Baidu, Inc. (NASDAQ:BIDU) Q2 2025 Earnings Call Transcript

Baidu, Inc. (NASDAQ:BIDU) Q2 2025 Earnings Call Transcript August 20, 2025

Baidu, Inc. beats earnings expectations. Reported EPS is $1.9, expectations were $1.74.

Operator: Hello, and thank you for standing by for Baidu’s Second Quarter 2025 Earnings Conference Call. [Operator Instructions]. Today’s conference is being recorded. [Operator Instructions] I now like to turn the meeting over to your host for today’s conference, Juan Lin, Baidu’s Director of Investor Relations.

Juan Lin: Hello, everyone, and welcome to Baidu’s Second Quarter 2025 Earnings Conference Call. Baidu’s earnings release was distributed earlier today, and you can find a copy on our website as well as our 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 Securities 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 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.baidu.com. As a reminder, this conference is being recorded. In addition, 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.

Yanhong Li: Hello, everyone. In Q2, Baidu Core’s total revenue was RMB 26.3 billion. Our AI cloud continued to gain momentum, growing 27% year-over-year to RMB 6.5 billion. Notably, Baidu Core’s non-online marketing revenue exceeded RMB 10 billion for the first time. That’s up 34% year-over-year. This performance helped offset the near-term headwinds in our online marketing business. This year marks Baidu’s 20th anniversary as a public company. Over the past 2 decades, we remain grounded in our belief in technology and innovation. Today, technological advancement is unfolding at an unprecedented pace. We’ve embraced the mega trend with open mind, experimenting boldly adapting quickly and engaging deeply with AI frontiers. Amid rapid evolution, we’ve identified and doubled down on a few directions, we believe holds the greatest long-term value and are deepening our efforts with increasing clarity and confidence.

Foundation model development remains a key focus area where we are actively exploring the frontier of foundation model research and pushing the boundaries of AI capabilities. With an application-driven approach, we see earnings intuition towards areas with real world application value. such as the fundamental AI transformation of Baidu Search and our industry-leading digital human technology. Take digital human as a prime example, which represents 1 of the best applications of our ERNIE models. This quarter, powered by ERNIE, our digital human technology reached new levels of realism and capabilities, matching or even exceeding human performance in certain scenarios. A standout case was a live stream featuring the digital human of volume call, a top influencer in China.

The 7-hour live stream generated tens of millions in GMV fully powered by ERNIE series models. ERNIE 4.5 Turbo generated the complete script, including dialogue, tone and action queues. closely mirroring the real person’s communication style. Our multi-model capabilities delivered industry-leading visual realism with nuanced facial expressions, gestures and body movements that responded naturally to conversation flow in real time, achieving next level of performance that sets new standards in digital human technology. Beyond this flagship case, digital humans are empowering our broader merchant base with performance that already surpasses human live streaming hosts in many scenarios. Going forward, we will continue accelerating foundation model integration, strategically focusing our efforts on areas with application value where we can maintain our most competitive capabilities.

Beyond the model capabilities, our unique 4-layer end-to-end AI architecture has become a core competitive advantage and represents a key focus in our AI cloud business where our full stack AI capabilities are driving healthy growth. As the infrastructure layer, we achieved a critical system engineering breakthrough this quarter by completing the large-scale stable deployment of prefiled detailed separation architecture. This breakthrough significantly improves inference on currency and resource utilization, while substantially reducing inference costs. The achievement was made possible at the end to end optimization enabled by our unique 4-layer AI architecture. spending infrastructure framework models and applications, which allows us to comminate improvements across all layers.

At the same time, each layer remains open giving customers flexible choices between Baidu’s proprietary and third-party options. As a result, we continuously improving the cost effectiveness of our AI cloud products and solutions reinforcing our position as China’s top-tier cloud provider in the AI era. Meanwhile, our industry-leading MaaS platform, Qianfan continue to evolve to better support enterprise clients in building models and facilitating AI application development. Qianfan features a comprehensive model library covering nearly all mainstream foundation models on the market. This quarter, we further expanded the library with a range of new models, including our newly often sourced ERNIE 4.5 series, additional third-party multi-model models and other leading options enabling greater flexibility across enterprise use cases.

