was RMB [ 100.2 ] billion, up 37% Q-on-Q or 27.8% at RMB 27.8 billion, mainly driven by pre capital generation, partially offset by share repurchase as well RMB 19.2 billion.

[Operator Instructions]. The first question comes from Yao from Citi.

Good evening, management congrats on the strong results. My first question is about your gaming business. Your international gaming business growth rate has been accelerating for multiple quarters. So I just want to know what have you done right to achieve such good results? And how should we think about the growth trend going forward besides could you share more sorts on your international gaming credits? For example, will you continue investing high-quality overseas skim studios or bringing more developed games to global markets.

And my second quick question is about your CapEx. And this quarter, CapEx was around RMB 13 billion, but the cash payment for CapEx was RMB 20 billion. So how should we interpret the difference between these 2 figures? And is there any new update to your full year CapEx guidance?

Ray, why don't I start with the questions around games and the growth rate of the international game business, the strategy for the international game business. So the growth rate that we reported for the quarter for the international game business is substantially faster than the underlying trend line, and that's because during the quarter, we had the benefit of consolidation of newly acquired or recently acquired game studios, as well as the benefit of the upfront revenue recognition on comp sales for the game Dying Light the beast.

So going forward and looking into fourth quarter, you should expect the growth rate for the international games segment, subsegment to decelerate closer to the underlying trend line. In terms of the strategy for our international game business, yes, the drivers that you mentioned, we'll continue seeking to acquire game studios. We'll continue seeking to partner with overseas game studios and we'll continue seeking to bring more games that are made in China to a global audience as well.

In terms of CapEx, the difference timing gap between the accrual of server-related expenditure and cash payment, which can cause temporary mismatches between the two. In particular, the credit period for us to pay server suppliers is usually 60 days. In terms of the CapEx for 2025 to share with you in 2024, our total CapEx grew by 221% year-on-year was about 12% of the revenue. Previously, 2025, we guided total CapEx was as a percent of revenue to be at low teens for -- and the 2025 CapEx will be lower to our previous guided range, but the amount will be higher than that of 2024.

We will take the next question from Rishay Yap from Citigroup.

And also congrats on the solid results. First question, can management elaborate about your comment on the upgrading Hunyan team and also the Hunyan infrastructure. What should we be expecting to see from the upgraded version. And then does management have any updated view on how you Yambao might complement the AI capabilities that you have embedded into the wasting ecosystem the past few months?

And then second question is on your advertising marketing service revenue. So that's that automated ad campaign solution, the AIM pass better serve the smaller advertiser should we expect the solution to drive broader adoption rate for advertisers and drive higher ROI spending that support potentially accelerations of the ad revenue growth in the coming quarters.

Yes. In terms of the Hanyan team and the Hanyan architecture, we are actually hiring more tonnage talent, especially in the research area in order to complement our existing strong engineering team and they are complementary to each other. And we have also been in proving the Hanyan overall architecture across different dimensions such as improving the hardware and software infrastructure in order to support better data preparation to support better pretraining of the model as well as to support reinforce learning across different knowledge domains at scale. So these are the improvements that we are making more specifically on the Hanyan team as well as the Hanyan architecture.

Now in terms of how Yambao and Weixin complement each other. I would point to the fact that Weixin has actually introduced a number of AI features based on Yambao's capability. For example, in the prepared comments, we actually talked about the Yambao feature in video accounts and official accounts comment box which allows user to ask Yambao to summarize the content so that they can actually have very quick reference. And it actually encouraged a lot of interesting additional follow-up questions and follow-up comments. Based on the summary of what -- provided.

And we also enriched the Tencent News Feed in Weixin with Yambao generated content and allowed a lot of users to use that as a way to explore more news content-related news content as well as ask questions on the news content. And we're actually adding more and we are planning to add more functionalities of Yambao intuition. So those functionalities actually, one, serve the Weixin users better; and two, actually help Yambao about to gain a larger audience and more and more of these audiences find Yambao capability. duration and eventually become a Yambao app user. So that's sort of complementary to each other.

And this year, in terms of the automated campaign solution really if the automated ad campaign solution benefits or the advertisers to deploy it by enabling them to automatically reach inventories as well as user profiles that are more performant than the inventories and user profiles they were manually targeting. You're right to say that small- and medium-sized businesses are the first -- or the most eager to adopt this kind of product because they have the least legacy process to replace, and that's what we're experiencing right now. But we're also seeing bigger advertisers adopting as to how it has the experience of meters advantage plus automated ad solution overseas.

