Tencent Hldgs Unsp/Adr

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. At this time, all participants are in a listen-only mode. After the management's presentation, there will be a question and answer session. For participants who dial in by phone, if you wish to ask a question, please press five on your telephone to raise your hand. If you are accessing from the Tencent meeting or rule meeting application, please click the raise hand button at the bottom left. 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 propelled in accordance with IFRS. For a detailed discussion of risk factors in a non-IFRS measures, please refer to our disclosure documents on the IR section of our websites. 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 Lau will conclude a 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 re-enforced 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 increase over 20% on upgrade the recommendation algorithm and enrich content ecosystem. Our marketing services revenue growth outperforms the industry. Starting 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 increase the enterprise demand for our industry leading test and SaaS products and supply chain optimization. Internationally, our international games business surpassed 10 billion US dollars 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 market as we expand partnership with key clients and drove a higher adoption of our flagship cloud product. The robust operating leverage and cash flow generated by our core businesses enable us to set up investment in AI. During the year, we upgrade our team with top tier AI talent and build processes for improving foundation model intelligence in a systematic way. We began deploy new AI capabilities in services, including Yuanbao and Weixin and core type products. Looking at our financial numbers for the first quarter, total revenue was 194 million RMB, up 13% year-on-year. Gross profit was 108 billion RMB, up 19% year-on-year. Non-IFRS operating profit was 70 billion RMB, up 17% year-on-year. And non-IFRS debt profit attributable to equity holders was 65 billion RMB, 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. will 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 worlds of bits 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, tick rates that are low compared to value provider 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 effects 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 access 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've also invested decades building a payment network of difficult to replicate rails into partner banks, merchants, and connecting them with more than a billion consumers, which brings its own network effects. And our mobile payment tick rates are already among the lowest in the world, which we believe makes competing with us on price highly economical. 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 non-player 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, AimPlus, 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 contents, 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 non-performing 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 rebuild our AI infrastructure for pre-training and reinforcement learning. We're now iterating more intelligent models at a faster pace. Huan Yuan 3.0 is in internal testing and currently represents a bigger step in capabilities versus Huan Yuan 2.0. Then 2.0 was versus 1.0. For multimodal capabilities, our 3D text-to-image and word 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're 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 Huan Yuan 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 claw bots 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 range models. However, improving the performance of Huanyuan will enable us to offer new, unique to Weixin agent capabilities. So the Weixin and Huanyuan teams will work increasingly closely together going forward. Speaking of claw bots, 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 skill hub. CloudBots are upgrading AI from thinking to doing via autonomous workflows and continuous task execution. Users control this new generation of AI tools through command line interfaces in their existing communication apps, which generally means Weixin and QQ in China is the efficient for users to interact with digital agents in a place and format where they are already interacting with human contacts. 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 two biggest new AI products, Huanyuan and Yuanbao, was 7 billion RMB in the fourth quarter of 2025 and 18 billion RMB for the full year. These figures are only for Huanyuan 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 Huanyuan, 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 from 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 capabilities 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, break even 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 5 billion RMB 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, codenamed NAP, in the same way. With that, let me pass to James.