Leveraging our breakthrough in cloud infrastructure, Qianfan delivers enhanced stability, higher concurrency and lower inference costs when running models, meeting our superior price performance. On the tool chain front, Qianfan’s tool chains are among the most comprehensive with industry-leading reinforcement learning and post training tools for our model development. In Q2, Qianfan was further enhanced to support a wider range of AI tools and functions that can be caught via MCP or API including Baidu’s proprietary capabilities such as Baidu AI Search, Baidu Wiki, Baidu Maps as well as selected third-party capabilities like payment services. These enhancements helped simplify AI application development and continue to solidify Qianfan’s leadership as 1 of China’s top MaaS platforms.

Autonomous driving remains 1 of the most promising areas with long invested, which represents a critical frontier in physical world AI. Following the successful validation of our urban model at the end of last year, Apollo Go is now scaling rapidly. In Q2, Apollo Go provided over 2.2 million fully driverless rides to the public. That’s up 148% year-over-year, marking our strongest quarterly growth in 2 years. Also, Apollo Go’s global expansion has gained solid momentum, highlighted by two strategic partnerships with leading global life saving platform. In July, we announced a multiyear strategic partnership with Uber. Under this partnership, thousands of Apollo Go’s fully autonomous vehicles will be deployed on the Uber platform across multiple international markets with initial rollouts planned for Asia and the Middle East.

This milestone was followed by our partnership with Lyft in August, which will also bring thousands of our fully autonomous vehicles to key European markets through the Lyft platform. Starting with Germany and United Kingdom and sailing across Europe over time. Our expansion into international markets is built on a strong foundation. In China, we have already achieved positive unit economics in markets where ride fares are much lower than those in major overseas markets. That’s why this global partnerships are both logical and strategic, positioning us to capture greater value in higher fare markets while scaling efficiently. Our partners’ global market presence — leveraging our partners’ local market presence, we can accelerate market entry across different continents and achieve faster deployment while maintaining a cost-efficient asset-light business model.

In markets we’ve already entered, we continue to make encouraging progress in Hong Kong, one of the world’s most complex right- hand drive city. We recently expanded our testing coverage to include Tongcheng and Southern District advancing our open road testing into more complex urban scenarios across both commercial and residential areas. Also, we further strengthened our presence in the Middle East in Dubai and Abu Dhabi, we started open road testing in designated areas in August. Notably, Apollo Go leads the world in right-hand drive robotaxi market. This is a space where hardly any companies of our kind have entered, and we’ve made by far the most progress. The rapid progress we are making in Hong Kong really shows our global leadership.

It’s proof of how adept our technology is and how mature our operations have become across all kinds of environment. Our experience there provides us valuable insights for entering other right-hand drive markets, strengthening our confidence in scaling Apollo Go globally. With solid progress quarter by quarter, we are more confident than ever in Apollo Go’s international potential. As China’s largest autonomous ride hailing service provider and a global leader in this space, Apollo Go continues industry-leading technology — Apollo Go combines industry-leading technology, extensive operational experience and extraordinary safety records to bring safe, comfortable and affordable autonomous ride-hailing services to more markets worldwide than anyone else.

In our mobile ecosystem, transforming our products with AI remains a strategic priority, especially our legacy consumer-facing product Baidu Search. Baidu is at the forefront of applying AI to transform search globally rather than simply inserting AI summaries into search results. We are fundamentally revolutionizing the third experience by completely replacing static structural hyperlinks with intelligent, structured and multi-model first AI-generated responses. These responses start with relevant multi-model content right at the top. Making complex information more accessible to a broader user base and therefore, creating a more intuitive experience. In Q2, our AI transformation continued to accelerate, with AI-generated content reaching over 50% of mobile search result pages by the end of June up from 35% in April.

By July, 64% of mobile search result pages contained AI-generated content presented in a structured and multi-model first format, marking the broader rollout of our innovative AI search experience. This AI transformation reached over 90% of Baidu App’s monthly active users in July, with over 60% of such search result pages, starting with rich media elements such as images or videos. As we advance our AI transformation, the expanding content ecosystem across Baidu provides meaningful support leveraging ongoing progress in Gen AI and multi-model capabilities, Baidu’s AI-generated content has grown significantly in both scale and quality providing more high-quality content for search results. AI-generated multi-model content, in particular, has been a seen rapid expansion.

