Q1 2026 Tencent Holdings Ltd Earnings Call

May 13, 2026

Speaker #1: Ain't nothing I don't know where you've been. So many lies instead. I do it all again, all around. Ain't nothing all of those words we part.

Speaker #2: Today and a good evening. Thank you for standing by. Welcome to Tencent Holdings Ltd 2026 first quarter results announcement webinar. I'm Wendy Huang from Tencent IR team.

Wendy Huang: Good day, and good evening. Thank you for standing by. Welcome to Tencent Holdings Limited 2026 Q1 Results Announcement Webinar. I'm Wendy Huang from Tencent IR team. At this time, all participants are in a listen-only mode. After 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 5 on your telephone to raise your hand. If you are accessing from the Tencent meeting or group meeting application, please click the Raise Hand button at the bottom left. 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 it may not be realized in the future for various reasons.

Speaker #2: At this time, all participants are in a listen-only mode. After 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 5 on your telephone to raise your hand.

Speaker #2: If you are accessing from the Tencent meeting or group meeting application, please click the raise hand button at the bottom left. And please be advised that today's webinar is being recorded.

Wendy Huang: If you are accessing from the Tencent meeting or group meeting application, please click the Raise Hand button at the bottom left. 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 it may not be realized in the future for various reasons.

Speaker #2: 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.

Speaker #2: 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.

Wendy Huang: 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. Chief Financial Officer John Lo will conclude with financial discussion before we open up floor for questions. I will now pass it to Pony.

Speaker #2: For a detailed discussion of risk factors and non-FIRS measures, please refer to our disclosure documents on the IRS section of our website. Now let me introduce the management team on the webinar tonight.

Wendy Huang: 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. Chief Financial Officer John Lo will conclude with financial discussion before we open up floor for questions. I will now pass it to Pony.

Speaker #2: Our Chairman and CEO, Pauline Ma, will kick off with a short overview. President Martin Lau and Chief Strategy Officer James Mitchell will provide a business review.

Speaker #2: And Chief Financial Officer, John Lau, will conclude with financial discussion before we open the floor for questions. I will now pass it to Pauline.

Speaker #3: Thank you, Wendy. Good evening. Thank you, everyone, for joining us. We start 2026 by making significant initial progress on our new AI products. We also continue to utilize AI to grow our existing core business.

Pony Ma: Thank you, Wendy. Good evening. Thank you everyone for joining us. We start 2026 by making significant initial progress on our new AI products, as well as continue to utilize AI to grow our existing core business. The Hunyuan 3.0 preview 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 OpenRouter Token measure since April 28th. Our productivity AI agent solutions have attained early traction, we believe that our WorkBuddy 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.

Speaker #3: The Hunyuan 3 Preview model built by our revamped team of AI researchers on the architecture AI infrastructure is a leader in its parameter size class.

Speaker #3: Delivering practical utilities and cost efficiency. And has been top ranked in open router token measure. Since April 28th. Our productivity AI agent solutions have attained early action and we believe that our work body is currently the most widely used productivity AI agent service in China.

Pony Ma: Our productivity AI agent solutions have attained early traction, we believe that our WorkBuddy 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.

Speaker #3: 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 deployment.

Speaker #3: Looking at our financial numbers for the first quarter, total revenue was $196 billion RMB up 9% year on year. Adjusting from for the impact on revenue recognition for our value-added services from the later spring festival this year, compared to last year.

Pony Ma: Looking at our financial numbers for Q1. Total revenue was yuan billion RMB, up 9% year on year. Adjusting from 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 yuan billion RMB, 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. Non-IFRS net profit attributable to equity holders was RMB 68 billion, up 11% year-on-year. Turning to our key services for communication and social networks, combined MAU of Weixin and WeChat grew year-on-year and quarter on quarter to 1.4 billion.

Speaker #3: Total revenue would have increased 11% year on year. Gross profit was $111 billion RMB up 11% year on year. Non-IFRS operating profit was $76 billion RMB up 9% year on year.

Pony Ma: 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. Non-IFRS net profit attributable to equity holders was RMB 68 billion, up 11% year-on-year. Turning to our key services for communication and social networks, combined MAU of Weixin and WeChat grew year-on-year and quarter on quarter to 1.4 billion.

Speaker #3: Excluding new AI products, non-IFRS operating profit was $84 billion RMB up 17% year on year. And non-IFRS net profit attributable to equity holders was $68 billion RMB up 11% year on year.

Speaker #3: Turning to our key services, for communication and social networks, combined MAU of WeChat and WeChat Group year on year and quarter on quarter to 1.4 billion.

Speaker #3: For digital content, Tencent Video solidified its leadership in animated series with eight animated titles ranked top 10 industry-wide in the first quarter of 2026.

Pony Ma: For digital content, Tencent Video solidified its leadership in animated series with eight animated titles ranked top 10 industry-wide in Q1 2026. For games, Honor of Kings and Peacekeeper Elite achieved record height in gross receipts during Q1 2026, while newly released creature collecting game, Roco Kingdom: World, achieved breakout success. Tencent Cloud AI agent solutions achieved rapid growth and healthy retention rate. Now I will hand over to Martin for the business review.

Speaker #3: For games, Honor of Kings and Peacekeeper Elite achieved record highs in gross receipts during the first quarter of 2026. While newly released Creature Collecting game Roku Kingdom World achieved breakout success.

Speaker #3: 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, Pauline.

Martin Lau: Thank you, Pony, good evening and good morning to everybody on the call. For Q1 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 sub-segment was 16%, domestic game sub-segment was 23%, and international games was 10%. Marketing Services was 19% of total revenue, and FinTech and Business Services was 31%.

Speaker #3: 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.

Speaker #3: As Pauline 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.

Speaker #3: Adjusting for the timing of the spring festival, total revenue would have been up 11% year on year unlike for like basis. By segment, vast represented 49% of our total revenue within which social networks subsegment was 16%, domestic game subsegment was 23%, and international games was 10%.

Martin Lau: 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 sub-segment was 16%, domestic game sub-segment was 23%, and international games was 10%. Marketing Services was 19% of total revenue, and FinTech and Business Services was 31%.

Speaker #3: 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 $111 billion RMB.

Martin Lau: Our gross profit was up 11% year-on-year in the first quarter to CNY 111 billion. VAS gross profit increased 9% year-on-year and represented 54% of our total gross profit. Marketing services gross profit increased at 19% year-on-year, contributing 19% of total gross profit. 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.

Speaker #3: Vast gross profit increased 9% year on year and represented 54% of our total gross profit. Marketing services gross profit increased at 19% year on year contributing 19% of total gross profit.

Speaker #3: 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.

Speaker #3: Over the last six 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.

Martin Lau: 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.

Speaker #3: Our new team is young, energetic, and cohesive, enabling us to make progress quickly in this highly dynamic AI era. In February, we re-engineered the system and process for pre-training and reinforced learning from the ground up.

Martin Lau: Our new team is young, energetic, and cohesive, enabling us to make progress quickly in this highly dynamic AI era. In February, we re-engineered the system and process for pre-training and reinforcement learning from the ground up. We re-architected the infrastructure to support robustness, scalability, and efficiency across pre-training data and reinforcement learning. On data, we expand 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 pre-training and supervised fine-tuning, and we scaled up to reinforcement learning. For evaluation, we're moving away from chasing public benchmarks that can be gamed. Instead, we evaluate our model through the latest exams, 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.

Speaker #3: We re-architected the infrastructure to support robustness, scalability, and efficiency across pre-training 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.

Speaker #3: On training, we upgraded the process for pre-training and supervised fine-tuning and we scaled up to reinforcement learning. And for evaluation, we're moving away from chasing public benchmarks that can be gamed.

Martin Lau: On training, we upgraded the process for pre-training and supervised fine-tuning, and we scaled up to reinforcement learning. For evaluation, we're moving away from chasing public benchmarks that can be gamed. Instead, we evaluate our model through the latest exams, 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.

Speaker #3: Instead, we evaluate our model through the latest exams, human tests, product feedback, and in-house tasks to see how the model actually performs in the real world.

Speaker #3: 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 de-risk scaling toward larger models.

Martin Lau: When we set out to build this model, the purpose was to build a cost-efficient and solid model for diverse applications and de-risk 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 move beyond narrow expertise and towards comprehensive intelligence, such as integrating reasoning, long context understanding, instruction follow, dialogue coding, and tool use capabilities. By co-designing inter-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 agentic tasks.

Speaker #3: 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 two-use capabilities.

Speaker #3: And by co-designing inference with model, we're able to reduce costs significantly so that the intelligence is in canonical enough to be used at scale.

Martin Lau: By co-designing inter-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 agentic tasks.

Speaker #3: 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 agentic tasks.

Speaker #3: Internally, the model has been deployed across 131 widely used internal products including Yunbao, QQ, and WorkBuddy. Providing valuable feedback and iterative improvement via co-design process.

Martin Lau: Internally, the model has been deployed across 131 widely used internal products, including Yuanbao, QQ, and WorkBuddy, providing valuable feedback and iterative improvement via co-design process. Externally, Hunyuan 3 Preview has been well-received by users and developers in real applications. It has ranked first among all models available on OpenRouter 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.