Thank you, Marcin. For the fourth quarter of 2025, our total revenue was up 13% year-on-year. The AAS 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 108 billion renminbi. The AS gross profit increased 21%, marketing services increased 22%, and fintech and business services increased 17%. Turning to business segments, value-added service revenue was 90 billion RMB, up 14% year-on-year. Our social network revenue grew 3% year-on-year to 31 billion RMB, 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 Supercells 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, Chaps 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 three 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, missed bloom skins, limited time modes and e-sports 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 up players' cards, providing a more dynamic competitive experience. Wuthering Waves won the Player's 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 ruins maps, and new characters. Warframe launched a major update, The Old Peace, featuring a new storyline, two 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 41 billion RMB. 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 spent 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's 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 61 billion RMB, 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 volume 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, a number of users each increase 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. 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 playback 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 Q4 2025, total revenue was 194.4 billion RMB, up 13% year-on-year. Gross profit was 108.3 billion RMB, up 19% year-on-year. Other gains were 1.3 billion RMB compared with other gains of 2.5 billion RMB in the same period last year due to lower subsidies and tax rebates. Operating profit was 60.3 billion RMB, up 17% year-on-year. Interest income was 4.8 billion RMB, up 22% year-on-year, driven in part by growth in cash reserves. Finance costs were 3.6 billion RMB compared with 2.5 billion RMB in the same quarter last year, primarily due to Forex loss this quarter versus Forex gains in the same quarter last year. Shared profit of associates and joint venture was 6.8 billion RMB compared with 9.3 billion RMB in the same quarter last year. On an eye-to-eye basis, share of profit was RM9.1 billion up from RM7.7 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 12.5 billion RMB. On a non-IVRS basis, diluted EPS was 6.966 RMB up 18% year-on-year, outpacing non-IVRS net profit growth due to reduced share count up to out-share buybacks. On Q4, non-Ivirus financial figures operating profit was 69.5 billion RMB, up 17% year-on-year. Net profit attributable to equity holders was 64.7 billion RMB, 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 by segment. Vast gross margin was 60%, up 4 percentage points year-on-year, primarily driven by greater contributions from internally developed high-margin games. Marketing services gross margin was 60%, up 2 percentage points year-on-year as AI-powered marketing services brought strong growth in high-margin revenue streams, particularly video accounts and business search. FinTech and business services cross-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 quote of all operating expenses, selling and marketing expenses were 13 billion RMB, up 26% year-on-year, reflecting increased promotional efforts to support the growth of our AI-native application and games. R&D expenses growth, rose by 20% year-on-year to 23.8 billion renminbi, primarily due to high staff force and increased depreciation expenses driven by our AI investments. G&A, excluding R&D expenses, increased by 8% year-on-year to 12.5 billion RMB due to higher staff force. At quarter end, we had approximately 116,000 employees up 5% year-on-year or 1% Q&Q, primary reflected headcount, additions to games and our technology platform, including AI-related headcount. Our fourth quarter non-IA virus operating margin was 36%, up 1 percentage point year-on-year, For fourth quarter, operating CapEx was 16.9 billion RMB, increasing 41% quarter-to-quarter as we accelerated investment in server infrastructure. Year-on-year operating CapEx decreased by 51%, reflecting concentrated CapEx spending in fourth quarter 2024, leading to a high base effect. On operating CapEx was 2.7 billion RMB, up 60% year-on-year due to higher facility-related investments. Free cash flow was 34 billion RMB, increasing over six times 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 queue-on-queue basis, free cash flow decreased by 42% due to seasonally lower gain, gross receipt, and seasonal settlement of student accounts payable. Net cash position was 107.1 billion RMB, up 5% quarter-and-quarter, or 4.7 billion RMB, mainly driven by free cash flow generation, partially offset by share repurchase of 19.6 billion RMB, and net cash flows of 6.9 billion RMB, primarily relating to investment in other corporations. For the full year of 2025, we repurchased 153 million shares with a total consideration of HK$80 billion, a 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 event, we are proposing an annual dividend of HK$5.3 per share, reflecting an 18% year-on-year increase. This dividend will be payable to shareholders on 1 June 2026. Thank you.

Thank you, John. We shall now open the floor for questions. If you are dialing in by phone, please press five to raise a question, then press six to unmute yourself. If you are accessing from the Tencent meeting or Wu meeting application, please click the raise hand button at the bottom. We will take one question from each analyst in the interest of time. So the first question comes from Kenny Spong from UBS.

Hi, good evening, management. Thanks for taking my questions. I have a question on the AI front versus the margin. In our prepared remark, we expect to increase 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 But given the recent market development, has management views shifted? How are we prioritizing allocating resources or KPI that we monitor? Is that a development of a SOTA last language model or user engagement or token growth IE2P solutions? Thank you.

Kenneth, why don't I start and then Martin may compliment. 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 stepped-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 represent an opportunity for us to expand our footprint, 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. uh you know we'll continue to make uh selective hires but we actually feel we have uh you know really a state-of-the-art team uh ai talent team already in place and uh you know we've been able to put it in place uh not only through through compensation as an incentive but also through creating uh the right culture for the team through allocating uh you know the roles of the team and 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 those that compute for different use cases, you know, the priority right now is, you know, Hunyuan and new AI products more generally. You know, the CLAW products are inherently distributed in nature and they can themselves source compute, you know, from local devices, from, you know, multiple clouds, you know, 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.

Thank you, James. Reminder that each analyst, please only ask one question. We can take your follow-up later if we have more time. Next question comes from Robin Zhu from Bernstein.

Thank you, management, for taking my question. 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?

Thank you.

OK, well, I think from an ROI perspective, we have already seen very good ROIs when we apply AI into our existing businesses. 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, oh, 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. I think that's level number one. Then level number two is an investment into new AI products. On that front, I think we would be seeing new investments first. There's not that much of a revenue, especially in the context of China. unlike in the US 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 revenue 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, 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, 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?

