Baidu, Inc.

Hello and thank you for standing by for Baidu's second 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. If you wish to ask a question, You will need to press the star key followed by the number 1 on your telephone keypad. 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 second quarter 2026 earnings conference call. Baidu's earnings duties were distributed earlier today, and you can find a copy on our website as well as on newswire services. On the call today, we have Robin Li, our co-founder and CEO, Julius Rong Luo, our EVP in charge of Baidu Mobile Ecosystem Group, MEG, Dou Shen, our EVP in charge of Baidu AI Cloud Group, ACG, and Henry Haijian He, 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 may 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 findings with S&C and the 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 annotated non-GAAP financial measures. Our press release contains a reconciliation of the annotated non-GAAP measures to the annotated most directly comparable GAAP measures and is available on our IR website at ir.baidu.com. As a reminder, this conference is being recorded. A webcast of this conference call will be available on Baidu's IR website. I will now turn the call over to our CEO, Robin.

Hello, everyone. In Q2, Baidu General Business generated total revenue of RMB 25.2 billion, with Baidu Core AI-powered business continuing to represent half of the total, reinforcing AI's position at the core of our business. AI Cloud Infra delivered another quarter of strong growth with overall revenue increasing 50% year-over-year, once again outpacing the broader market. Within AI Cloud Infra, GPU cloud revenue nearly quadrupled year-over-year, growing 283% and accelerating significantly from an already strong 184% growth rate last quarter. With AI powered business now at the core of our revenue mix, we are focused on building a stronger foundation for its next phase of growth. Across our full AI stack, from chips and cloud infrastructure to models and applications, we are continuing to strengthen the capabilities that will support sustained innovation, power our future growth, and reinforce our long-term competitiveness. Let me now turn to the key business highlights of this quarter, starting with our proprietary AI chips, Kunlunxin. In Q2, Kunlunxin continued to demonstrate strong business momentum, with demand remaining robust and broadening across industries. A growing number of customers are adopting its chips for an expanding range of AI workloads, reflecting increasing market recognition of Kunlunxin's stability, efficiency, and versatility at scale. Kunlunxin continues to strengthen its software ecosystem, broadening compatibility with leading models and frameworks, and improving ease of deployment across enterprise environments. Building on its support for Ernie, and other leading foundation models in China. Kun Lunxin further extended its coverage in Q2 to include newer versions of major Chinese foundation models, such as Kimi EK3, GLM 5.2, Minimax M3 and Huiyuan 3. It also improved inference throughput and overall compute efficiency, strengthening its ability to support diverse and demanding AI workloads at scale. Over more than a decade, Kunlunxin has successfully developed and commercialized three generations of AI chips. Building on this track record, it continues to advance a clearly defined product roadmap, including the latest M100, optimized for large-scale inference, and the upcoming M300. This roadmap reflects Kunlunxin's deep understanding of evolving AI technology, workflows, and their compute requirements. positioning it to support the next wave of AI innovation. As we continue to advance our AI infrastructure capabilities, we believe sequencing will play an increasingly important role within our full-stack AI architecture and enhance our ability to deliver high-performance, reliable, and cost-efficient AI computing at scale. As demand for AI computing in China continues to grow, we believe our proprietary AI chips and full-stack capabilities will become increasingly valuable, supporting the future growth of our AI businesses and reinforcing our long-term competitiveness in AI. Building on our strengths at the infrastructure layer, AI Cloud Infra delivered another quarter of strong growth In Q2, AI Cloud Infra revenue increased by 50% year-over-year, continuing to outpace the broader industry. Several factors combined to drive this sustained growth momentum. First, AI Cloud Infra continued to benefit from strong demand for AI computing. Demand remained robust across both training and inference workloads, while computing supply remains constrained across the market. Second, our existing key clients, including leading companies in online gaming, e-commerce, and lifestyle content, continue to increase both their usage and spending with us. Meanwhile, our overall customer count grew rapidly, with new clients spanning companies of varying sizes. Third, demand remained broad-based across industry verticals, including internet, embodied AI, autonomous driving, smartphones, financial services, and more. Within this mix, internet and autonomous driving sustained strong growth while embodied AI revenue grew approximately six-fold year-over-year in Q2. Based on these trends, we believe AI cloud infra-revenue growth will remain strong in the second half, with the potential for further acceleration. Importantly, the growth in AI Cloud Infra was accompanied by rapid profit growth and expanding margins on a year-over-year basis, reflecting continued improvement in the overall health and quality of the business. Within AI Cloud Infra, GPU cloud revenue growth accelerated