Baidu, Inc.

Hello and thank you for standing by for Baidu's first quarter 2026 earnings conference call. At this time, all participants are in a listen-only mode. After management's prepared remarks, there will be a question and answer session. Today's conference is being recorded. If you have any objections, you may disconnect at this time. I would now like to turn the meeting over to your host for today's conference, Juan Lin, Baidu's Director of Investor Relations.

Hello, everyone, and welcome to Baidu's first quarter 2026 earnings conference call. Baidu's earnings release was distributed earlier today, and you can find a copy on our website as well as on Newswire Services. On the call today, we have Rodney Lee, our co-founder and CEO. Julius Rongluo, our EVP in charge of Baidu Mobile Ecosystem Group, MEG. Zhou Shen, our EVP in charge of Baidu AI Cloud Group, ACG. And Henry Haigiancu, our CFO. After our prepared remarks, we will hold a Q&A session. Please note that the discussion today will contain forward-looking statements made under the safe harbor provisions of the U.S. Credit Security Litigation Reform Act of 1995. Forward-looking statements are subject to risks and uncertainties that cause actual results to differ materially from our current expectations. For detailed discussions of these risks and uncertainties, please refer to our latest annual report and other filings with SEC and Hong Kong Stock Exchange. Baidu does not undertake any obligation to update any forward-looking statements except as required under applicable law. Our earnings press release and this call include discussions of certain unaudited non-GAAP financial measures. Our press release contains a reconciliation of the unaudited non-GAAP measures to the unaudited most directly comparable GAAP measures and is available on our IR website at ir.biz.com. As a reminder, this conference is being recorded. In addition, a webcast of this conference call will be available by this IR website. I will now turn the call over to our CEO, Robin.

Generated RMB 26.0 billion in total revenue in Q1 of 2% year-over-year, marking a return to positive growth. Revenue from our core AI-powered business reached RMB 13.6 billion, up 49% year-over-year. For the first time, it accounted for more than half of Baidu general business revenue, reaching 52%. This is an important milestone as AI-powered business has now become the majority of our revenue mix. AI Cloud Infra delivered exceptional momentum in Q1 with overall revenue growing 79% year-over-year. Within AI Cloud Infra, GPU cloud revenue continued its strong trajectory from last quarter's 143% growth, accelerating further to 184% year-over-year. ApolloGo also had a strong quarter. We delivered 3.2 million fully driverless rides in Q1, sustaining triple-digit growth in total rise year-over-year, reflecting the continued scaling of our operations. Together, these results confirm that AI has clearly become the primary growth driver of Baidu, reinforcing our position as an AI-first company. As AI adoption continues to accelerate, real-world applications are expanding opening up new and increasingly diverse demand for AI capabilities. We are confident in our ability to capture these opportunities as they unfold and believe AI will continue to drive the next phase of Baidu's growth. Now, let me walk you through the key highlights of this quarter, starting with AI Cloud Infra. As AI adoption accelerates across industries, we continue to see demand surge across both training and inference workloads, with inference ramping especially fast and accounting for a growing share of overall demand. Q1 was a quarter of significantly accelerated growth for our AI cloud infra, with revenue growth well above the broader market. The mix of our business continued to shift toward higher quality revenue streams. GPU cloud, which typically carries stronger margins, has become a meaningful contributor to our total AI cloud infra revenue, underscoring the ongoing improvement in overall business health. A key driver behind this momentum is the differentiated advantage of Baidu's full-stack AI capabilities, one that very few companies globally can truly claim. With proprietary components at every layer from underlying infrastructure to applications, we were able to ensure stable and reliable compute supply while also optimizing end-to-end across the entire stack, continuously improving performance, reducing costs, and delivering compelling cost effectiveness for our customers. As AI applications continue to proliferate, this full-stack advantage becomes increasingly pronounced, enabling us to capture a broader and more diverse range of opportunities. At the infrastructure layer, we hold a distinct advantage through Kunlun Xin, our self-developed AI chips. We have seen strong and expanding demand for Kunlun Xin, with a growing number of customers across diverse industries adopting it for a broadening range of AI workloads. This reflects growing market recognition of Kunlunxin's stability, efficiency, compatibility, and versatility. It is also among the first domestic AI chips to achieve large-scale commercial deployment in a single AI computing cluster of over 30,000 accelerators, with industry-leading cluster performance and stability. Built on a comprehensive software stack, Kunlunxin delivers raw compatibility with different models and frameworks, as well as