Baidu Q1 2026 Earnings Call | Ernie Bot Monetization Scales As Core Cloud Revenue Up 12%

We reported RMB 26.0 billion in total revenue in Q1, up 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 BU 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. Apollo Go also had a strong quarter. We delivered 3.22 million fully driverless rides in Q1, sustaining triple-digit growth in total rides year-over-year, reflecting the continued scaling of our operations. Together, these results confirm that AI has clearly become the primary growth driver of BU, 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 BU'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 BU'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 are 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 Kunin, our self-developed AI chips. We have seen strong and expanding demand for Kunin, with a growing number of customers across diverse industries adopting it for a broadening range of AI workloads. This reflects growing market recognition of Kunin'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, Kunin delivers broad compatibility with different models and frameworks as well as strong usability across enterprise environments. To date, it has been optimized and validated for workflows across various models covering the latest versions of Ernie and other mainstream foundation models, with inference support recently extended to Deepseek V4, GLM 5.1, and Minimax M2.7. As an important component of our AI infrastructure, Kunin further strengthens the foundation of our infrastructure layer, enabling BU's 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. BU's 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 Unitry, Honor, OPPO, and Bible. 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 MaaS front, as open source gained traction across the industry, we moved quickly to expand the model library on our Qianfan MaaS platform. In addition to Ernie, Qianfan now supports an expanding set of in-demand models, including popular ones from Chipo AI, Minimax, Kimi, 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 MaaS revenue also scaled rapidly, we believe the MaaS platform still has significant untapped potential as the ecosystem around agents and AI applications continues to evolve. On foundation models, we recently launched Ernie 5.1, which delivers stronger text capabilities, a more compact model size, and enhanced 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 Doommate, our AI agent for everyday productivity, which we recently showcased at BU Create. Doommate 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 Doommate is its seamless integration with BU's proprietary skills including AI search, coding, and more. As we continue to expand Doommate'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 hyperrealistic digital human technology continues 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 BU 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 script 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 TikTok and Shopee, with several partners deepening their collaboration with us. Next is Ma. Our vibe coding platform 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 Ma grew around 70% quarter over quarter, while our domestic paid user rate reached approximately three times the level at the end of last year. At BU Create we launched Ma 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, Ma now supports the generation of standalone mobile applications, further expanding what users can create with Ma. Another example is Faro agent. Our self-evolving agent designed to address complex operational challenges across industries and help enterprises unlock meaningful productivity gains. With the launch of Faro agent 2.0 at Create, we further expanded its accessibility. While earlier versions were primarily used by developers and technical teams, agent 2.0 zero 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 a port, one of the world's leading ports with highly sophisticated scheduling systems and deeply complex operational logic, Faro 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, Faro agent autonomously explores the solution space to identify optimal decisions across berth scheduling, equipment allocations, and cargo prioritization. Even on top of an already highly optimized baseline, Faro 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 significant reduction in low-quality content. Meanwhile, Ernie assistant continued to see strong user engagement driven by ongoing improvements to its interaction experience. In March, daily active users of Ernie 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 Ernie 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 robot taxi stands as the most powerful embodiment of this transformation. In Q1, Apollo Go, 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, Apollo Go's fully driverless operations are now running across multiple zones in Dubai. Also in late March, we officially launched the Apollo Go 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 Apollo's commercial reach. In Haidan, 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 Haiko airport. So Apollo Go is right there waiting as visitors step out of the terminal. We believe robot taxi can deliver value well beyond daily commuting, opening up new monetization opportunities in the process. As Apollo Go 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, Apollo Go has moved well beyond technology demonstration and small-scale pilots. At this scale, we are addressing a new frontier centered on how robotaxi services fit more naturally into public transportation, city operations, and everyday life. These experiences are helping us build the expertise and knowledge needed for Apollo Go 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.

Thank you, Alex. We have seen remarkably strong enterprise demand for AI infrastructure, both training and inference, with inference showing particularly strong momentum, which is a healthy signal. It tells us that customers have moved beyond training models and are now running AI across more parts of their business at an accelerating pace. Closely related to this, our MaaS platform is seeing strong traction. Qianfan is one of the very few MaaS platforms in China. As I just mentioned, besides Ernie, we have quickly expanded Qianfan's model library to include the most in-demand models like Deepseek, GLM, Minimax, and others. We're seeing continued growth in token consumption from external customers. Importantly, supporting new models quickly is not a simple plug-and-play process. It requires high-throughput inference and efficient model serving capabilities so we can run these models reliably at scale and serve more token demand with the same amount of compute. Demand is broad-based across verticals including AI, autonomous driving, embodied AI, gaming, advanced manufacturing, and more. It's not just existing customers spending more; we keep winning new ones too, including industries that historically weren't heavy users of AI and cloud computing, like retail and IT-based consumer brands. The addressable market is still expanding, and with demand remaining strong and supply relatively tight, we are actively expanding capacity and improving resource efficiency to better support growing customer needs. Our confidence in capturing this demand comes from our differentiated full-stack AI capabilities, which provide two key advantages. First, efficiency: owning and optimizing across the full stack enables us to deliver highly competitive price performance for customers. Second, our proprietary chips have earned strong recognition in real-world deployments. On margins, the key driver is business mix. GPU cloud usually carries better margin profiles than traditional CPU cloud for a few reasons. First, GPU cloud is technically more complex with much higher barriers to entry. We were actually one of the earliest cloud providers in China to build GPU cloud at scale, and we remain at the forefront. Second, demand remains very strong while high-quality supply is relatively tight. Customers prioritize proven performance, stability, and availability, not just cost. Certainly, our proprietary AI chips and full-stack capabilities give us more room to optimize cost, and continued improvement in our customer mix further supports margin expansion. So as GPU cloud takes a larger and larger share of our total cloud infrastructure revenue, we believe the blended margins for our cloud will improve structurally, and that's a durable ongoing trend. We're confident in the long-term profitability trajectory of our cloud business. Thank you, Alex.