We will take the next question from Gary Yu from Morgan Stanley.

My first question is a follow-up on Yambao and Weixin. It appears that both the Yambao adoption and also Agenetic AI function Weixin on foundation model capabilities. But yet CapEx spending remains slowed according to our latest comment. So is there a risk that the company is not aggressive enough such that the potential application market could be lost to other companies who have either better model capabilities or more aggressive CapEx spending.

And my follow-up question is regarding some of the expense items, selling and marketing and. So when should we expect some of the internal AI adoption to benefit on cost efficiency in order to offset some of the investment that we have talked about on Yambao and game advertising.

Yes. In terms of Yambao adoption and also the CapEx spending at this point in time. We actually believe that there's no in sufficiency of GPUs for us at this moment. All our GPUs actually sufficient for our internal use. And there is some limiting factor for external cloud revenue.

Now in terms of the Yambao capability and -- model capability. As I talked about to Alicia's question, we are actually making a lot of improvement in terms of our team, in terms of our talent recruitment and in terms of our -- Huanyan have infrastructure and your overall process of the research. And I would say we are actually happy with the progress we have made already. And if you wait a little bit for our mix model, you can see, meaning for improvement in terms of the Huanyan capability. And I believe with the new improvements that we have been making, we'll continue to pick up pace on the Huanyan capability.

And at this point in time, we actually do not believe that there is a decisive better model in China as everybody is actually locked in the pretty close range and different models may be different maybe better in different use cases as well. So we don't believe we are really behind. And as we continue to improve our year capability. And we actually have been also seeing quite a good ramp in terms of Yambao engagement. So I think you see both the model capability as well as our AI products keep on improving.

Now in terms of the expenses, I think that this point of time, the G&A expense, especially the R&D is actually some of that is related to our AI investment. So there's a natural ramp up because new invest more in AI. And if you look at the benefit AI, at this stage, a lot of the efficiency gains are more on the revenue side. and the gross profit side. So you see pretty good growth in those items.

But in terms of the cost item, I would say we have already done a pretty big organizational optimization a few years back. And the organization that we have is actually an efficient and AI adoption actually allows our team to do more as well as instead of to reduce cost, which I think some other companies you are probably comparing with.

We will take the next question from Alex Yao from JPMorgan.

Congrats on a very, very strong quarter and also thank you for playing a very smooth and relaxing music before the call, I will insure I watch this TV drama after the earnings season. So 2 questions from my side. First one, you mentioned that Tencent is developing Agentic AI capabilities within region in the prepared remarks. Can you share your thoughts about how Agentic AI creates value to consumers in Weixin. I'm particularly interesting in your thoughts around Agentic-commerce. Second one is on CapEx.

Did I hear John, right? The CapEx for 2025 will be lower than the previous guidance, but higher than the '24 actual CapEx spending, if I get that right, does it reflect a change of AI chip availability or a change of investment strategy or a change of your expectation of a future token consumption.

Yes. On your second question, the answer is you heard it right. It's not a reflection of our change in AI strategy. It's not a change in terms of expectation of future token consumption. It is indeed a change in terms of AI chip availability. Now in terms of the Agentic AO capabilities, right.

I think the blue sky scenario is that eventually, Weixin will come up with an AI agent actually can help the user to essentially do a lot of tasks within AI within Weixin and leveraging AI, right? Because if you look at the ecosystem of Weixin, it has a very strong communications and social ecosystem and it has a lot of data that allows the agent to understand about the users, feeds as well as the intentions and interest. It has a very strong content ecosystem in the form of official accounts and video accounts. It has mini-program ecosystem, which essentially includes most of the use cases on Internet. It has a commerce ecosystem, which allows people to buy stuff and the payment ecosystem, which actually allows people to pay for it almost immediately.

So that is almost ideal assistant for users and understands about the users' needs and can actually perform all the tasks within the ecosystem. So that's the blue sky scenario. Now I think, how do we get there, right? At this point in time, it's actually very early stage in terms of development. Weixin is doing a number of things. In parallel, for example, it's introducing Yambao capabilities into Weixin so that we can test out a lot of the AI features on a stand-alone basis with innovation. It's also enhancing search with AI so that we can serve the users search and information collecting as well as analysis needs more efficiently. We are also starting to work on vertical AGM capabilities. And that's something that we are working on. We have not launched it yet. But then very likely, we'll be sort of working on a functionality one by one.