Speaker #3: 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.

Speaker #3: By token usage since April 28th, and continued its lead even after its three-period ended on May 8th. While significant strides have been made with Hunyuan 3 Preview, we view this as merely just the first step for Hunyuan large language models.

Martin Lau: 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.

Speaker #3: 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.

Martin Lau: By aggregating bigger and better data sets and scaling more powerful reinforcement learning, we can strengthen the model's contextual understanding, enhances agentic capabilities in areas including coding, and increase the model's general intelligence. Through co-designing and collaborating with other Tencent product teams, we're optimizing dataset selection and focusing reinforcement learning for high-value use cases. Beyond foundation models, it has become increasingly evident that agentic AI represents a breakthrough use case after AI chatbots have become popular. AI 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 ClawBot and WorkBuddy. These breakthroughs were made possible by more powerful models and by the harness infrastructure that allows models to utilize tools and act as interfaces that enable users to manage agents effectively.

Speaker #3: By aggregating bigger and better data sets, and scaling more powerful reinforcement learning, we can strengthen the model's contextual understanding and enhance its agentic capabilities in areas including coding and increase the model's general intelligence.

Speaker #3: Through co-designing and collaborating with other Tencent product teams, we are optimizing dataset selection and focusing reinforcement learning on high-value use cases. Beyond foundation models, it has become increasingly evident that agentic AI represents a breakthrough use case, after AI chatbots have become popular.

Speaker #3: AI agents are more valuable in uplifting productivity from initial use cases supporting programmers in creating code, such as without product to code buddy, to now catering to a wider range of workloads and occupations such as with flaws and work buddy.

Martin Lau: AI 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 ClawBot and WorkBuddy. These breakthroughs were made possible by more powerful models and by the harness infrastructure that allows models to utilize tools and act as interfaces that enable users to manage agents effectively.

Speaker #3: 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.

Speaker #3: Our platform inherently has many benefits, of hosting AI agents. As users can control AI agents through our communications and browsing interfaces such as WeChin, WeCom, QQ, Yunbao, and QQ Browser in addition to third-party applications.

Martin Lau: 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. 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 agentic 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.

Speaker #3: Users can also choose which model to use from a wide range of models based on their own needs and preferences on token costs and performance.

Speaker #3: 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 agentic AI deployment evidenced by the leading DAU of our product WorkBuddy.

Martin Lau: 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 agentic 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.

Speaker #3: 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 and label us to identify and provide complementary software and services, which in turn drives increased AI agents usage.

Martin Lau: The high time spent and high-frequency interaction with AI agents among early adopters act as a virtuous feedback loop to Tencent and enable us to identify and provide complementary software and services, which in turn drives increased AI agents 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 let pass on to James.

Speaker #3: 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.

Speaker #3: Now with that, I will pass on to James.

Speaker #2: Thank you, Martin. Turning to business segments, value-added services revenue was 96 billion renminbi up 4% year on year. Social network revenue was down 2% year on year to 32 billion renminbi, reflecting decreased reported revenue from app-based game item sales in China arising from the late spring festival.

James Mitchell: 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.

Speaker #2: 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 eight of our self-commissioned series ranking among the top 10 across all video platforms in China during the quarter.

James Mitchell: 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.

Speaker #2: We believe Tencent Video possesses competitive advantages in creating animated series, including our ability to crossover 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.

Speaker #2: 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.

James Mitchell: 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 H2 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 prioritized recommendations.

Speaker #2: 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.

Speaker #2: 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.

James Mitchell: 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 prioritized recommendations.

Speaker #2: To better support merchants selling branded products, we introduced incentives including preferential take rates for brands, product subsidies, and prioritized recommendations. Branded merchants' GMV more than tripled year on year in the first quarter, particularly in key categories such as FMCG and beauty.

James Mitchell: Branded merchants GMV more than tripled year-on-year in Q1, 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. For content creators, we upgraded the matchmaking mechanism so creators can more efficiently outreach to relevant merchants or to promote the merchant's products in the creator's 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' interests to recommend more personalized and relevant content.

Speaker #2: 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 in order to promote the merchant's products in the creator's video accounts and official accounts.

Speaker #2: On the AI front, we've enabled Weichen 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.

James Mitchell: 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' interests to recommend more personalized and relevant content.

Speaker #2: We scaled up the number of parameters and enhanced the algorithm for video accounts content recommendation model enabling deeper understanding of users' interests to recommend more personalized and relevant content.

Speaker #2: 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 plugins, including CodeBuddy, to create and debug Mini Programs.

James Mitchell: 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 plugins, including CodeBuddy, to create and debug Mini Programs, and over time, would enable Mini Program code to evolve into skills for AI agent use 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 Q1, Honor of Kings achieved lifetime high quarterly gross receipts, benefiting from top-tier outfits inspired by Chinese ink paintings 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.

Speaker #2: And over time, we'll enable mini program code to evolve into skills for AI agent use within Weichen. Total query volume on Weichen Search increased over 25% year on year, benefiting from foundation model-powered ranking and broadening AI search coverage to include image-based queries.

James Mitchell: 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 Q1, Honor of Kings achieved lifetime high quarterly gross receipts, benefiting from top-tier outfits inspired by Chinese ink paintings 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.

Speaker #2: 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 ink paintings and ancient Silk Road culture.

Speaker #2: 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 and new class-based extraction mode and IP collaborations with partners such as Ferrari contributed to the growth in users and gross receipts.

James Mitchell: 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. During Q1, we released distinctive weapon items such as Ignite Capsule, which contributed to strong gross receipts. VALORANT MOBILE has consistently ranked among top 10 mobile games industry-wide since its launch in August last year. Roco Kingdom: World, a creature collecting open world game, released on 26 March.

Speaker #2: 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.

Speaker #2: 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.

James Mitchell: During Q1, we released distinctive weapon items such as Ignite Capsule, which contributed to strong gross receipts. VALORANT MOBILE has consistently ranked among top 10 mobile games industry-wide since its launch in August last year. Roco Kingdom: World, a creature collecting open world game, released on 26 March.

Speaker #2: Roco Kingdom World, a creature collecting open world game, released on March the 26th. In its first month since launch, the game has achieved over 13 million average DAUs and is sustaining high user retention rates.

James Mitchell: 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 Q1, benefiting from Eastern mythology-themed outfits, brand collaborations, and anniversary events.

Speaker #2: 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.

Speaker #2: 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.

James Mitchell: 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 Q1, benefiting from Eastern mythology-themed outfits, brand collaborations, and anniversary events.

Speaker #2: Among our international games, PUBG Mobile's gross receipts grew year on year in the first quarter benefiting from Eastern Mythology themed outfits, brand collaborations, and anniversary events.

Speaker #2: For League of Legends, riots conducted a substantial revamp of the team processes and technology in the last two to three years, which are now collectively resulting in a faster velocity of big new content releases including the popular ARAM Mayhem constant teamfight mode, a well-received new season in Fordamachia, and the revenant reign exalted tier outfit for the Champion Viego.

James Mitchell: For League of Legends, Riot's conducted a substantial revamp of the team processes and technology in the last two to three 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 Revenant Reign Exalted 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 game's gross receipts growth during the period. After a consolidation period, Brawl Stars' DAU and gross receipts grew rapidly year-on-year, benefiting from new abilities called Buffies, an upgraded broadcast, and an improved trophy system.

Speaker #2: 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 game's gross receipts growth during the period.

James Mitchell: 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 game's gross receipts growth during the period. After a consolidation period, Brawl Stars' DAU and gross receipts grew rapidly year-on-year, benefiting from new abilities called Buffies, an upgraded broadcast, and an improved trophy system.

Speaker #2: And after a consolidation period, Brawl Stars’ DAU and gross receipts grew rapidly year-on-year, benefiting from new abilities called Buffys, an upgraded Brawl Pass, and an improved trophy system.

Speaker #2: For marketing services, revenue grew 20% year on year to $38 billion renminbi with notable growth from internet services, e-commerce, and games categories. 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.

James Mitchell: For marketing services, revenue grew 20% year-on-year to CNY 38 billion, with notable growth from internet services, e-commerce, and games categories. Revenue growth improved from 17% year-on-year in Q4 as we deepen 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 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.

Speaker #2: 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.

James Mitchell: 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 intent while balancing model complexity with system efficiency.

Speaker #2: This upgrade provides deeper understanding of user context and intent while balancing model complexity with system efficiency. By inventory, video accounts add impressions grew rapidly year on year supported by increased total time spent video views and ad load.

James Mitchell: 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.

Speaker #2: We released more inventory of rewarded ads, which deliver high click-throughs for advertisers. Mini game and mini drama studios increased their marketing spending within mini programs, specifically for mini games with introduced an instant play advertising format.

James Mitchell: 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. For 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 CNY 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 Q4 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.

Speaker #2: Enabling users to play the game within the ad without needing a redirection, which reduces friction in the new user acquisition process. And for our mobile ad network, we've made more rewarded or incentivized ad formats available to third-party app developers.