Oh, the last question was, if we think about the AI stack between kind of you know, 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, you know, areas where we think these would be commoditized and, you know, it's okay just to have something?

I think at this point in time, it's actually very dynamic. In a fast-moving market, I think it's very difficult for someone to say, oh, there will be one layer more important than the others. 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. Actually, we have to build the team from scratch. once again, and now it's actually sort of, as James said, you know, 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, you know, playing into our strength, right? Because then suddenly you don't even need to have that model capability, but it actually plays into 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, it's actually our core strength too. 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 played out itself and hopefully it will become best of breed in all layers.

Thank you. We will take the next one question from from Goldman Sachs.

Thank you, Pony, Martin, James, John, and Wendy. So I want to ask about the AI agent possibility. potential with the recent launch of QClaw WorkBuddy, and we saw the scale hub 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 we plan to differentiate other parts of the stack, for example, models? Thank you.

I think Claw is actually a very... exciting concept, right? And it actually sort of presents a decentralized model or a decentralized regime for how AI works in this world. So there's some parallel to sort of how the internet evolves, right? In the very beginning, when internet first appears, 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. And then when mobile internet comes, suddenly you see a multitude of applications coming up. And within the applications, there are applications which are completely mobile native, mobile applications. 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? seems to be sort of new. Everybody is trying to fight to become the AGI hegemon, a monopoly. 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. But the reality is not. You have multiple models becoming very strong, and they specialize in different kinds of activities. One in chatbot, the other one in 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 are fast followers too. And then there was a time in which in the 2C world, there seems to be the chatbot being 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. And it's supported by the infrastructure of cloud. And each one of the claw has to figure out its unique value proposition to win the heart of the users. And the claws also make use of not just the cloud, not just its 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, you know, there's a lot of opportunities for us, right? You know, 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 would try to come up with their own claws, right? You know, and their own agentic capabilities and different models would also sort of, you know, 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, you know, we just need to, as I said, right, build expertise in the different layers, you know, in the model layer, in the product layer, in the infrastructure layer, And each layer would have their own specific value proposition to win its own usage.

Thank you, Martin. We will take the next question from Ellie John from Macaulay.

Thank you so much, management, for taking my question. 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 Kunyuan alongside with the other LLMs, you know, kind of towards the prosumers and consumers, how do we potentially prevent from the other LLMs diluting our own foundation models value in the longer term? Thank you.

I think that in terms of Tencent's unique value proposition or what we can bring to users in the CLAW era, that 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's touched on them, but one of those attributes is that We're a company whose, you know, capabilities span across, you know, PC, mobile, cloud. We're a company whose capabilities span across applications and the World Wide Web, you know, just as the agentic clause, you know, 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 World Wide Web experience. And, you know, now with these agentic capabilities and flaws, then there's an opportunity for, you know, decentralized experiences such as mini programs to to be turbocharged and themselves develop far more powerful capabilities than they enjoyed in the past. So, you know, that's, you know, why we think there's inherently a natural fit between our capabilities and our interests and the deployment of these agents or clause. And, you know, that's why, you know, we're seeing one reason why we're seeing consumers and prosumers enthusiastically adopting our own agents and clause services. In terms of The part of your question about preventing other large language models diluting our model's value, I may not understand the premise correctly, but I don't see that happening. If you use these clause, 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, all models B through Y in the middle. And that's part of the appeal of the clause. 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. The clause that are successful will be clause 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.

Thank you. We will take the next question from Alicia Yap from Sydney.

Hi. Good evening, management. Thanks for taking my questions. I have a question related to the physical AI. So considering the proliferation 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 assessments of Tencent's capability and also the competitive strength in the future physical AI era? Thank you.

Alicia, I think your point is a reasonable one that there is already a in a computer aided design capabilities. And one would naturally expect AI to supplements 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 a 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. uh but you know it's ultimately a sort of a big niche uh and um you know it's one that uh you know we are well positioned to address uh but but i wouldn't say it's you know the biggest opportunity uh ahead of us you know there's many larger more immediate opportunities thank you we will take the next question from john choi from taiwan

Thank you for taking my question. I have a question related to games and AI disruption. I've already started 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? Thank you.