For example, daily AIGC video generation reached millions of units starting from May and daily AIGC video distribution within Baidu App has grown rapidly. We’re delighted to see sustained improvements in user metrics. In June, Baidu App’s MAU reached 735 million representing a 5% year-over-year growth. The daily average time spent per user in Q2 increased by 4% year-over-year. Building on Search, ability to satisfy user intent, we are expanding its boundaries from providing smart answers to completing tasks and connecting real-world services. For instance, our agents engaged users in multiround conversations, connect them with relevant service providers when needed and facilitate end-to-end task completion across multiple verticals. We believe this represents a meaningful expansion of what Search can achieve enabling users to seamlessly move from information to action.

Now let me review the key highlights of each business sector this quarter. AI cloud revenue reached RMB 6.5 billion in Q2, up 27% year-over-year with non-GAAP operating profit achieving year-over-year growth. The growth was primarily driven by the growing demand for our highly cost-effective end-to-end AI products and solutions. Within the enterprise cloud, which contributes the vast majority of AI cloud revenue, subscription-based revenue grew at a solid pace, signaling a healthier and more sustainable revenue structure. On the infrastructure layer, we continuously enhanced our resource management capabilities, achieving higher and higher infrastructure utilization. Through ongoing end-to-end optimization across our 4-layer AI architecture, combined with increasingly refined and efficient GPU resource management capabilities.

Our large-scale key clusters have achieved over 90% utilization rates recently for key tasks. Our enhanced capabilities allow us to deliver better performance at lower cost and provide more competitive pricing for enterprise customers, establishing a virtuous circle, where our growing customer base and diversified workloads further improve resource utilization, reinforcing our sustainable revenue model. In Q2, our customer portfolio continued to improve. existing clients deepen the collaboration and increased spending, while mid- tier enterprise clients demonstrated strong growth momentum. Additionally, this quarter marked several strategic partnerships with prominent companies across key verticals, including a leading lifestyle platform and top-tier gaming company in China.

In the embodied AI industry, we have partnered with 20 companies cumulatively, including Shenzhen Institute of Artificial Intelligence And Robotics for Society. In autonomous driving, we established a partnership with Black Sesame Technologies on AI cloud infrastructure. This partnership reflects the strong recognition of Baidu AI cloud and affirm our competitive positioning in China’s AI cloud market. Building on our full stack AI capabilities, we are not only serving enterprise clients but also driving internal productivity and mass- market AI adoption at the application layer. Internally, we widely adopted Comate, our AI coding assistant for developers. Comate capabilities continue to improve, enabling more agentic and efficient development workflow.

In July, AI contributed to generating over 45% of our new code with our developers providing oversight and approval. This has significantly boosted our engineering productivity and meaningfully enhanced our internal R&D efficiency. Externally, Miaoda extends this AI development capabilities to the broader community. Following Miaoda’s official launch last quarter, we are now delivering 2 no-code capabilities that enable users to create applications from mini games to utility tools and websites through simple natural language conversations with AI, no programming expertise required. As of July, users have created around 200,000 applications on Miaoda all built completely without writing a single line of code. We are continuously enhancing no code capabilities as we work toward our mission to democratize AI and empower anyone to innovate.

Moving to intelligent driving. In Q2, Apollo Go provided over 2.2 million fully driverless rides to the public, up 148% year-over- year. As of August, cumulative rides provided to the public have surpassed 14 million, underscoring the scale and maturity of our fully driverless operations. As of June, Apollo Go’s global footprint spans 16 cities. To date, our fleets have accumulated over 200 million autonomous kilometers with an outstanding safety record, which is a testament to the ability and safety of our autonomous driving technology. Beyond global partnerships like Uber and Lyft, we are accelerating the rollout of asset-light business models domestically. This quarter, we established new partnerships with HelloRide and T3 Mobility, expanding our collaborative network with leading mobility service providers.

Additionally, building on the partnership announced last quarter, Apollo Go’s fully autonomous vehicle rental service officially went live on the Car Inc. app. offering users a new access point to our Apollo Go fleet. These partnerships enable us to rapidly scale our services while leveraging partners’ operational expertise and existing customer bases, creating an efficient path to broader market penetration. Going forward, we are confident to further accelerate our global expansion and capture significant value across multiple markets worldwide. For mobile ecosystem, we continue accelerating AI transformation of search in Q2. In today’s highly competitive mobile Internet market, where new products and technologies are emerging and evolving faster than ever, user needs and behaviors are constantly shifting, making it essential for us to keep iterating at a rapid pace.