Hi Alicia, this is Robin. The model landscape is moving very quickly with active releases from players both in China and globally. We believe model capabilities will continue to advance rapidly, and strong in-house foundation model capabilities remain essential. So we will continue to invest in Ernie with conviction. Meanwhile, we have always believed that models ultimately create value through applications. That's why we have consistently taken an application-driven approach. Each iteration of Ernie is guided by real product needs and use-case scenarios. Most recently, we released Ernie 5.1, which achieved leading results on the LM Arena text and search leaderboards, demonstrating continued progress in text capability, reasoning, and search. Going forward, we will continue to iterate Ernie in line with the needs of our key applications: AI search, digital humans, Ma, and Faro agent. These are among the application areas we believe hold the greatest value, and our goal is to build the strongest capabilities where they matter most. For example, we will keep improving Ernie's capability to understand user intent and assess content quality so AI search can deliver more accurate, higher quality, and more intelligent results. We are also strengthening Ernie's text and multimodal capabilities to make our digital humans more vivid, hyperrealistic, and more effective at engaging users and driving sales in e-commerce live streaming. We are enhancing coding capabilities to better support vibe coding, enabling users to build applications through natural language. As coding becomes an increasingly foundational capability in the AI era, this will be a growing area of focus. And we will continue to strengthen Ernie's capability to identify better and better solutions across complex real-world scenarios, helping enterprises in a wide range of industries achieve greater efficiency gains. To better support these directions, we have also made organizational adjustments to our model teams, and we'll continue to evolve our structure as needed. We're confident that Ernie will keep getting stronger across all of these areas. Besides Ernie, we also have a range of smaller, faster, and more efficient models, as well as model combinations optimized for specific scenarios. Different use cases have different requirements for capability, cost, latency, and deployment efficiency. Our goal is always to deliver the best outcome for each application. Over the longer term, we believe the full potential of AI applications is still far from realized. As more AI use cases unfold, the value of our application-driven approach will become even clearer, and Ernie will become more capable and more valuable along the way. Thank you.

Hi, this is Robin. First on scale, Apollo remains a global leader. We've completed over 22 million cumulative rides as of April. China is one of the most open markets in the world, so it's natural that our domestic scale today is significantly ahead of overseas markets. But we are also seeing more markets globally opening up for robotaxi, with the regulatory environment turning more positive. We are really happy that our domestic operational experiences prepare us well for international expansion. We have made significant progress in a very short period. We only began accelerating our international expansion a few quarters ago, and our footprint has expanded across key markets in Europe, the Middle East, and Asia. That pace reflects the scalability of both our technology and our operations across different market environments. Our confidence in overseas expansion is backed by the large-scale operational capabilities we've proven out in China through years of real-world fully driverless operations. We have accumulated deep experience in complex road conditions, operational challenges, and corner cases that only emerge at certain scale. This is not something that can be built overnight. These experiences have continuously sharpened our algorithms and operational standards, making our robotaxi operations progressively more robust with every mile driven. So when we expand globally, that accumulated experience travels with us and helps us move faster. A good example is our progress from Hong Kong to London. Hong Kong has been an important right-hand drive robotaxi market for us. Over the past year plus, we have accumulated valuable experience there, and that know-how has helped support our recent entry into London, another major right-hand drive market. Regarding profitability, Apollo Go has already achieved unit economic break-even in its largest operational city in China, despite very low fare levels. As we expand globally, the pricing environment becomes much more attractive. We believe our overseas operations have the potential to deliver much stronger profitability as they continue to ramp up. The overall international market outside of the US and China is also bigger than the China domestic market. Finally, on our long-term role in the ecosystem, I think it's still early to call. The robotaxi industry is still evolving, and both the value chain and business models are still taking shape. What we are focused on right now is continuing to scale, deepening our technology and operational advantages, and maintaining our global leadership. With that foundation in place, we will have the strategic flexibility to define our role as the ecosystem matures and capture long-term value accordingly. Thank you.