But eventually, we can actually sort of integrate all these giant capabilities as well as the AI features so that we can actually create this blue sky scenario of Weixin agent. I think in terms of Agentic commerce, I think there's the agent side and there's the commerce side. The commerce, we're actually making very good progress in terms of building up our e-commerce ecosystem and the mini shop is actually growing very nicely in terms of over time, as it continue to grow, right, and as we work on the vertical agents, at some point in time, we will have Agentic ecommerce as well. But that's a bit later in the process.

We will take the next question from the William Packer from Axon.

Congrats on the strong quarter. Firstly, Bloomberg have reported today that you've come to terms regarding a 15% commission with Apple within the WeChat ecosystem. Below their 30%, while you're probably prefer not to talk about the specifics in the press article. Could you help us think through the implications of your improving relationship with Apple and the impact on your business, particularly in mini games and domestic video games? And then secondly, as a follow-up, do you feel it was another very good quarter for marketing services with revenue growth accelerating. Could you help frame the growth outlook in the shorter term into 2026 and any new structural or cyclical factors to consider?

Well, in terms of Apple, right, what I could say is that, number one, we have a very good relationship with Apple, and we have sort of collaborated on a lot of different areas. And we have been in discussion with Apple to make the mini game ecosystem more vibrant. And we constructive with the progress that we've made so far. And I think at some point in time, there may be an official announcement. And I think everybody should wait for that.

And in terms of the advertising growth outlook, we think that it's largely a continuation of current trends. Overall, China consumer spending is subdued but are gently improving, which is a general tailwind for advertising spending on the demand side. And then in terms of the supply that we provide, we'll continue deploying more AI capabilities, including the AIM+ program automated ad campaign program that I referred to earlier.

We will take the next question from Charlene Liu from RCBC.

I think a quick one on R&D spending, especially as a percentage of revenue, how do we expect that to trend in the near and medium term? And then separately, we've seen really good GPM optimization at the cemental level. How should we think about overall impact to OPM taking into consideration potential uptick in AI investments, decretion costs and whatnot. Yes. So those 2, I wanted to kind of see how that margin net impact would sort of play out in the medium term.

But why don't I take the gross profit margin question. And first of all, to clarify, while the gross margins of our various segments have been trending upward over time, that's not purely or even primarily due to sort of optimization efforts per se. There are some subsegments such as cloud, where we have taken a number of measures to optimize profitability and that has flowed through into higher gross margins in the last 2 years.

But for most of our segments, the improvement in gross margins is more a function of the positive mix shift towards higher quality revenue streams that we've talked about a number of times in recent quarters. In terms of the dynamic between gross profit margin and operating profit margin, I would not put too much weight on that quarter-to-quarter because there are cost switch at an early stage in a product development cycle we would expense into R&D and therefore come below the gross profit line.

But then as we actually make the product more widely available, commercialize the product, we would move the costs from R&D expense into cost of service and, therefore, above the gross profit line. So I would probably focus more on revenue growth, operating profit growth without getting too fixated on gross profit margin versus operating profit margin.

We will take the next question from Kanes Ball from UBS.

Congrats on a strong result and thanks, management, for taking my questions. About the investment strategy. given the strong equity market performance year-to-date globally, could management share some thoughts on our investment portfolio and strategy and direction. So basically, how should we deploy or recycle our capital.

So as you point out, markets have been quite buoyant both in terms of price and in terms of liquidity. And so we've been taking advantage of that buoyancy to more actively recycle our portfolio primarily via some on market sales of our investment holdings. We've also been new investing in some emerging growth opportunities as well as our normal sort of focus areas such as games and digital content. But overall, year-to-date, divestments have exceeded investments by over $1 billion. And we've been actively investing in some interesting AI start-ups, particularly in China, where we can see a sort of new way for value creation ahead.

So we will take the next question from Robin Drew from Bernstein.

I guess 2 questions on gaming, please. One is -- if we look at the shoot of genre, I think that there used to be a bit of a change of guard with Battlefield, Delta Force, our operator is now doing quite well. I would be curious your thoughts on what you think is happening at the genre level? And for Delta Force specifically, what it would take what's being planned to get the game #2 -- from #3 closer to the top 2 games. Is it realistic to expect that, that happens at some point or not?

And I guess a follow up on an earlier question, on the mini games developments, be curious if you could try and dimension some of the relative contributions of in-app advertising versus in our purchases on Android right now and whether we think that this discussion going on with Apple is primarily on mini games has been reported or -- is there a broader discussion going on about what could potentially go on about the broader games business as a whole.