Speaker #2: 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.

James Mitchell: Looking at Fintech and Business Services, segment revenue was CNY 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 Q4 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.

Speaker #2: Fintech services revenue growth is primarily driven by commercial payment volume and 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.

Speaker #2: 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.

James Mitchell: For wealth management, average assets per user and number of users each increased year-on-year. Turning to Business Services, revenue in Q1 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 demands contribute 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 control 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. Now I'll pass to John.

Speaker #2: 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.

James Mitchell: For Tencent Cloud, AI-related demands contribute 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 control 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. Now I'll pass to John.

Speaker #2: We upgraded Tencent Cloud's AI agent solutions with proprietary security infrastructure, skill hubs, and control interfaces, contributing to rapidly increasing usage and initial token monetization.

Speaker #2: 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.

Speaker #2: And now I'll pass to John.

Speaker #1: Thank you, James. For quarter one 2026, total revenue was $196.5 billion renminbi, up 9% year on year. Gross profit was $111.3 billion renminbi, up 11% year on year.

John Lo: Thank you, James. For Q1 2026, total revenue was CNY 196.5 billion, up 9% year-on-year. Gross profit was CNY 111.3 billion, up 11% year-on-year. Operating profit was CNY 67.4 billion, up 17% year-on-year. Interest income was CNY 4 billion, up 7% year-on-year, mainly driven by growth in cash reserves. Finance costs were CNY 3 billion compared with CNY 3.9 billion in the same quarter last year, primarily due to higher Forex gains and lower average interest rates. Share profit of associates and joint venture was CNY 3.6 billion compared with CNY 4.6 billion in the same quarter last year. On a non-IFRS basis, share profit was CNY 7.1 billion compared with CNY 7.6 billion in the same quarter last year.

Speaker #1: Operating profit was $67.4 billion renminbi, up 17% year on year. Interest income was $4 billion renminbi, up 7% year on year. Mainly driven by growth in cash reserves.

John Lo: Finance costs were CNY 3 billion compared with CNY 3.9 billion in the same quarter last year, primarily due to higher Forex gains and lower average interest rates. Share profit of associates and joint venture was CNY 3.6 billion compared with CNY 4.6 billion in the same quarter last year. On a non-IFRS basis, share profit was CNY 7.1 billion compared with CNY 7.6 billion in the same quarter last year.

Speaker #1: Finance costs were $3 billion renminbi compared with $3.9 billion renminbi in the same quarter last year. Primarily due to higher forex gains and lower average interest rates.

Speaker #1: Share profit of associates and joint venture was $3.6 billion renminbi compared with $4.6 billion renminbi in the same quarter last year. On an on-air virus basis, share profit was $7.1 billion renminbi compared with $7.6 billion renminbi in the same quarter last year.

Speaker #1: Income tax expense increased by 6% year on year to $14.5 billion renminbi. On on-air virus financial figures, operating profit was $75.6 billion renminbi, up 9% year on year.

John Lo: Income tax expense increased by 6% year-on-year to CNY 14.5 billion on non-IFRS financial figures. Operating profit was CNY 75.6 billion, up 9% year-on-year. Operating profit, excluding new AI products, was CNY 84.4 billion, up 17% year-on-year. Net profit attributable to equity holders was CNY 67.9 billion, up 11% year-on-year. Diluted EPS was CNY 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 margin 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.

Speaker #1: Operating profit excluding new AI products was $84.4 billion renminbi, up 17% year on year. Net profit attributable to equity holders was $67.9 billion renminbi, up 11% year on year.

Speaker #1: Diluted EPS was $7.364 renminbi, up 12% year on year, outpacing non-air virus net profit growth due to reduced share count after our share buybacks.

John Lo: Diluted EPS was CNY 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 margin 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.

Speaker #1: Moving on to gross margins for Q1, overall gross margin was $57%, up 1 percentage point year on year. By segment, vast gross margin was $63%, up 3 percentage points year on year.

Speaker #1: 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.

John Lo: Marketing services gross margin was 55%, down 0.5 percentage point 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 CNY 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 CNY 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 costs.

Speaker #1: 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.

Speaker #1: In Q1, operating expenses, selling and marketing expenses were ¥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.

John Lo: On Q1 operating expenses, selling and marketing expenses were CNY 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 CNY 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 costs.

Speaker #1: R&D expenses rose by 19% year on year to $22.6 billion renminbi, primarily due to our increased investment in AI, which drove high equipment depreciation and associated operating costs as well as higher sales force.

Speaker #1: GNA excluding R&D expenses decreased by 24% year on year to $11.3 billion renminbi, reflecting a high base in the prior year period, which included a one-off $4 billion renminbi share-based compensation expense related to the restructuring of an existing commercial arrangement at an overseas subsidiary.

John Lo: G&A, excluding R&D expenses, decreased by 24% year-on-year to CNY 11.3 billion, reflecting a high base in the prior year period, which included a CNY 1.4 billion share-based compensation expense related to the restructuring of an existing commercial arrangement at an overseas subsidiary. At quarter end, we had approximately 115,000 employees, up 5% year-on-year, driven by headcount additions to games and our technology platform, including AI-related headcount. 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.

Speaker #1: At quarter end, we had approximately $115,000 employees, up 5% year on year, driven by headcount additions to games and our technology platform, including AI-related headcount.

Speaker #1: And down 1% Q on Q, mainly due to lower headcount at our independently operated subsidiaries and in-house tech support subsidiaries. On Q1 on-air virus operating margin was $38.5%, stable year on year.

John Lo: 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.

Speaker #1: Non-air virus 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.

Speaker #1: Operating CAPEX was $31.2 billion renminbi, up 18% year on year. And $84% quarter on quarter. As we accelerated investment in server infrastructure. Non-operating CAPEX was $0.7 billion renminbi, free cash flow was $56.7 billion renminbi, up 20% year on year.

John Lo: Operating CapEx was RMB 31.2 billion, up 18% year-on-year and 84% quarter-on-quarter as we accelerated investment in server infrastructure. Non-operating 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.

Speaker #1: Driven by growth in games, gross receipts, and advertising billings. Highly 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 cost receipts.

John Lo: 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.

Speaker #1: And the timing of certain seasonal accounts payable settlements, partly offset by higher server infrastructure and compute spending. Net cash position was $146.9 billion renminbi, up 37% quarter on quarter.

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

Speaker #1: Or roughly $40 billion renminbi, mainly driven by free cash flow generation partly offset by share repurchase of $7.9 billion renminbi and net cash outflows of $7 billion renminbi, related to investment in other corporations.

Speaker #1: Thank you.

Speaker #2: Thank you, John. We shall now open the floor for questions. We will take the first question from Alicia Yap from Citigroup.

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

Alicia Yap: Hello, can you hear me?

Speaker #3: Hello. Can you hear me?

Alicia Yap: Hello, can you hear me?

Speaker #4: Yes.

John Lo: Yes.

Wendy Huang: Yes, we can.

Alicia Yap: Hi. Good evening, management. Thanks for taking my questions. Two questions. First, since, you know, the release of Hunyuan 3 preview, I think management also mentioned, the model has been deeply integrated to a lot of the internal core products, including the Yuanbao, ima, and WorkBuddy. Can management share some details on the performance enhancements that you have observed in these workflows since the adoption? Additionally, what is the roadmap of integrating, you know, Hunyuan 3 more broadly into WeChat workflows? Will Mini Programs enterprises be able to leverage these agentic workflows to improve their productivity and maybe future monetization?

Speaker #3: Hi. Good evening, management. 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.

Speaker #3: So including the Yuanbao, Yima, and WorkBuddy. Then can management share some details on the performance enhancements that you have observed in this workflows since the adoption?

Speaker #3: So then additionally, what is the roadmap of integrating Hunyuan 3 more broadly into WeChat workflows? Will mini programs enterprises will be able to leverage these agentic workflows to improve their productivity and maybe future monetization?

Alicia Yap: Additionally, what is the roadmap of integrating, you know, Hunyuan 3 more broadly into WeChat workflows? Will Mini Programs enterprises be able to leverage these agentic workflows to improve their productivity and maybe future monetization?

Alicia Yap: 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? What type of digital content or the web activities are likely to 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? Any thoughts or insight you could share would be helpful. Thank you.

Speaker #3: 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?

Speaker #3: 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 app formats to adapt to this potential shift in the app spending?

Alicia Yap: What type of digital content or the web activities are likely to 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? Any thoughts or insight you could share would be helpful. Thank you.

Speaker #3: So any thoughts or insight you could share would be helpful. Thank you.

Speaker #4: 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-à-vis Hunyuan 2 on the AGNT capabilities.

Martin Lau: Thank you, Alicia. In terms of Hunyuan 3, you know, 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. At the same time, it has significant improvement vis-a-vis Hunyuan 2 on agent capabilities. You know, with that, when we actually integrate Hunyuan 3 into the different products, the performance was actually, you know, quite, I would say quite encouraging. You know, the different products have all expressed and marked improvement in terms of the performance, because they actually sort of, you know, see it from the user's end.