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

Thank you. Just to add a couple more points, right? Number one, When you talk about AI disruption for games, that basically imply it's actually bad for the gaming industry. But I think gaming is actually one of the industries that would benefit from AI. Because when AI proliferates, I think people would have more free time at their hands and the demand side would actually increase significantly for AI. the gaming industry, which I think, you know, is a rare certainty in the sort of phase of AI proliferation. And number two is, you know, the availability of great tools would be available to new developers, but it also will be available to very organized teams and highly talented developers that are already running big evergreen games. I would say when a tool is actually available, it's gonna 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 new 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, when there's a multitude of players of innovations, right? A lot of times, I think, you know, what we saw in the gaming industry is like, you know, 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.

Thank you. We will take the next question from Alex Yao from JP Morgan.

Thank you, Wendy. Thank you, management, for the opportunity. I want to follow up on the AI cloud side of the business, given very strong demand for AI computes. But on the other hand, also price inflation for the server, AI servers are 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 get more market share or even potentially, you know, more than fully pass through the cost inflation to capture more profit. Thank you.

Thank you for the question, Alex. So, you know, first of all, I'd start by saying that, you know, clearly there is a surge in demand for sort of AI compute, but it's not only for AI compute. You know, when people utilize the agentic tools that we've been discussing, that they're using them and they create software and, you know, that software, you know, then primarily it needs to be executed. And when it executes, most of it is not executing on, you know, GPU, it's executing on CPU. And then it creates, as it executes, it creates memory demands. 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 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. You know, the supply is prioritizing the biggest, most regular customers, which are the hyperscalers such as ourselves. And therefore, you know, the customers, the smaller cloud providers, you know, no longer have certainty that they can source supply and they need to come to the hyperscalers. And, you know, the hyperscalers have been operating at low margins. And so, you know, 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, you know, how we sort of value capture in this dynamic environment, then, you know, one broad principle is, you know, we seek to deliver, you know, more value through, you know, enrichment. And so enrichment means that at a minimum, if you have value, 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 a 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've been on. And that's part of how Tencent Cloud has moved from very substantial losses four 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. Thank you.

Thank you.

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

Hi, good evening, and thank you for the opportunity. 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 late comer in AI. In the US, we have also observed that it's becoming very difficult for some of the late comers to catch up, even for those that have very high resources in terms of compute talents and data so so how does management get comfortable and confident that we won't be following the same path in terms of you know lagging behind not able to catch up and around areas on compute modeled applications thank you

Yeah, 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 opportunities new frontier that's opened all the time. So I think when every, it's already happening. If you look at the model, 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 it. And then suddenly sort of claw came around, which basically further decentralized the whole AI landscape. So in the future, we actually felt, oh, there will be just like apps, right? There will be a lot of different tools permutations of how AI will be packaged from model to the product to agent and existing services will be having different agentic capabilities. There will be new agentic capability coming around on mobile, on PC. 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'll 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 of the application layer, be it Weixian and be it our ecosystem of having... you know communication and and presence on pc and mobile and a lot of infrastructural capability including security and cloud and payment and you know all these elements can be packaged together you know in the new uh race of ai so it's not sort of you know one race it's actually sort of you know a world of many many races and uh i think you know that would you know, 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, you know, you know, being late, but I'd be worried about, you know, if we're not innovating fast enough, right? You know, which I think, you know, we, as we restructure our Huan Yuan team and as we started to invigorate all our product teams to start innovating with products. And I think, you know, that's actually happening in a very exciting way for us.

Thank you. We will take the next question from William Packer from BNP. William, your line is open.

Hi, management. Thanks for taking my question. 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. 10 cents a potential major beneficiary to what extent should we expect these cuts to flow through to 10 cents gross margin or would they be shared with other stakeholders such as consumers gaming partners or perhaps tax revenue thank you

Hi, Will. So, you know, happily in this case, the press reports were based on the sort of objective reality of an Apple, you know, 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, you know, there should be a good flow through, you know, 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 Apple take. And so that flows through to us. If by taxes you're referring to us paying a teen's 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 that 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 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 multi-step positive journey. Thank you.

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

Well, thank you for taking our questions. 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, for instance, all AI priorities. Thank you.

Thanks for your question. I think at this point of time, it's not the most critical thing that will be focused on. So if you look at the chip, there is a difference between training chip and inference chip. 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, 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 China. the training space where there's essentially one or two players who can actually command a very, very high margin. 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 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, over time, I think the market would actually 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're very focused on leveraging the best chip to train our model. Our Hunyuan 3.0 is going to be much better than Hunyuan 3.0, 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'll 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.