Robin, so in terms of what's happening with first-person action games then outside China, as you say, there may be a changing of the guard. Within China, I think that Delta Force has obviously been performing gratifyingly well, but Valorant has had an exceptionally strong year. And then peacekeeper elite, arena breakout cross-fire mobile, pretty much all of first-person action games have actually been growing DAU or growing monetization or mostly both during 2025 year-to-date. So to me, that's not really changing for the guide. It's more expansion of the Royal Guard, if you will, which I think speaks to the fact that first-person action games the leading games for -- in the rest of the world, they're not yet the leading game genre in China, but with Delta Force and Valorant and Peacekeeper Elite, the rest were seeking to bring them to the position that they should enjoy.

In terms of growing Delta Force further then we're really embracing platformization with our biggest games. And in a Delta Force unusually is sort of built from day 1 to support platformization in -- its modularity -- with more platformization, we can also support more new modes. And then one of the new modes that has done very well in pieces in PUBG Mobile and over time, we'll seek to nurture and Delta force is user-generated content.

And then we'll continue to add player versus environment content. We'll continue to strengthen the stream ecosystem and generally apply the experiences that we've accumulated over 17 years of launching 40 first-person action games in China to Delta Force.

And then on your second question, the stories report, the stories referred to mini games, not through app-based games. And at this point, the majority of the mini game revenue is in our purchase rather than in our advertising, so with theoretically benefit.

We will take the next question from Thomas Chong from Jefferies.

Thanks management for taking my question and congratulations on a very strong set of results. My question is on the SBS side. Given that we are emphasizing more on the consumer loan side, I just want to get some color with regard to the macro environment. Is this the fact that we need to take into consideration about our consumer loan revenue growth. And on the -- if we look into our cloud revenue, how should we think about the growth rate going forward? Should we kick into -- tax spending? Or should we expect the growth may decelerate because of less CapEx?

So in terms of the FBS, particularly with respect to Fintech, I think if you look at the fintech, there are major businesses within fintech. One is our payment business, second one's Wealth Management. The third one is loans, right? And in terms of macro environment, macro environment has the biggest bearing on the payment business because payment business is already very big. It tracks pretty closely with consumption growth in China. And there was a time in which the consumption growth was actually in more challenging state. I think over time, it's gradually improving. And what we see is -- in China, the consumption growth has been slow, and it's mainly due to the fact that a lot of consumers ramp up the savings during a period in which their balance sheet was actually sort of dragged down by the decline in property prices.

So unlike a lot of the other economic downturns around the world, which are driven by excessive credit and a lot of people sort of would go bankrupt, right? In China, it's just sort of people have resources, but then they decide to save more instead of spending more. We actually sort of -- so that's why we think there is actually potential for consumption to grow if people start to feel that they are secure now with the additional savings. And at the same time, if our property prices stop declining, I mean people will probably begin to spend more. I think this year, we have seen stock prices have been set pretty strong, and that adds to the household balance sheet and that is slightly a positive factor.

And at the same time, if you look at consumer loans, right, because people are not stretched from a balance sheet perspective, they're just sort of saving more it's not actually sort of affecting consumer loans delinquency that much. And by the way, we have been sort of very self-constrained in terms of extending loans in terms of loan amounts and also because of the data that we have, right? Our underwriting is actually very conservative, very data-driven and delinquency is among the industry leading. So that's essentially on the fintech side.

In terms of cloud business, I think we have been increasing our revenue finally sort of this year, right? In the past few years, our revenue has not grown that much, but our gross profit has grown very significantly. And this year, we're growing both the revenue as well as the gross profit and the business is actually sort of profitable. One constraint of cloud business growth is availability of AI chip because when AI chips are actually in short supply, we actually prioritize internal use as opposed to renting it out externally. And the other way to say is if there is not an AI supply constrained and our cloud revenue should be growing more.

We will take the next question from John Choi from Daiwa.

I just want to quickly follow up on the advertising business. I think another strong quarter, as you said. But I think in last quarter, management mentioned that it was more due to AI implementation. But for this quarter, can you kind of elaborate a bit more how impact from AI and how that has reshaped overall conversion and pricing for a business. So if you take that out organically what could kind of growth could be seen? And also just on the quickly, a quick follow-up on the payment side. I think Martin just mentioned that the overall household spending has high relation. But you also, I think, mentioned the retail and transportation category has done well on volume growth. especially on the grassroots side, have you noticed any trends that we are seeing on industry-specific levels? And in terms of the transactions or the transaction size that gives us more confidence that over the past couple of quarters to see the improvement trend.