While our AI transformation is progressing rapidly, it is still in the early stages with considerable room for optimization before reaching its full potential. And we are not yet at the stage for large-scale monetization. Against this backdrop, we began prudent small- scale monetization testing in Q2 with user experience remaining our top priority. Early results have been satisfying. For example, some queries that we previously difficult to monetize are now showing potential. Agents maintained strong performance in driving better conversion efficiency, further validating our effectiveness. In Q2, revenue generated by our agents for advertisers grew 50% quarter-over-quarter, contributing 13% of Baidu Core’s online marketing revenue. That’s up from 9% in Q2 — in Q1.

In parallel, digital human gained traction as an innovative monetization avenue for our advertising business, particularly through AI-powered live streaming. We’ve seen steady growth in digital human adoption over recent quarters. Beyond serving live streaming hosts for merchants, they were being adopted at growing scale in health care, legal services, education and automotive sectors. More advertisers recognize their value in boosting conversion performance through real-time user interaction and round-the-clock availability, leading to increased ad budget allocation towards digital humans. In Q2, revenue generated by digital human increased by 55% quarter-over-quarter, contributing 3% of Baidu Core’s online marketing revenue. To sum up, as we look ahead, Baidu will stay anchored in our long-term mission and move forward with greater focus and resolve as we continue to translate AI innovation into real-world value.

Before we move to Q&A, I’d like to take a moment to welcome Henry, Mr. Haijian He, who recently joined us as Chief Financial Officer. With that, let me turn the call over to Henry to go through the financial results.

Haijian He: Thank you, Robin, and hello, everyone. I’m delighted to join the Baidu team and looking forward to working with all of you. Now let me walk through the details of our second quarter financial results. Total revenues were RMB 22.7 billion, decreasing 4% year-over- year. Revenue from Baidu Core was RMB 26.3 billion, decreasing 2% year-over-year. Baidu Core’s online marketing revenue was RMB 16.2 billion, decreasing 15% year-over-year. Baidu Core’s non-online marketing revenue was RMB 10 billion, up 34% year-over-year, primarily driven by the boost of AI cloud business. Within Baidu Core’s non-online marketing revenue, AI cloud revenue was RMB 6.5 billion, increased by 27% year-over- year. Revenue from iQIYI was RMB 6.6 billion, decreasing 11% year-over-year.

Cost of revenue was RMB 18.4 billion, increasing 12% year-over-year, primarily due to an increase in costs related to AI cloud business and content costs. Operating expenses were RMB 11.1 billion, decreasing 4% year-over-year, primarily due to a decrease in personnel-related expenses, partially offset by the increase in channel spending expenses. Baidu Core’s operating expenses was RMB 9.7 billion, decreasing 5% year-over-year. Baidu Core’s, SG&A expenses were RMB 5 billion, increasing 6% year-over-year. SG&A accounted for 19% of Baidu Core’s revenue in the quarter compared to 18% in the same period of last year. Baidu Core R&D expenses were RMB 4.7 billion, decreasing 14% year-over-year. R&D accounted for 18% of Baidu Core’s revenue in this quarter compared to 20% in the same period of last year.

Operating income was RMB 3.3 billion. Baidu Core’s operating income was RMB 3.3 billion, and Baidu Core’s operating margin was 13%. Non-GAAP operating income was RMB 4.4 billion. Non- GAAP Baidu Core operating income was RMB 4.4 billion, and the non-GAAP Baidu Core operating margin was 17%. Total other income net was RMB 4.9 billion, increasing 531% year-over-year, primarily due to an increase in the fair value gain and a pickup of earnings from long-term investments. partially offset by increase in the net foreign exchange loss arising from exchange rate fluctuation between RMB and the U.S. dollar. Income tax expenses was RMB 881 million compared to RMB 1.1 billion in the same period of last year. Net income attributable to Baidu was RMB 7.3 billion, and the diluted earnings per ADS was RMB 20.35.