Speaker #4: 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.

Martin Lau: You know, with that, when we actually integrate Hunyuan 3 into the different products, the performance was actually, you know, quite, I would say quite encouraging. You know, the different products have all expressed and marked improvement in terms of the performance, because they actually sort of, you know, see it from the user's end.

Speaker #4: Because they actually sort of see it from the user's end. And the total token usage is actually at least 10x compared to Hunyuan 2.

Martin Lau: The total token usage is actually at least 10x compared to Hunyuan 2. That's the clear indication that, you know, 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? You know, that's why, you know, it's well-received by the products. In terms of the integration into the Weixin workflow, I think, you know, it would be a step-by-step process. Weixin itself actually sort of, you know, has been always using some part of the products, Hunyuan 2, and they have upgraded already to Hunyuan 3.

Speaker #4: So that's a 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?

Speaker #4: So that's why it's well received by the products. In terms of the integration into the Weitian workflow, I think it will be step-by-step process.

Martin Lau: In terms of the integration into the Weixin workflow, I think, you know, it would be a step-by-step process. Weixin itself actually sort of, you know, has been always using some part of the products, Hunyuan 2, and they have upgraded already to Hunyuan 3.

Speaker #4: And Weitian itself actually sort of have been always using some part of their products, Hunyuan 2 and the upgrade already to Hunyuan 3. And in some cases, they use different models and they evaluate the different models and evaluate what's the best model to use for their users, right?

Martin Lau: In some cases, they use different models and, you know, they evaluate the different models and evaluate what's the best model to use for their users, right? You know, as Hunyuan 3 continue to be getting better and better, then they will be adopting more. In terms of Mini Programs, I would say for the enterprises, one benefit is actually that, you know, they would be, you know, using some of our Hunyuan-enabled products such as, you know, coding or such as, you know, CodeBuddy, as well as WorkBuddy, right? You know, 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.

Speaker #4: So as Hunyuan 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 Cobuddy, as well as WorkBuddy, right?

Martin Lau: In terms of Mini Programs, I would say for the enterprises, one benefit is actually that, you know, they would be, you know, using some of our Hunyuan-enabled products such as, you know, coding or such as, you know, CodeBuddy, as well as WorkBuddy, right? You know, 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.

Speaker #4: 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.

Speaker #4: 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.

Martin Lau: At the same time, in the future, when we start integrating Mini Programs as skills, right, you know, to allow agents to, you know, have the ability to use Mini Programs as tools, then that would actually sort of add more traffic to these Mini Program enterprises. One is internal, right? You know, when they use our own agentic 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.

Speaker #4: So one is internal, right? When they use our own AGNT 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.

James Mitchell: Hi, 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, you know, when users spend time on e-commerce, it's because they're trying to find the lowest price. It's not because they, you know, necessarily enjoy that process.

Speaker #5: Hi, Alicia. And another 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.

Speaker #5: 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.

Speaker #5: 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.

James Mitchell: 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 are therefore not influenced by ads the way that human beings with a finite attention span are influenced. You know, all of that said, there's been many, you know, prior iterations of price comparison services, including search engines. The big e-commerce companies have generally thrived despite the existence of those price comparison services. I think it's, you know, 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.

Speaker #5: 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.

Speaker #5: 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.

Speaker #5: And the big e-commerce companies have 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.

Speaker #5: But we don't see it as a primary risk for Tencent. Thank you.

James Mitchell: We don't see it as a primary risk for Tencent. Thank you.

Speaker #3: Thank you. We will take the next question from Tennis Ball from UBS.

Wendy Huang: Thank you. We will take the next question from Kenneth Fong from UBS.

Speaker #6: Hi. Good evening, management. Thanks for taking my question. I have a question on the ROI on AI investment. If we look at the global PS, they have been allocating 80 to even 100% of their operating cash flow to AI CapEx.

Kenneth Fong: Hi. Good evening, management. Thanks for taking my question. 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. However, many of them have experienced decline in free cash flow ROE as their business become more asset heavy. Could management share or provide more quantifiable guidance on the AI-related CapEx for this year? What KPIs are being used to assess the value creation and return on this investment? Thank you.

Speaker #6: 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 their business becomes more asset-heavy.

Kenneth Fong: However, many of them have experienced decline in free cash flow ROE as their business become more asset heavy. Could management share or provide more quantifiable guidance on the AI-related CapEx for this year? What KPIs are being used to assess the value creation and return on this investment? Thank you.

Speaker #6: So could management share or provide more quantifiable guidance on the AI-rated CapEx for this year? And what KPIs are being used to assess the value creation and return on this investment?

Speaker #6: Thank you.

Speaker #5: Hi, 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.

James Mitchell: Hi, Kenneth. You know, we are seeing increased demand both, you know, from internal products as well as from, you know, external users of our model for our AI-related services. You know, we had previously guided that we will be increasing CapEx this year versus last year. You know, we are now more affirmative, more confident in that guidance. You know, we and you should expect a substantial increase in CapEx, especially in H2 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. You know, at a high level for our existing activities, such as advertising and games, the KPIs would be more revenue and profit related.

Speaker #5: 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.

Speaker #5: 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.

James Mitchell: You know, we and you should expect a substantial increase in CapEx, especially in H2 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. You know, at a high level for our existing activities, such as advertising and games, the KPIs would be more revenue and profit related.

Speaker #5: On the KPIs that 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.

James Mitchell: For our new AI products, the KPIs would be more, you know, capabilities, how intelligent is our foundation model and usage, you know, how much token consumption is happening on the WorkBuddy related. For Tencent Cloud, you know, until now, we actually haven't had sufficient GPUs to begin to service the external demand. The KPIs will be more, you know, revenue and market share related. Thank you.

Speaker #5: 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.

Speaker #5: 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.

Speaker #5: Thank you.

Speaker #6: Thank you.

Kenneth Fong: Thank you.

Speaker #3: Thank you, Kenneth. We will take the next question from Alex Yeo from JP Morgan.

Wendy Huang: Thank you, Kenneth. We will take the next question from Alex Yao from J.P. Morgan.

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

Speaker #4: Thank you, management, for taking my question. I'd like to follow up with the Kenneth's question. Just from slightly different perspective, when you allocate the financial resource to CapEx, an AI investment, how do you evaluate the AI infrastructure spent internally?

Speaker #4: What is the period you are underwriting this investment against? And over what time horizon? Thank you.

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

Speaker #5: 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 strictly financial approach.

Speaker #5: 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 question because I may not have caught the full meaning behind the question.

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

Speaker #4: Thank you, James. I mean, ultimately, the investment community needs to understand who pays these AI CapEx from what budget and over what time period or horizon do we expect to tap into those new commercial opportunities?

Speaker #5: Well, 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.

James Mitchell: Well, I think that, you know, 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, you know, been a consistently high return on equity. You know, we have not got there by limiting each new product, each new service, to, you know, very, near term quantitative, you know, 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, you know, any specific quarter or a twelve-month period.

Speaker #5: 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 lifecycle.

James Mitchell: You know, we have not got there by limiting each new product, each new service, to, you know, very, near term quantitative, you know, 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, you know, any specific quarter or a twelve-month period.

Speaker #5: 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 Wei Xin up, movement into payments, that either went through lengthy incubation periods where they had no return on investment, but we were confident in the franchise value creation.

James Mitchell: You know, there's been many products within Tencent, you know, whether it's, you know, our expansion into games, the launch of Weixin, our movement into payments, that either went through lengthy incubation periods where they had no return on investment, but we were confident in the franchise value creation. Over time, they had more lengthy, you know, harvesting periods where we've been able to drive, you know, very healthy returns on that, you know, sunk investment. You know, AI includes a range of sort of shorter cycle investments as well as longer cycle investments. If we buy GPUs and we deploy them into our ad tech, you know, then that's a relatively short cycle investment.

Speaker #5: And then over time, they had more lengthy harvesting periods where we've been able to drive in a very healthy returns on that sunk investment.

James Mitchell: Over time, they had more lengthy, you know, harvesting periods where we've been able to drive, you know, very healthy returns on that, you know, sunk investment. You know, AI includes a range of sort of shorter cycle investments as well as longer cycle investments. If we buy GPUs and we deploy them into our ad tech, you know, then that's a relatively short cycle investment.

Speaker #5: 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.

James Mitchell: 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, you know, that's something which we view as important for our franchise and, you know, where we're taking a longer term view. Again, you know, 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.

Speaker #5: 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 Honeywell Foundation model, that's something which we view as important for our franchise.

Speaker #5: 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 lifecycle basis.

Speaker #4: I think just to elaborate on what James is saying, there's sort of a range of different ways to look at this. And if you look at the model training, it's basically an investment for the future.

Martin Lau: I think just to elaborate on what James is saying, right? You know, there's sort of, you know, a range of different ways to look at this, right? You know, If you look at the model training, it's basically an investment for the future, right? There's probably not gonna be very immediate return. Over time, the capability accumulates, and it actually sort of, you know, helps unlock a lot of different businesses opportunities. When you look at the products that we are launching, right? You know, be it Yuanbao, WorkBuddy, CodeBuddy, right? You know, there's process in which, you know, you have free services, right? Over time, you know, you may have revenue.