sharply to 283% year-over-year. Building on an already high base of 184% growth last quarter, this momentum reflects strong underlying demand for scalable AI compute in the public cloud. The mix of our business continues to shift toward higher quality revenue streams, with GPU Cloud accounting for a growing share of AI Cloud infra revenue. Given its more attractive margin profile, this shift is contributing to a healthier revenue mix and strengthening the long-term profitability of our cloud business. On MaaS, our Tianfan MaaS platform offers one of the most comprehensive model libraries, covering Baidu's Ernie family, as well as virtually all of China's leading models. A key priority for Tianfan is to make model inference at scale more reliable and cost-efficient for customers. Leveraging our deep expertise in AI infrastructure and engineering, we further enhanced model serving through continued inference optimization, delivering higher throughput and greater service stability while reducing latency and inference costs. In Q2, revenue from external customers' token usage on Qianfan grew more than ninefold year-over-year, primarily driven by rapid growth in daily average token consumption among these customers. Turning to foundation models, advancing learning and our overall model capabilities remains important to our next phase of AI-driven growth. Our commitment to foundation model innovation remains unwavering. As discussed in prior quarters, we reorganized our model teams into two groups with clearer mandates and greater focus across foundation models and applications. More recently, we welcomed a new generation of top AI talent to work on foundation models, further demonstrating our determination to compete and innovate at the forefront of AI. We believe these efforts will support the continued evolution of Ernie and strengthen the foundation for future innovation across both models and AI applications. Moving next to AI applications, where we continue to enhance product capabilities and expand real-world use cases. Let me begin with digital humans. As our digital human technology continues to advance, it is delivering stronger performance at lower cost and enabling an expanding range of use cases. From e-commerce live streaming and digital human videos to real-time interactive digital humans and our newly introduced video podcast, these advances are opening up far broader possibilities for how digital humans can be used across industries. Our digital human capabilities are gaining increasing recognition from clients. In Q2, we continue to win new clients, including leading companies across industries, while existing clients also meaningfully scaled their usage. Some of our clients started with a pilot and after seeing what our digital human technology could deliver, expanded their usage. A well-known Chinese internet company, for example, expanded its digital human live streaming deployment to approximately 2.5 times the previous level after just one quarter of use. Meanwhile, we continue to advance the global expansion of our digital human capabilities. Since launching our overseas digital human platform last quarter, we've seen encouraging momentum with its differentiated capabilities delivering compelling results for merchants and creators overseas. As demand continues to unfold across more industries and regions, we believe the long-term growth potential for digital humans remains substantial. Turning next to MiaoDa, our VIVE coding platform, with the launch of MiaoDa 3.0 last quarter, users can now generate standalone mobile apps for both Android and iOS using natural language. Applications that once required a professional development team, a lengthy development cycle and significant investment can now be completed far more easily through MiaoDa, even directly from a phone. We are seeing users engage with MiaoDa more deeply. An increasing number of users are moving beyond one-off experimentation and returning to MiaoDa to continue developing. It is reading on and refining their applications over time, reflecting stronger user stickiness. In June, Miaoda's monthly active users increased by 67% compared with March. Adoption is also expanding across industries ranging from technology and education to healthcare, manufacturing, financial services, and logistics, demonstrating Miaoda's applicability across diverse business scenarios and its broader commercialization potential. We are also applying AI to help enterprises solve complex operational problems. A good example is PhamoAgent, which can autonomously explore possible solutions to identify the best ones. Following the launch of PhamoAgent 2.0 last quarter, we have continued to improve its usability and expand the scenarios it can address. Phamo agent has attracted growing interest from leading enterprises and begun to gain early commercial traction this quarter. We are pleased to see Phamo agent moving beyond efficiency gains to help enterprises optimize their operations and deliver real, tangible business value. As its capabilities continue to advance, we believe its potential will continue to grow. Another key direction for our AI applications is general purpose agents. Earlier this year, we launched DouMate, our general purpose agent for everyday productivity with seamless access across PC and mobile. In Q2, we introduced an enterprise version and continued to expand Duminate's proprietary Baidu skills and specialized toolkits, broadening the range and sophistication of tasks it can support. Meanwhile, our flagship consumer-facing AI applications, Baidu Wenku and Baidu Dry, continue to embrace AI across the board, introducing new AI capabilities, sharpening existing ones. and