Net income attributed to Baidu Core was RMB 7.4 billion, and the net margin for Baidu Core was 28%. Non-GAAP net income attributed to Baidu was RMB 4.8 billion. Non-GAAP diluted earnings per ADS was RMB 13.58. Non-GAAP net income attributed to Baidu Core was RMB 4.8 billion, and non-GAAP net margin for Baidu Core was 18%. As of June 30, 2025, cash, cash equivalents restricted cash and short-term investments were RMB 124.2 billion. And the cash, cash equivalents, research cash and short-term investments, excluding iQIYI, were RMB 119.9 billion. As of June 30, 2025, cash, cash equivalents, short-term investments and the long-term time deposits and held-to-maturity investments for Baidu Core were RMB 229.7 billion. Free cash flow was negative RMB 4.7 billion, and free cash flow, excluding iQIYI was negative RMB 4.6 billion, primarily due to the increase of investment in AI business.

We define net cash position, as total cash, cash equivalents, restricted cash, short-term investments, net long-term time deposits held-to-maturity investments and others, less total loans, convertible senior notes and notes payable. As of June 30, 2025, net cash position for Baidu was RMB 155.1 billion. Baidu Core had approximately 31,000 employees as of June 30, 2025. With that, operator, let’s now open up the call for the questions. Thank you.

Operator: [Operator Instructions] Your first question comes from Alicia Yap, Citigroup.

Q&A Session

Alicia Yap: And also welcome Henry as the new CFO. I have a question on your AI model. with the rapid model iteration, how do you view the current landscape? How do you position ERNIE strategically in the market and its alignment with Baidu broader business strategy? And we also have heard that you are planning to launch ERNIE 5.0, could management share plans for ERNIE in the second half this year and also the key focus area for this next version.

Yanhong Li: Alicia, this is Robin. Let me first give you our take on the current landscape. The pace of model iteration is faster than ever. We see multiple new models launched almost every week and each new generation is stronger than the last. In recent months, we’ve seen models grow more capable, reaching the stage where their deeper logic and greater creativity now enable them to proposed entirely new solutions we’ve never saying before. And I believe this is — this kind of innovative ability is getting stronger. Meanwhile, the foundation model landscape is becoming more diverse and clearly not a one-size-fit-all situation, especially in China, similar to EVs you always have a lot of choices, different models excel at different tasks.

Some are stronger in reasoning, some in coding and some in multimodality. So we will continue to see a market where multiple models coexist at very reasonable prices. And the value creation will happen at the application level more than at the model level. Against this backdrop, ERNIE’s positioning is clear. We take an application-driven approach to innovation. In fact, we’ve taken this approach since the launch of ERNIE — first launch of ERNIE more than 2 years ago. Rather than spreading efforts across every possible direction, we stay focused on the strategically important areas that’s valuable to us. We think we can deliver meaningful impact and sustain our leadership. For example, as we advance AI search transformation, we direct our model capabilities towards generating and selecting multi-model search results.

And our users love it. Our cloud customers also love it. They’re paying for our Search API for the purpose of RAG in their Gen AI applications. Another example is our hyper realistic digital human technology, which now matches and even exceeds real human performance in the live streaming e-commerce scenario. Our model is just better at convincing people to buy. Cloud customers are paying for these capabilities, too. As we move into the second half and beyond, we will continue this acceleration. We’re currently working on the next flagship version of ERNIE with significant improvements across key capabilities and expect to launch it as we are ready. In the meantime, we will continue to roll out iterations and updates on an ongoing basis for our existing models.

We also keep monitoring industry developments to ensure our technology road map captures the most promising market opportunities. Thank you.

Operator: Your next question comes from Alex Yao from JPMorgan. .

Alex C. Yao: And Henry all the best to your new role. So here is my question, how is the AI-powered search upgrade progressing in Q2 and Q3? Could the management share updates — updated metrics on how user behavior is shifting with the new experience, how should we think about the end game of AI search in terms of product format, user reach and lastly, commercial potential.

Rong Luo: Alex, thank you so much for your question. This is Julius. I think Q2, we continue to accelerate transformation. And as Robin has just mentioned, Baidu leads globally in using AI to transfer search and we are maybe were the most aggressive in revolutionized search. And we’re probably the only company that has completely replaced the traditional links with intelligent AI answers that start with the multi-model content. This creates a more efficient, intuitive user experiences and unlike the current AI answers — travel that remains mostly still as a text base. Our focus remains delivering the better user experiences beyond the MAUs and the time spent improvements and the user exposed to AI Search now shows higher UV and retention indicating our next generation, such experience is driving the stronger user satisfaction.