Speaker #4: And there's probably not going to be very immediate return. But over time, the capability accumulates. And it actually sort of helps unlock a lot of different businesses opportunities.

Martin Lau: Over time, the capability accumulates, and it actually sort of, you know, helps unlock a lot of different businesses opportunities. When you look at the products that we are launching, right? You know, be it Yuanbao, WorkBuddy, CodeBuddy, right? You know, there's process in which, you know, you have free services, right? Over time, you know, you may have revenue.

Speaker #4: And then when you look at the products that we are launching, be it Yanbao, WorkBuddy, Cobuddy, there's process in which you have free services and then over time, you may have revenue that the business-oriented revenue can come faster than the consumer-oriented revenues.

Martin Lau: The business-oriented revenue can come faster than the consumer-oriented revenues. There will be sort of, you know, a return cycle on that. If you look at the business revenue sort of or the cloud revenue in the sense of a mass or rental of compute, then there's a clear ROI, right? You know, you have a depreciation cost and you usually put on some kind of margin, and then so you rent it out. That would be sort of, you know, having a clearer return. When we have advertising, as James pointed out, right, you know, we usually see very good return from those investments. I think, you know, you know, for different computes, there's different ways to look at it.

Speaker #4: 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 a mass or rental of compute, then there's a clear ROI.

Speaker #4: You have a depreciation cost. And you usually put on some kind of margin. And then sort of you rent it out. So that would be sort of having a clearer return and then when we have advertising as James pointed out, we usually see very good return.

Martin Lau: That would be sort of, you know, having a clearer return. When we have advertising, as James pointed out, right, you know, we usually see very good return from those investments. I think, you know, you know, for different computes, there's different ways to look at it.

Speaker #4: From those investments. So I think for different computes, there's different ways to look at it.

Speaker #3: Thank you, Alex. We will take the next question from William Packer from BNP Paribas. William, your line is open.

Wendy Huang: Thank you, Alex. We will take the next question from William Packer from BNP Paribas. William, your line is open.

William Packer: Hi management. Thanks for taking my questions. 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 via faster content creation cycles, or is that a delayed benefit? Are you seeing cost efficiencies benefits hit the margins today, or do you need to invest the initial phase limiting any benefit? As a quick follow-up, thanks for the commentary on the CapEx outlook. Could you talk through any implications for the share buyback in the H2 of the year? Thanks very much.

Speaker #6: Hi, management. Many thanks for taking my questions. 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?

Speaker #6: Is it driving incremental monetization via faster content creation cycles? Or is that a delayed benefit? And are you seeing cost efficiencies benefit the margins today?

William Packer: Are you seeing cost efficiencies benefits hit the margins today, or do you need to invest the initial phase limiting any benefit? As a quick follow-up, thanks for the commentary on the CapEx outlook. Could you talk through any implications for the share buyback in the H2 of the year? Thanks very much.

Speaker #6: Or do you need to invest the initial phase limiting any benefit? And as a quick follow-up, thanks for the commentary on the CapEx outlook.

Speaker #6: Could you talk through any implications for the share buyback in the second half of the year? Thanks very much.

Speaker #5: Yeah, so I don't know. I addressed those. As you hypothesized for the game business, generative AI enables us to produce more content faster, and that content is in some cases to enhance the overall player experience.

James Mitchell: Yeah. Why don't I address those? You know, as you hypothesized, for our game business, generative AI enables us to produce more content faster. You know, 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. You know, that's what we are doing and that's what we're seeing. We think that we're a, you know, a China leader and to some extent even more so a global leader in terms of, you know, deploying that capability and achieving that benefit. You know, the objective at this point is really, you know, faster content creation and incremental revenue generation. We're not prioritizing margin expansion per se.

Speaker #5: 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.

Speaker #5: And that's what we're 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.

James Mitchell: We think that we're a, you know, a China leader and to some extent even more so a global leader in terms of, you know, deploying that capability and achieving that benefit. You know, the objective at this point is really, you know, faster content creation and incremental revenue generation. We're not prioritizing margin expansion per se.

Speaker #5: 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.

James Mitchell: It's more that, you know, as we deliver the revenue uplift that we're seeing, and if we can, you know, keep headcount fairly stable, then, you know, I suppose mathematically that combination would tend to result in higher margins over time. That's, you know, sort of a happy output rather than the intention of the process. In terms of your question about capital returns, you know, we will be stepping up our investments in AI in response to the increased demands that we're seeing. However, we do have, you know, a very cash generative business, as you can see from the Q1 results. We also have a very substantial investment portfolio, and we're accelerating the process of liquidizing some of that investment portfolio.

Speaker #5: 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 demands that we're seeing.

James Mitchell: In terms of your question about capital returns, you know, we will be stepping up our investments in AI in response to the increased demands that we're seeing. However, we do have, you know, a very cash generative business, as you can see from the Q1 results. We also have a very substantial investment portfolio, and we're accelerating the process of liquidizing some of that investment portfolio.

Speaker #5: 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.

Speaker #5: 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.

James Mitchell: That would enable us to sustain buybacks going through the rest of this year. You know, at this point in time, we believe our share price is somewhat dislocated and, you know, therefore, it's an opportune time for buybacks, a particularly opportune time for buybacks. Thank you.

Speaker #5: And at this point in time, we believe our share price is somewhat dislocated. And therefore, it's an opportune time for buybacks, particularly opportune time for buybacks.

Speaker #5: Thank you.

Speaker #4: Thanks for the comment.

William Packer: Thanks for the color.

Speaker #3: Thank you. Next question comes from the Robin from the Bernstein.

Wendy Huang: Thank you. Next question comes from the Robin from the Bernstein.

Speaker #6: Thanks. Thanks, management. Thanks for taking my question. If I could have a couple of questions. So one, in terms of the changes that we've made to our data pipeline and training RL infer and so on, do you feel now that having seen the release of Honeywell 3, we're now on a more sustainable upward trajectory where we can deliver major updates, say, one major update a year, several smaller ones in between, like some of the other labs?

Robin Zhu: Thanks. Thanks, management. Thanks for taking my question. If I could have a couple questions. One, in terms of the changes that we've made to our data pipeline and training RL Infer and so on, do you feel now that, you know, having seen the release of Hunyuan 3, we're now on a more sustainable upward trajectory where, you know, we can deliver major updates, say, you know, 1 major update a year, several smaller ones in between, like some of the other labs, are we there or, you know, is that still more of a work in progress?

Speaker #6: 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 US 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.

Robin Zhu: Second, just on the kind of philosophy of some of the AI product investments, I think one of the tensions in the US has been, you know, I think OpenAI has been the big DAU player, whereas Anthropic has kind of gone after a small pool of high intent power users, you know, highly willing payers effectively. Just, you know, curious on I mean, at 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, you know, to what extent does the current kind of token maxing phenomenon play into that pool? Thank you.

Robin Zhu: Just, you know, curious on I mean, at 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, you know, to what extent does the current kind of token maxing phenomenon play into that pool? Thank you.

Speaker #6: 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 token maxing phenomenon play into that thought?

Speaker #6: Thank you.

Speaker #4: Yeah. 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.

Martin Lau: Yeah. In terms of the production timeline, I think, you know, 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, you know, the pre-training, the post-training, the RL, as well as the eval. You know, and we have deliberately actually built a smaller model to basically validate all these different points, right? You know, and the combination of this, right, when it's all integrated into Hy3 preview, is that it produces a pretty competent model at its size.

Speaker #4: And if you look at Honeywell 3, we have revamped the entire team, the production process, the infra, and all the different major modules in producing great models.

Martin Lau: Including the data pipeline, as you point out, you know, the pre-training, the post-training, the RL, as well as the eval. You know, and we have deliberately actually built a smaller model to basically validate all these different points, right? You know, and the combination of this, right, when it's all integrated into Hy3 preview, is that it produces a pretty competent model at its size.

Speaker #4: Including the data pipeline, as you point out, the pre-training, the post-training, the RL as well as eval. So and we have deliberately actually built smaller models to basically validate all these different points, right?

Speaker #4: And the combination of this, right, when it's all integrated into Honeywell 3 preview, is that it produces pretty competent models at its size. And we clearly see in each one of these modules, there's a lot of work that we could be doing.

Martin Lau: We clearly see in each one of these modules, there's a lot of work that we could be doing. I think, you know, we're happy with the results. To some extent, you know, we are actually surprised by the speed at which it's done and the fact that it's actually proved to be useful, right? You know, for a long time, I think, you know, a lot of models would actually come up pretty high in terms of the benchmarks. When it's actually rolled out to different products, people complain. When you put the model to the developers and the user, right, you know, people won't use it, right? I think, you know, if you look at how this is received in the actual use cases, it's actually.

Speaker #4: So I think we're happy with the result. To some extent, we're actually surprised by the speed at which it's done. And the fact that it's actually proved to be useful, right?