this quarter rolling out an upgrade to GameFlow that brings AI more deeply into users' everyday workflows. In June, AI DAU penetration across Baidu Wenku and Baidu Drive increased by 27.4% year-over-year, reflecting broader adoption of their AI-powered features. Turning to AI search, we continue to improve both the quality of AI-generated answers and the overall user experience. Users are increasingly receiving answers that are more reliable, better structured, and more effectively presented. At the same time, hallucination rates remain low while our models became more effective at assessing content quality, helping reduce the incidence of low-quality answers. Together, these improvements draw better user experience and higher user satisfaction. We also further integrated AI search with Ernie Assistant, extending the search experience beyond one-time answers into more seamless and interactive conversations that can better address users' follow-up questions and broader needs. In June, Ernie Assistant's daily active users grew 83% year-over-year, while daily average conversation rounds more than tripled, reflecting growing user adoption and deeper engagement with this evolving search experience. Turning now to AI in the physical world, let me discuss ApolloGo, our autonomous ride-hailing service. This quarter, we continue to advance global expansion while further enhancing safety, operational performance, and the rider experience. Hong Kong marked an important milestone for ApolloGo this quarter. In June, we received Hong Kong's first permits for fully driverless testing and began testing on Airport Island in July. This made ApolloGo the first autonomous ride-hailing service provider globally to conduct fully driverless testing in a right-hand drive, left-hand traffic robotaxi market. Hong Kong is one of the world's most sophisticated urban mobility markets with a complex operating environment and rigorous standards for both technology and operations. Reaching this milestone in Hong Kong provides strong validation of the maturity and adaptability of our technology and operational capabilities. The experience we have gained in Hong Kong is already helping us advance more efficiently in London. In July, ApolloGo began open-road testing there in partnership with Uber and Lyft. Together, our progress in these two markets demonstrates our technology's ability to generalize across different operating environments, giving us greater confidence in expanding into more and more high-value right-hand drive, left-hand traffic robotaxi markets over time. We also made progress across several other international markets. In Dubai, we launched fully driverless commercial operations in July and now operate at the largest scale among fully driverless autonomous ride-hating services in the city with rides available through both the Apollo GO and Uber apps. In Switzerland, we began open-road testing in partnership with Hostbus. We also signed a memorandum of understanding with Kazakhstan's Turlov Private Holding Limited to jointly explore autonomous ride-having services in the country. Overall, ApolloGo delivered around 1 million fully driverless operational rides in Q2. As of June 2026, cumulative rides provided to the public by ApolloGo exceeded 23 million. Ride volume during the quarter was temporarily affected by operational adjustments in certain domestic cities due to regulatory considerations. Over this period, we conducted a systematic review to further strengthen the robustness of our autonomous driving systems and the rigor of our operational processes. As of August, operations in the affected cities had begun to resume on a stronger footing. Meanwhile, we continued to expand our operations across other domestic markets. We are confident that ride volume will regain momentum over the coming quarters as we steadily ramp up operations and pursue further expansion. In Q2, we continue to raise the bar on safety and the rider experience. As of the end of June, our fully driverless vehicles recorded an average of approximately one airbag deployment every 14.4 million kilometers, underscoring our industry-leading safety performance. We also enhanced pick-up and drop-off point recommendations to reduce walking distances and avoid unsuitable stopping locations, while further improving perception and motion planning capabilities to deliver smoother and more consistent rides. These improvements represent an even higher operating standard when we intend to build on as we continue to integrate ApolloGo more seamlessly into urban transportation systems, making it a more convenient and trusted part of everyday mobility. Looking ahead to the second half, our priorities for ApolloGo are clear. Further enhance our safety standards and operational capabilities advance our global expansion, scale our fleet and ride volumes, and bring more cities to unit economic spread even. We believe progress across these priorities will further strengthen ApolloGo's leadership in autonomous ride hailing and lay a stronger foundation for scaling its operations safely and sustainably over the long term. To summarize, the progress we made across our full AI stack this quarter reaffirms Baidu's transition into an AI-first company and further strengthened the foundation for our next phase of growth. We are also actively expanding our AI businesses into global markets and are encouraged by the progress we are already seeing, including in AI applications and robot taxing. With this stronger foundation, we believe we are well-positioned to capture a broader range of opportunities across markets over time. With that, let me turn the call over to Henry to go through the financial results.