Tencent Holdings Limited

Good day and good evening. Thank you for standing by. Welcome to Tencent Holdings Limited 2026 First Quarter Results Announcement Webinar. I'm Wendy Huang from Tencent IR team. At this time, all participants are in a listen-only mode. After the management's presentation, there will be a question and answer session. For participants who dial in by phone, if you wish to ask a question, please press 5 on your telephone to raise your hand. If you are accessing from the Tencent meeting or VOOC meeting application, please click the raise hand button at the bottom left. And please be advised that today's webinar is being recorded. Before we start a presentation, we would like to remind you that it includes four looking statements, which are underlined by a number of risks and uncertainties, and it may not be realized in the future for various reasons. Information about general market conditions is coming from a variety of sources outside of Tencent. This presentation also contains some un-audited non-IFRS financial measures that should be considered in addition to, but not as a substitute for measures of the group's financial performance propelled in accordance with IFRS. For a detailed discussion of risk factors and non-IFRS measures, please refer to our disclosure documents on the IR section of our website. Now let me introduce the management team on the webinar tonight. Our Chairman and CEO Pony Ma will kick off with a short overview. President Martin Lau and Chief Strategy Officer James Mitchell will provide a business review. And Chief Financial Officer John Lowe will conclude with financial discussion before we open the floor for questions. I will now pass it to Pony.

Thank you, Wendy. Good evening. Thank you everyone for joining us. We start 2026 by making significant initial progress on our new AI products, so as continue to utilize AI to grow our existing core business. The Hunyuan 3 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 productive AI agent solutions have attained early traction and we believe that our work body is currently the most widely used productivity AI agent service in China. Our core businesses continue to grow their engagement, revenue and profit, providing the cash flow to fund our AI investments as well as use cases for future AI deployments. Looking at our financial numbers for the first quarter, total revenue was 196 billion RMB up 9% year-on-year, adjusting for the impact on revenue recognition for our value added services from the later spring festival this year compared to last year. Total revenue would have increased 11% year-on-year. Gross profit was 111 billion RMB up 11% year-on-year. Non-IFRS operating profit was 76 billion RMB up 9% year-on-year. 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. Turning to our key services for communication and social networks, combined MAU of WeChat Group year-on-year and quarter-on-quarter to 1.4 billion. 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. For games, Honor of Kings and Peacekeeper Elite achieved record highs in gross receipts during the first quarter of 2026. While newly released creator collecting game, Roku Kingdom World achieved breakout success. Tencent Cloud's AI agent solutions achieve the rapid growth and healthy retention rate. Now I will hand over to Martin for the business review.

Thank you, Pony, and good evening and good morning to everybody on the call. For the first quarter of 2026, our total revenue was up 9% year-on-year. As Pony mentioned, our total revenue growth was impacted by the later timing of Spring Festival this year compared to last year, which shifted to more games related revenue recognition to future periods. Adjusting for the timing of the Spring Festival, total revenue would have been up 11% year-on-year on a for-like basis. By segment, NAS represented 49% of our total revenue, within which social networks sub-segment was 16%, domestic games sub-segment was 23%, and international games was 10%. Marketing services was 19% of total revenue, and fintech and business services was 31%. Our gross profit was up 11% year-on-year in the first quarter to 111 million RMB. Bass gross profit increased to 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. And FinTech and business services gross profit increased 13% year-on-year, contributing 28% of total gross profit. Now, a bit of update on our AI initiatives. Over the last six months, we have made significant progress on our Huanyuan large language model, but I would say it's just getting started. We started the initiative by completely overhauling our foundation model team, centering around newly added elite AI researchers and engineers with deep expertise in large language models. Our new team is young, energetic and cohesive, enabling us to make progress quickly in this highly dynamic AI era. In February, we re-engineered the system and process for pre-training and reinforced 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. And 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 Kunyuan 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. The core design principles behind Huanyuan 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. And by co-designing inference with model, we're able to reduce costs significantly so that the intelligence is economical enough to be used at scale. Huanyuan 3 Preview has delivered on these expectations. The model has already become a leading reasoning model in China and has proven effective in real-world software engineering and other productivity agent tasks. Internally, the model has been deployed across 131 widely used internal products, including Yuanbao, QQ, and WorkBuddy, providing valuable feedback and iterative improvement vehicle design process. And externally, 1.3 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 28th and continued its lead even after its free 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. The next step is to scale up to larger models. Our Hunyuan team is already working on a larger parameter model, leveraging our infrastructure and learnings from Hunyuan 3 by aggregating bigger and better data sets and scaling more powerful reinforcement learning, we can strengthen the model's contextual understanding, enhances agent capabilities, including coding, and increase the model's general intelligence. Through co-designing and collaborating with other Tencent product teams, we are 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. Agents are more valuable in uplifting productivity from initial use cases of 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 Clause 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. Our platform inherently has many benefits of hosting AI agents, as users can control AI agents throughout 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 costs and performance. And in the future, AI agents will be able to access our mini programs ecosystem using mini programs codes as AI skills. Tencent has established an early lead in 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. 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 complimentary 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 pass on to James.