Why don't I take those? So in terms of the advertising revenue, roughly half of the growth or about 10 points was due to a higher CPM, which contribute primarily to AI supported ad tech as well as to close loop benefits. And then the other half was due to increased impression volume, which reflects increased user engagement and increased -- in terms of the commercial payment volume trends, then there is a measured improvement. As Martin spoke to, it's positive for China consumers accumulated substantial savings above trend savings in recent years. So they may be less worried by property price fluctuations are more receptive to the stock market performing well than would otherwise be the case.

Given the substantial pent-up spending power. And we have seen that the online payment volume continued to grow quite steadily through the weaker periods and now through this more stable period. But the off-line payment volume, which had been very suppressed and under pressure for a period of time has also started to recover.

So while online payment volume is growing faster than offline payment volume. The gap has been narrowing as off-line payment volume has improved in categories speeding transportation and retail, which I suppose reflects people going out and about more often.

But I have to stress, such improvement is still pretty nascent. So we actually need to see it for a few more months in order to sort of have more confidence and saying this is a trend.

We will take the last question from Ronald Keung from Goldman Sachs.

So I have a question on advertising -- is following on what you hear how the AI marketing plus product, any early data points on the performance and ROI for merchants on that. And I also see you mentioned mini shops in one of the early bullets in the results. So could you quantify the potential of that add potential that I'm particularly looking for the increasingly vibrant many shop transaction ecosystem, the have potential there?

And then my second question, I just want to ask about the analogy from lesion and Q2 because we have seen Facebook and Instagram kind of certain different cohorts within the company, and we have been serving those with -- in Q2 as well. Any parallels and differences, how we see Weixin as our key product, but also potentials for different products serving cohorts within domestic China, just an open question -- open-ended question.

Why don't I start with the question around AIM+. So when you introduce this automated ad campaign system, the biggest sort of keep for the advertisers is allowing us as the platform parade to actually manage the bidding process on their behalf. And of course, there's a degree of internal conservatism within the bigger advertisers as to whether to entrust the platform to manage the price or not. And typically, the larger advertisers will run the automated and the manual processes in parallel for a period of time and compare the ROI to verify whether the automated process is delivering more performance or not. And we've turned on that automated bidding tool relatively recently. But the early results positive, those advertisers who are adopting the automated solution are enjoying superior returns. And therefore, the plant of our advertisers and the percentage of our advertising spending is going through AIM+ are steadily increasing.

And in terms of the mini shops, then I think you can benchmark the advertising to GMP ratios of the incumbent e-commerce marketplaces in China, across the GMP for mini shops, which is growing very quickly. And that would give you a sense of the advertising revenue potential from the mini shop operators. So that's on the advertising question.

Yes. In terms of Weixin and QQ and then sort of analogy for rest of world, for example, Facebook and Instagram. I think it's a very interesting question. And I think there's some fundamental differences, right, in the sense that, number one, if you look at Instagram and Facebook, they are primarily social networks, right? And if you look at Weixin and QQ, they are both communication network and social networks. So if you have social network, and it's sort of content-based, then it's actually easier for you to have different groups of people dialing in and reading different content versus its communication that the network effect of communication platform is actually stronger.

And the other thing is China there's much more mobile-oriented versus, I think, the rest of the world, there's still a lot of people who are using PC and in PC, then Facebook seems to be sort of adding more PC users. And I think 30 is -- if you compare Facebook and Instagram and Facebook tends to sort of keep the more mature users and Instagram sort of more younger people. But in China, it's actually different between Weixin and QQ, right? The QQ users are primarily -- younger in nature.

So I think there is some kind of fundamental of differences, but at the same time, Weixin and QQ are serving different user group. And different use cases, a lot of the younger people also have Weixin, but then they use QQs that they would not be seeing their parents and their teachers and some people at younger people would not be seeing their colleagues.

And so I think going forward, when we continue to evolve QQ as a product, right? Then we should actually latch on to these features and the user needs and sort of make it more fun, make it very differentiated from Weixin. Weixin serve our purpose, whereas sort of QQ would serve the younger people, more active people, and we should sort of try to provide a lot of functionalities. You can meet new people, you can sort of more of your interest-based groups. And I think that's the way we are going to be differentiating QQ and Weixin and make sure that they serve our users in different use cases and scenarios.

Thank you. We are now ending the webinar. Thank you all for joining our results -- today. you wish to check out our press release and other financial information, please visit the IR section of our company website at www.tencent.com. The replay of this revenue were also soon available.

Thank you and see you next quarter.