strong usability across enterprise environments. To date, it has been optimized and validated for workloads across various models, covering the latest versions of Ernie and other mainstream foundation models, with inference support recently extended to DeepSeq v4 GLM 5.1 and Minimax M2.7. As an important component of our AI infrastructure, Kunlunxin further strengthens the foundation of our infrastructure layer, enabling Baidu AI Cloud to support customers' AI deployment with greater efficiency, reliability and cost effectiveness, and enhancing the overall competitiveness of our cloud offerings. These advantages are translating into strong client momentum on the infrastructure side. Baidu AI Cloud has become a trusted infrastructure partner for a growing number of major companies across a broad range of industries, including internet, gaming, embodied AI, autonomous driving, smartphones, financial services, and more. This quarter, we added several prominent new clients, including leading model companies. Our client base also includes leading names such as Unitree, Honor, Opal, and Bevo. At the same time, existing top-tier clients continue to deepen their collaboration with us and scale their usage, driving healthy expansion across our client base. On the MOS front, as OpenClaw gained traction across the industry, we moved quickly to expand the model library on our Qianfan MOS platform. In addition to Ernie, Qianfan now supports an expanding set of in-demand models, including popular ones from Zhipu AI, Minimax, Kimmy, and DeepSeek, keeping our model library comprehensive and up-to-date. In March, daily average token consumption from external customers grew to nearly seven times the level of a year ago, while our MOS revenue also scaled rapidly. We believe the MOS platform still has significant untapped potential as the ecosystem around agents and AI applications continues to evolve. On foundation models, we recently launched Earning 5.1, which delivers stronger tax capabilities, a more compact model of size. and enhanced the reasoning compared to its predecessor. We also made advances in key areas, including code generation, agentic capabilities, and deep search. Recently on the LM arena, Ernie 5.1 ranks first among Chinese models on the text leaderboard. Ernie 5.1 also topped the LM arena search leaderboard among Chinese models, ranking fourth globally making it the only Chinese model to appear on that leaderboard as well. Looking ahead, we remain firmly committed to advancing Ernie through an application-driven approach, continuously iterating based on real-world needs to keep Ernie at the forefront of AI capabilities. Now let me turn to AI applications. We have long believed that the true value of AI is ultimately realized through applications. and we have been early and persistent in building a comprehensive portfolio serving both enterprises and individual users. This quarter, we continue to see encouraging progress across several high potential directions. Let me highlight a few examples. The first is DoMate, our AI agent for everyday productivity, which we recently showcased at Baidu Create. Do-Mate is designed to execute complex, multi-step workflows across applications and files autonomously, handling long-running tasks from start to finish. Available across both PC and mobile, it enables users to initiate tasks anytime and from anywhere while operating continuously in the background as a 24-7 AI assistant. Users simply describe what they need and come back to results. What truly differentiates DuMate is its seamless integration with Baidu's proprietary skills, including AI Search, Vibe Coding MiaoDa, FaMou, and more. As we continue to expand DuMate's skill ecosystem, we believe it will be able to better tackle an ever-wider range of office workflows and complex, real-world tasks, helping users complete them end to end more effectively, Turning to digital humans, our hyper-realistic digital human technology continued to advance with improved performance and increasing readiness for large-scale deployment. On the cost front, we achieved around 80% cost reduction over the past two quarters, lowering the adoption barrier and making our digital humans more affordable and accessible for a broader range of clients. Meanwhile, we are also taking our digital human capabilities global. At the recent Baidu Create, we launched an overseas digital human platform that enables merchants and creators to easily generate digital human content from e-commerce live streams to digital human videos and beyond. To make our digital humans truly work for global markets, we have built in deep localization from the ground up. supporting 24 languages including Spanish, French, and Thai with scripts and presentation styles culturally adapted to resonate with local audiences. This helps merchants run round-the-clock digital human live streams that feel authentically native, unlocking new levels of efficiency and conversion potential across global markets. Our growing partner base in China and overseas includes Jingdong, Suoyebang, TikTok, and Shopee, with several partners deepening their collaboration with us. Next is MiaoDa, our vibe coding platform. MiaoDa empowers anyone to bring their ideas to life without writing a single line of code, and we are seeing this value increasingly recognized. In March, monthly active users of MiaoDa grew around 70% quarter