Speaker #4: 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.

Martin Lau: When it's actually rolled out to different products, people complain. When you put the model to the developers and the user, right, you know, people won't use it, right? I think, you know, if you look at how this is received in the actual use cases, it's actually.

Speaker #4: And when you put the model to the developers and the user, right, people won't 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.

Martin Lau: You know, better than our expectation by quite a bit.

Speaker #4: 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?

Martin Lau: So with that, I think, you know, it builds a very solid foundation for us to scale the model to the next level. In terms of how we think about the different products, we felt this is actually sort of, you know, a very early stage in terms of AI diffusion, right? You know, we would see many different products coming up going forward. Initially, it was chatbot, and everybody felt, you know, chatbot is actually the, you know, king of the product, you know? Suddenly you have a coding that come up and this becomes sort of even a more, you know, eye-catching and a significant use case because it's very high value, right?

Speaker #4: 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.

Martin Lau: You know, we would see many different products coming up going forward. Initially, it was chatbot, and everybody felt, you know, chatbot is actually the, you know, king of the product, you know? Suddenly you have a coding that come up and this becomes sort of even a more, you know, eye-catching and a significant use case because it's very high value, right?

Speaker #4: And then, suddenly, you have a coding that came up. And this becomes sort of even a more eye-catching and significant use case, because it's very high value, right?

Speaker #4: And now we're seeing sort of AGNtic 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?

Martin Lau: You know, now we're seeing sort of agentic capability proliferating, right. You know, I think, you know, that would actually allow AI to be diffused to different industries. You have many different agents coming up which can help you to do work, right. You know, there's gonna be new products coming up. I think that would continue to propagate.

Speaker #4: 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 the high-value use case as opposed to sort of just purely focus on DAU because the difference between the AI revolution and internet is that this is about intelligence.

Martin Lau: You know, I think to some extent, right, you know, in the AI world, you actually have to find the high value use case, you know, as opposed to, you know, just purely focus on DAU because.

Martin Lau: The difference between the AI revolution and internet is that, you know, this is about intelligence. Intelligence is what manifests its, you know, value in sort of, you know, how, how much people are willing to pay for it. At the same time, the intelligence is not free, right? You know, in the internet world, you basically sort of, you know, have mostly, you know, existing information. You know, you also create some new information and content, but then, you know, that's a fixed cost. Sort of the variable cost for delivering is actually very small, right? You only have to pay for bandwidth.

Speaker #4: And intelligence is the manifest it's value in sort of how much people are willing to pay for it. And at the same time, the intelligence is not free, right?

Speaker #4: 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.

Speaker #4: 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?

Martin Lau: The compute sits on people's devices, right? You know, as a result, you know, you can almost like go for infinite scaling.

Speaker #4: And as a result, you can almost go for infinite scaling. But in this case, right, every single delivery of a DAU actually costs you quite a bit, right?

Martin Lau: In this case, right, you know, every single delivery of a DAU actually costs you quite a bit.

Speaker #4: And as a result, right, 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.

Martin Lau: As a result, right, you can't just apply the same logic as, you know, internet and apply it to AI.

Martin Lau: I would say the ability to find high value use cases is gonna be as important, if not more important, than just sort of blindly get a lot of DAU and user time. I think, you know, that is one important distinction. We, you know, as we think about how to deploy our product, you know, and how to co-design our product with the models, these are the kind of new considerations that we have to put into play.

Speaker #4: So I think that is one important distinction. And as we think about how to deploy our product and how to co-design our product with the models that these are the kind of new considerations that we have to put into play.

Speaker #5: Thank you.

Wendy Huang: Thank you. Thank you. Thank you. We will move to the next one, Alex Xu from Bank of America.

Speaker #6: Thank you. Thank you. We will move to the next one. Alex Liu from Bank of America.

Alex Xu: Thanks, management for taking my questions. I have 2 questions. Appreciate the sharing on the agentic AI strategy. I'm especially, you know, interested in the concept that, you know, 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 timeline we should expect for this to materialize? A follow-up would be related to the last questions. You know, 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 Weixin Agent against the current pretty tight compute capacity on hand? Thank you.

Speaker #7: Oh, thanks. Management for taking my questions. So I have two questions. So appreciate the sharing on the agentic AI strategy. I'm especially interested in the concept that Tencent's AI agents could access the mini-program ecosystem and use mini-program code as an AI skills.

Alex Liu: Thanks, management for taking my questions. I have 2 questions. Appreciate the sharing on the agentic AI strategy. I'm especially, you know, interested in the concept that, you know, 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 timeline we should expect for this to materialize?

Speaker #7: Just wondering on that, is there any timeline we should expect for this to materialize? A follow-up would be related to the last questions. 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?

Alex Liu: A follow-up would be related to the last questions. You know, 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 Weixin Agent against the current pretty tight compute capacity on hand? Thank you.

Speaker #7: Against the current pretty tight compute capacity on hand. Thank you.

Speaker #4: 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.

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

Speaker #4: So, there's—we have a timeline. We're not going to be able to share with you a definitive answer because there's a lot of design that needs to come into place, right?

Martin Lau: You know, there's You know, we have a timeline. We, we're not, you know, gonna be able to share with you with a definitive answer because, you know, there's a lot of design that needs to come into place, right? You know, at some point in time, I think, you know, it's a concept that our ecosystem can actually help each other out, and this is one unique advantage that we have.

Speaker #4: 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.

Speaker #4: 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?

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

Speaker #4: So I think that's unique advantage that we have. And we'll be providing that over time.

Speaker #8: 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.

James Mitchell: On your question about balancing between the various, you know, 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, you know, Tencent Cloud. I think most, you know, big tech hyperscale companies with cloud businesses have one, you know, flagship internal use case where they're allocating a large number of GPUs. We have, you know, multiple flagships. We have the Hunyuan foundation model. We have agentic developments within Weixin. We have, you know, the Yuanbao support. We have the AI deployment for advertising, for games, you know, now also for the WorkBuddy and CodeBuddy use cases.

Speaker #8: 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.

Speaker #8: We have multiple flagships. We have the Hunyuan Foundation model. We have agentic developments within Weishin. We have the Yunbao support. We have the AI deployment for advertising, for games, now also for the work body and code body use cases.

James Mitchell: We have, you know, multiple flagships. We have the Hunyuan foundation model. We have agentic developments within Weixin. We have, you know, the Yuanbao support. We have the AI deployment for advertising, for games, you know, now also for the WorkBuddy and CodeBuddy use cases.

Speaker #8: And the reason why we've been able to support all of these at once is because we have not been active in leasing out GPU capacity in Tencent Cloud.

James Mitchell: The reason why we've been able to support all of these at once is because we have not been active in leasing out GPU capacity in Tencent Cloud. 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. You know, that's where the trade-off has been made, that we have been, you know, consciously late to monetize AI opportunity through Tencent Cloud because we've been simultaneously supporting a number of AI initiatives internally. Thank you.

Speaker #8: Now, looking through the rest of this year, as these supply of China-designed 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.

Speaker #8: 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.

James Mitchell: You know, that's where the trade-off has been made, that we have been, you know, consciously late to monetize AI opportunity through Tencent Cloud because we've been simultaneously supporting a number of AI initiatives internally. Thank you.

Speaker #8: Thank you.

Speaker #6: Thank you. We will take the next question from Xiaoling Liu from HSBC.

Wendy Huang: Thank you. We will take the next question from Charlene Liu from HSBC.

Speaker #9: Thanks, Wendy. And thank you. For the opportunity. I have two questions. First is, on monetization, we're seeing Doubao starting to explore subscription models for their 2C users.

Charlene Liu: Thanks, Wendy, and thank you for the opportunity. I have two questions. First is on monetization. We're seeing Doubao starting to explore subscription models for their To C users. I would like to understand how big the management thinks that the To C subscription market looks like in China. I guess subscription aside, are ads and Mini Programs or Shop key monetization avenue for To C AI or there are more, and how much upside do you expect from ad and Mini Programs? That's the first question. The second question is on compute power bottleneck. The US players obviously have sort of moved on to working on resolving bottleneck issues or shortages in CPU and networking chips beyond GPU.

Speaker #9: I would like to understand how big the measurement things that the 2C subscription market looks like in China. And I guess subscription aside, are ads and mini-programs a shop key monetization avenue for 2C AI or there are more?

Charlene Liu: I guess subscription aside, are ads and Mini Programs or Shop key monetization avenue for To C AI or there are more, and how much upside do you expect from ad and Mini Programs? That's the first question. The second question is on compute power bottleneck. The US players obviously have sort of moved on to working on resolving bottleneck issues or shortages in CPU and networking chips beyond GPU.

Speaker #9: And how much upside do you expect from ad and mini-programs that's the first question. The second question is, on compute power bottleneck, the US plays obviously have sort of moved on to working on resolving bottleneck issues or shortages in CPU and networking chips beyond GPU.

Speaker #9: And has this issue begun to surface? Do we anticipate it too? And what are the measurement plans to resolve them? Thank you so much.

Charlene Liu: Has these issues begin to surface? Do we anticipate it to? What are the management's plans to resolve them? Thank you so much.

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

Speaker #4: In terms of the 2C monetization, I would say it's actually not easy, right? If you look at global standards, in the Western market, when the paid service is actually very well penetrated and the living standard is actually very high, the subscription price in the Western market is multiple times what an equivalent service in China is—be it music service or be it video service.

Martin Lau: You know, the subscription price in the Western market is multiple times of what the equivalent service in China is like, you know, be it music service or be it, you know, video service, that the paying penetration is probably, you know, in the single digit, right? When you sort of applied it to China, I think the subscription model is not gonna be that big for the China market.

Speaker #4: The paying penetration is probably in the single digit, right? And when you sort of apply it to China, I think the subscription model is not going to be that big for the China market.

James Mitchell: You know, you use that as a standard, sort of, you know, start to read across for China, then it will not be that much. At the same time, it's necessary, right? For the reason that I talked about earlier, it's not like internet service 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. 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 gonna be a winner-take-all business.

Speaker #4: 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?

Speaker #4: Every single user actually sort of costs 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.

Speaker #4: 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.

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

Speaker #4: 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 US players where the ECPM is actually much higher, right?

James Mitchell: You know, for even the US players where the eCPM is actually much higher, right? You know, the, you know, the leading player has not been able to roll out very robust advertising model. You know, so I think, you know, it will be for the longer term, and it will be supplements to probably a subscription model.

Speaker #4: The leading player has not been able to roll out very robust advertising model. And so I think it would be for the longer term and it would be supplements to probably a subscription model.

Speaker #4: 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 are 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.

James Mitchell: I think that's why I said, you know, in the world of AI, you know, 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.

Martin Lau: That you have the best return on your limited compute in order to achieve the best result.

Speaker #5: 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-designed GPUs being brought into China.

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

James Mitchell: Then the China design GPUs, you know, facing limited fab capacity within China. You know, as a result, the country has really been, you know, short of GPU or ASIC capacity. You know, that's now being addressed because the China designed ASICs are seeing, you know, more supply from fabs within China, as well as more supply from fabs in neighboring countries.

Speaker #5: And then the China-designed GPUs, facing limited fab capacity within China. And as a result, the country has really been short of GPU or ASIC capacity.

Speaker #5: 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.

James Mitchell: you know, by contrast, we haven't faced those sort of artificial additional constraints on CPU or networking chips. you know, we've been a big buyer of, you know, CPU and networking chips for many years before, you know, 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. you know, on their side, while one might think that these suppliers would be, you know, sitting back and just, you know, selling at the highest possible price into the spot market, you know, that's not actually the reality. The smart suppliers are taking very conscious, you know, 3 to 5-year forward views and, you know, negotiating long-term agreements in order to give them certainty of, you know, their revenue outlook over the next 3 to 5 years.

Speaker #5: But by contrast, we haven't faced those sort of artificial additional constraints on 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.

Speaker #5: 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.

Speaker #5: The smart suppliers are taking very conscious three to five-year forward views and negotiating long-term agreements in order to give them certainty of their revenue outlook over the next three to five years.

James Mitchell: The smart suppliers are taking very conscious, you know, 3 to 5-year forward views and, you know, negotiating long-term agreements in order to give them certainty of, you know, their revenue outlook over the next 3 to 5 years.

Speaker #5: 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.

James Mitchell: When they're deciding with whom to sign those long-term agreements, you know, they're looking to work with a number of partners, not just a single partner. They're looking to work with partners who, you know, have been there for many years already and will be there for many years to come. Ideally, with partners whose demand they believe will grow substantially over time. Happily, we fulfill all of those criteria. You know, we've been, you know, a big customer for, you know, the Intel and AMD and so forth for many years. We've been progressively growing our volume with them for many years. They believe we will continue to progressively grow our volume for many years to come.

Speaker #5: 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.

Speaker #5: And happily, we fulfill all of those criteria. We've been a big customer for Intel and AMD and so forth for many years. We've been progressively growing.

James Mitchell: Happily, we fulfill all of those criteria. You know, we've been, you know, a big customer for, you know, the Intel and AMD and so forth for many years. We've been progressively growing our volume with them for many years. They believe we will continue to progressively grow our volume for many years to come.

Speaker #5: Our volume with them for many years. And they believe that we'll 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.

James Mitchell: You know, on the procurement side, I'd say that the challenges are more around, you know, GPU and those challenges are now being addressed. We've been able to secure a good supply of CPU and networking chips. Thank you.

Speaker #5: And then we've been able to secure a good supply of CPU and networking chips. Thank you.

Speaker #1: Thank you. We will take the next question from Ronald Kwon from Goldman Sachs.

Wendy Huang: Thank you. We will take the next question from Ronald Keung from Goldman Sachs.

Speaker #6: Thank you, Pony Martin James John and Wendy. So two questions. One is on the consumer AI agent side. So compared with a potential kind of Asian agent that we've been talking about, which is at the app level, knowing that Asian is super app, but how does management view long-term potentials or potential disruptions from operating system-level agents?

Ronald Keung: Thank you, Pony Ma, Martin Lau, James Mitchell, John, and Wendy Huang. Two questions. One is on the consumer AI agent side. Compared with a potential kind of Weixin Agent that we've been talking about, which is at the app level, knowing that Weixin is 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, these built by phone makers? How would we see that potential or disruption or threat? On second, on advertising, we've seen a very good re-acceleration, noting that we are very patient on ad load versus peers, but with a slight kinda edge up of ad load in the first quarter.

Speaker #6: Noting agents from iOS or Android or mobile phone, these both by phone makers. How would we see that potential or disruption or threat? And then on second, on advertising, we've seen a very good re-acceleration.

Ronald Keung: How would we see that potential or disruption or threat? On second, on advertising, we've seen a very good re-acceleration, noting that we are very patient on ad load versus peers, but with a slight kinda edge up of ad load in the first quarter.

Speaker #6: Noting that we are very patient on ad load versus peers. But with a slight kind of edge-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?

Ronald Keung: I'm just thinking, is there any room for any thinking or change to have a potential further revenue acceleration for ads? Reason I would say thinking bigger advertising profits could drive more reinvestments into AI. Would love to hear your thoughts. Thank you.

Speaker #6: And reason, I would say, thinking bigger advertising profits, could drive more reinvestments into AI. So we'd love to hear your thoughts. Thank you.

Speaker #4: I think from a operating system perspective, right, you mixed in a number of different things, right? There is a real operating system which is iOS and Android, right?

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

Speaker #4: And there are and then you lob in sort of other applications which try to pretend to be operating systems. So I think if you are an 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?

Speaker #4: You actually sort of want to have that balance, right? You can have an agent which tries to provide services to your users, but then you actually need to have the permission, right, of the different applications.

Martin Lau: You know, you can have an agent which try to provide services to your users. You actually need to have the permission, right, you know, of the different applications. Otherwise, you know, as an operating system, you are essentially robbing different apps, and that's not the best way of managing an operating system. I think, you know, 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.

Speaker #4: Otherwise, as an operating system, you are essentially robbing 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.

Speaker #4: 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.

Speaker #4: But if you say, "Oh, there's another app which sort of tries to become an operating system like a service and try to sort of invade other apps," I think that's a real competition.

Martin Lau: If you say, "Oh, you know, there's another app," which sort of, you know, try to become an operating system like a service and try to sort of invade other apps, I think, you know, that's a real competition, and that's not something which, you know, any app would actually allow. I think the operating system itself, which should try to sort of, you know, stop that from happening as well. I think, you know, you, if you're talking about agents which will sort of, you know, be an app trying to compete with other app, I think, you know, that's one level of issue, right?

Speaker #4: 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.

Speaker #4: So I think if you're talking about agents which will sort of be an app trying to compete with other apps, I think that's one level of issue, right?

Martin Lau: You know, I think, you know, operating system would always try to be sort of, you know, quite impartial and try to maintain a, you know, a healthy ecosystem for everybody to be involved in order for it to be a successful ecosystem or operating system.

Speaker #4: And I think operating system would always try to be sort of quite impartial and try to maintain a healthy ecosystem for everybody to be involved in order for it to be a successful ecosystem.

Speaker #4: Or operating system.

Speaker #6: And in terms of the advertising revenue, factually, our ad load on video accounts is still the lowest in the industry at 45%. So there's clearly a substantial headroom for us to increase the ad load.

James Mitchell: In terms of the advertising revenue, you know, factually our ad load on Video Accounts is still the lowest in the industry, at 4% to 5%. There's, you know, clearly a substantial headroom for us to increase the ad load. You know, as to whether, and to what extent we'll sort of feel the need to do so, you know, we are in a position where we have multiple revenue growth drivers beyond advertising. You know, for our game business, the jump in deferred revenue in the quarter, provides us with a sort of tailwind to the reported revenue over the coming 3 quarters.

Speaker #6: 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.

Speaker #6: For our game business, the jump in deferred revenue in the quarter provides us with a sort of tailwind to the reported revenue over the coming three quarters.