over quarter, while our domestic paying user rate reached approximately three times the level at the end of last year. At Baidu Create, we launched MiaoDa 3.0, introducing an enterprise version and a mobile app, enabling broader adoption across both individuals and enterprises. as well as more flexible usage across time and use scenarios. Notably, MiaoDa now supports the generation of standalone mobile applications, further expanding what users can create with MiaoDa. Another example is Phamo Agent, our self-evolving agent designed to address complex operational challenges across industries and help enterprises unlock meaningful productivity gains. With the launch of FAMO Agent 2.0 at Baidu Crate, we further expanded its accessibility. While earlier versions were primarily used by developers and technical teams, FAMO Agent 2.0 lowers the barrier to entry by enabling domain experts to interact with the agent directly through natural language, no coding expertise required. For example, at Qingdao port, one of the world's leading ports with highly sophisticated scheduling system and deeply complex operational logic, FAMO agent is helping push the efficiency of an already advanced system even further. In an environment where thousands of interdependent variables must be coordinated in real time, FAMO agent autonomously explores the solution space to identify optimal decisions across birth scheduling, equipment allocation, and cargo prioritization. Even on top of an already highly optimized baseline, FAMO agent continues to unlock incremental efficiency gains, further enhancing the overall operational performance. Next is AI search. In Q1, We continue to advance our AI search transformation with a particular focus on improving user satisfaction and the overall search experience. Through ongoing enhancements in model capabilities, we further improved how search results are planned, structured, and generated, enabling better assessment of content quality, broader distribution of high-quality information. and a significant reduction in low-quality content. Meanwhile, Early Assistant continued to see strong user engagement, driven by ongoing improvements to its interaction experience. In March, daily active users of Early Assistant nearly doubled year over year, while daily average conversation rounds more than tripled over the same period. Next day, retention also improved meaningfully, reflecting stronger user stickiness. Looking ahead, we will continue to deepen the integration between AI Search and Early Assistant, further enhancing the experience across information discovery, content understanding, and task completion. Beyond the digital world, AI is reshaping the physical world in profound ways and Robotaxi stands as the most powerful embodiment of this transformation. In Q1, ApolloGo, our Robotaxi business, maintained strong momentum with fully driverless rides continuing to grow and our safety record remaining industry-leading. We also continued to advance our international expansion, making steady progress across key overseas markets. In Europe, we are on track to commence open road testing in Switzerland, and our first vehicles have arrived in London in preparation for testing with Uber and Lyft, expected to begin soon. In the Middle East, ApolloGo's fully driverless operations are now running across multiple zones in Dubai. Also in late March, we officially launched the ApolloGo app making us the first and only autonomous ride-hailing service with its own standalone app there. Beyond traditional ride-hailing, we are exploring new use cases that broaden ApolloGo's commercial reach. In Hainan, one of China's most popular tourist destinations, we partnered with Car, Inc. on a rental model with our fully driverless vehicles stationed directly at the arrival level of Haiku Airport. So ApolloGo is right there waiting as visitors step out of the terminal. We believe Robotaxi can deliver value well beyond daily commuting, opening up new monetization opportunities in the process. As ApolloGo continues to scale fully driverless operations, we have encountered a broader and increasingly complex range of real-world scenarios, including system and operational complexities that only emerge at larger scale. When such situations arise, we handle them with rigor and use them to continuously strengthen our operations. More broadly, ApolloGo has moved well beyond technology demonstration and small-scale pilots. At this scale, we are addressing a new frontier centered on how robo-taxi services fit more naturally into public transportation, city operations, and everyday life. These experiences are helping us build the expertise and knowledge needed for ApolloGo to coexist more seamlessly with the broader transportation ecosystem over time and ultimately to become a more convenient and trusted service for the people we serve. In closing, our AI-powered businesses delivered strong momentum across the board in Q1. AI has now become the core driver and the majority of our business. and we see this role only growing from here. As we scale AI across an increasingly diversified portfolio and extend our reach into global markets from AI applications to autonomous ride hailing, we see significant opportunities opening up on multiple fronts. We are confident in our ability to capture them. With that, let me turn the call over to Henry to go through the financial results.