Speaker #6: For our cloud business, we've talked about how bringing on stream in a more GPUs in the second half of the year should facilitate revenue growth trends.

James Mitchell: For our cloud business, we've talked about how bringing on stream, you know, more GPUs, in the H2 of the year should facilitate, you know, revenue growth trends for cloud. You know, for our fintech business, you know, for many quarters we've been struggling with a situation where volume growth was positive, but pricing was negative. Now, you know, volume growth remains positive and pricing's moved to a more neutral stance. You know, we feel with that, across our portfolio of businesses, you know, there are, you know, certain positive things playing out.

Speaker #6: 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's moved to a more neutral start.

Speaker #6: 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.

James Mitchell: you know, we'll, you know, continue to manage it as a broad portfolio, and we'll, you know, continue to manage the ad load within Video Accounts in a way that, you know, we think, is conducive to both, you know, supporting the overall growth of our business metrics, but also to supporting, you know, growth of, you know, time spent and engagement within the Video Accounts product itself.

Speaker #6: 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.

Speaker #1: Thank you. We will take the next question from Ali Jiang from Macaury.

Wendy Huang: Thank you. We will take the next question from Ally Zhang from Macquarie.

Speaker #5: Great. Thank you so much for taking my question and good evening, management. I have two questions. Number one is if you look at the work body's current traction, it does seem like we have been getting very early leadership, especially in the productivity agent space.

Ally Zhang: Great. Thank you so much for taking my question, and good evening, management. I have 2 questions. Number one is, if you look at the WorkBuddy, its current traction, it does seem like we have been gaining very early leadership, especially in the productivity agent space. 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 mass or SaaS related versus the traditional cloud revenue as well as the others? Specifically, do you have any internal ARR target, you know, for these agentic workflow products by the end of fiscal 2026 and in the next kind of 2, 3 years? Thank you.

Ellie Jiang: Great. Thank you so much for taking my question, and good evening, management. I have 2 questions. Number one is, if you look at the WorkBuddy, its current traction, it does seem like we have been gaining very early leadership, especially in the productivity agent space.

Speaker #5: 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., it'll be kind of mass or SaaS related versus the traditional cloud revenue as well as the others?

Ellie Jiang: 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 mass or SaaS related versus the traditional cloud revenue as well as the others? Specifically, do you have any internal ARR target, you know, for these agentic workflow products by the end of fiscal 2026 and in the next kind of 2, 3 years? Thank you.

Speaker #5: And specifically, do you have any internal AR target for these agentic workflow products by the end of fiscal year '26 and in the next coming two to three years?

Speaker #5: Thank you.

Speaker #2: Yeah, to Ali, 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.

James Mitchell: Ally, the upturn in, you know, sort of productivity AI is really something that's happened, you know, not in the last few quarters or even last few months, but last few weeks. I think that's true, you know, globally actually. The, you know, really it's, you know, since late in or since the end of Q1 that, you know, the agentic AI has, you know, broken through in terms of its ability to create code, in terms of its ability to, you know, make people more productive. In Q1, the business services growth was not, you know, a function of, you know, that token consumption. The token consumption has, you know, been more recent than, the end of Q1.

Speaker #2: And I think that's true globally, actually. 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.

Speaker #2: 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.

James Mitchell: In Q1, the business services growth was not, you know, a function of, you know, that token consumption. The token consumption has, you know, been more recent than, the end of Q1.

James Mitchell: In terms of, you know, ARR targets and so on, you know, by extension, this is all changing so quickly that, you know, we could set a target today and we'd be, you know, out by an order of magnitude 12 months from now in either direction because, you know, the usage demand is so dynamic. So at this point, you know, we're less focused on, you know, hitting certain dollar ARR numbers and, you know, more focused on having the right products. And, you know, the right products includes the right product at, you know, the model level where, you know, Hunyuan 3 is, you know, very good in terms of many agent capabilities. And, you know, the next iteration will be substantially better later this year.

Speaker #2: 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.

Speaker #2: So at this point, we're less focused on hitting certain and more focused on having the right products and the right products include 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.

James Mitchell: So at this point, you know, we're less focused on, you know, hitting certain dollar ARR numbers and, you know, more focused on having the right products. And, you know, the right products includes the right product at, you know, the model level where, you know, Hunyuan 3 is, you know, very good in terms of many agent capabilities. And, you know, the next iteration will be substantially better later this year.

Speaker #2: Later this year. And also at the product level in terms of code body and increasingly work body, being the right interface for users to access and extract the most intelligence from these foundation models.

James Mitchell: You know, also at the product level in terms of, you know, CodeBuddy and increasingly WorkBuddy, you know, being the right, you know, interface for users to, you know, access and extract the most intelligence from these foundation models. Right now that's our, you know, priority. Thank you.

Speaker #2: So right now, that's our priority. Thank you.

Speaker #1: Thank you. We will take the last question from Thomas Chong from Jefferies.

Wendy Huang: Thank you. We will take the last question from Thomas Chong from Jefferies.

Thomas Chong: Hi, good evening. Thanks management for taking my questions. 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 will also have expecting AI drama to be a blockbuster content in coming years? How should we think about all the content costs and the business model going forward? My second question is on 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? Thank you.

Speaker #3: Hi. Good evening. Thanks, management, for taking my questions. 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 will also have expecting AI drama to be blockbuster content in coming years?

Speaker #3: And how should we think about all the content cost and the business model going forward? And my second question is on AI on the fintech segment.

Thomas Chong: My second question is on 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? Thank you.

Speaker #3: Given the risk management is substantially enhanced with AI, how should we think about the online lending and wealth management outlook with AI? Thank you.

Speaker #2: 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.

James Mitchell: Again, you know, the landscape for AI has been so dynamic. You know, our own position has changed so much, you know, in the last few weeks, in the last few months, that it's difficult to speak very definitively. I think when you talk about, you know, AI disruption in content creation, you may be alluding to, you know, mini videos or mini drama series rather than, you know, the long-form drama series that is historically Tencent Video's strength. You know, on the long-form side, you know, what we're seeing is that there is a certain, you know, double-digit percent of the market that likes animated content.

Speaker #2: 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 Videos' strength.

Speaker #2: 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 very good best-in-class products.

James Mitchell: You know, now, as a result of the confluence of, you know, tools such as Unreal Engine and capabilities such as generative AI for video, it's becoming increasingly feasible to, you know, create the same 3D assets for games and for, you know, animated content, animated linear video content and, you know, both become very good best-in-class products within their particular categories. That's something where, you know, Tencent is a natural leader because, you know, we have our big content IP operations, we have our game business, we have our AI technology capabilities. We have, you know, particular strength in certain multi-modalities within AI.

Speaker #2: 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.

James Mitchell: That's something where, you know, Tencent is a natural leader because, you know, we have our big content IP operations, we have our game business, we have our AI technology capabilities. We have, you know, particular strength in certain multi-modalities within AI.

Speaker #2: We have our AI technology capabilities. We have particular strength in certain multi-modalities within AI. And so as Pony mentioned in the opening remarks, we've actually become 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.

James Mitchell: As Pony mentioned in the opening remarks, you know, we've actually become, you know, a very clear industry leader now in the business of, you know, producing animated TV series. AI enables us to do that, you know, faster, cheaper, you know, better. It also enables us to bring, you know, far more IP into linear video format that was previously sort of stuck in novel format or in game format, and so, you know, expand the funnel, expand the audience. That's on AI for content. Then on, you know, AI for fintech, you know, financial services represents a very big part of global GDP. It represents a very big part of our revenue.

James Mitchell: It also enables us to bring, you know, far more IP into linear video format that was previously sort of stuck in novel format or in game format, and so, you know, expand the funnel, expand the audience. That's on AI for content. Then on, you know, AI for fintech, you know, financial services represents a very big part of global GDP. It represents a very big part of our revenue.

Speaker #2: And so expand the final 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.

Speaker #2: 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.

James Mitchell: It's an industry that is inherently very data-heavy, you know, it's naturally an industry that, you know, should and will lend itself over time to uplift in productivity from AI. You know, if you think about the industries that are already being uplifted by AI, such as coding, such as, you know, advertising, then, you know, financial services is actually very logical to be uplifted in the near future too, because it shares certain characteristics, you know, with coding, with advertising and so forth. To give one example, you know, on the lending side, you know, credit scoring has historically been more of an art than a science.

Speaker #2: 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.

Speaker #2: 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.

James Mitchell: To give one example, you know, on the lending side, you know, credit scoring has historically been more of an art than a science.

Speaker #2: And there's been this universe of data available, but only a small subset of that universe has 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.

James Mitchell: You know, there's been this universe of data available, but only a small subset of that universe has actually, you know, fed into the model effectively. Versus now, with, you know, transformer-based models, you can sort of take the totality of data available and, you know, see what is predictive and, you know, improve your loan extension on the basis of that uplift in predictability. You know, I think it's an area that, you know, many companies will be investing a great deal of time and energy and, you know, where, you know, we'll be participating as well.

Speaker #2: 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.

Speaker #1: 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.

Wendy Huang: 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 us 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.