As for the end game of AI Search, I think still an open question, but our path is quite clear. We are fundamentally restructuring Search. First, instead of just indexing or linking to information, we are delivering the intelligent AI generating answers that begin with the relevant multi-model content. Multi modern content now appears more at the very top of AI answers with increasing portion being AI generating as high-quality AIGC content expensed on our platform it directly enrich the search results and broadens what we can offer to the users. And meanwhile, the AI is also empowering the people across our ecosystem from users, content creators, advertisers and service providers to produce the more backed content. This includes enabling those who were not traditional content creators to participate in making our whole ecosystems more vibrant.

And for example, in July, we have launched our MuseSteamer, our proprietary video generation model to facilitate AIGC video creation at scale. And the latest version of MuseSteamer with significant update will be launched tomorrow afternoon. And just stay tuned, we’re moving fast. And second, we are also evolving from fighting information to completing tasks and connecting users with the real-world services. For example, through the MCPs, we have connected search to external capabilities like our British Museum metropolitan museum MCPs that can provide ambitious explanations right in search. For more complicated needs, our agents help understand the user’s intent and connect them with the services providers when the offline services are required.

What we have done today is only the beginning and Search will continue advancing in capabilities and reach over time. In the third place, we’re also working towards the shift from the general results to personalized pages. While AI Search understands the individual context, memories and preference to generate the tailor-made responses, delivering more intelligent and relevant and personalized answers while better matching the users with the tools and services they need. And looking ahead, we will continue to accelerate AI transformation, which in the short term will weigh on our revenue. But over time, we believe the AI search will unlock exciting commercial possibilities and upside is substantial. Thank you for your question, Alex.

Operator: Next question comes from Gary Yu, Morgan Stanley. .

Gary Yu: I have a question regarding the AI cloud revenue. Can management provide a breakdown of the current revenue mix and margin profile. What’s the split between subscription based and project-based revenue? And how do you see them evolving in the coming quarters? And also what’s the margin profile looking like in the near term and over the long term?

Dou Shen: Thank you, Gary. This is Dou. In Q2, AI cloud revenue grew 27% year-over-year to RMB 6.5 billion. For the first half of 2025 AI cloud revenue increased 34% year-over-year, accelerating from the low teens growth we saw in the first half of 2024. Enterprise Cloud has consistently outgrown our overall AI cloud business and remains the main growth driver. Then within the Enterprise Cloud, subscription-based revenue accounts for more than half of the total and continued growing steadily in Q2. The growth was driven by strong momentum in subscription-based AI infrastructure, which grew over 50% year-over-year. We are seeing a good traction with both top-tier and mid-tier customers. Our mid-tier customers, in particular, delivered notable revenue growth as they continue expanding with this.

reflecting our broadening customer base. The other part of the enterprise cloud is project-based revenue. Project-based revenue is typically linked to customer deployments and will inevitably fluctuate from quarter- to-quarter based on contract timing and project schedules. We are currently conducting a careful review of our project portfolio and aim to gradually reduce the propulsion of project-based revenue for greater revenue stability. Turning to Personal Cloud, which is a smaller part of our overall AI cloud business. Over the recent quarters, we’ve integrated Baidu Drive with Wenku and launched multiple new AI features. Recently, we opened up select AI features for free to encourage wider adoption. While this may involve some near-term trade-offs, we believe it helps deepen user engagement and positions us to benefit from a broader AI adoption.

On profitability, we achieved year-over-year growth in non-GAAP operating profit and maintained a healthy margin driven by a healthier revenue mix duty towards higher value offerings, while margins can move around from quarter-to-quarter due to dynamic market environments, we see clear potential for the future improvement over the long run as we scale and optimize our mix. Thank you Gary.

Operator: Our next question comes from Lincoln Kong from Goldman Sachs.

Lincoln Kong: So my question is about the Search. So actually, can management share more color on the reason AI search monetization testing because the following your earlier comments on AI search opening up new monetization opportunity. Could you elaborate on that? And how are all pricing format and business model evolving? What will be the margin look like?

Rong Luo: Thank you Lincoln, the master question is curious. I mentioned about the monetization opportunities earlier, and let me elaborate over here. And from a product perspective, while our AI transformation already covers a large portion of such results, we are still in the early stage with substantial room for improvement. We aim to further increase the penetration of multimodal content in such results and continue building and enriching our AI native ecosystem through MCP agents and on the foundation, enable the deeper, broader or higher quality connections to the real-world services. As the AI transformation on once and the user experiences improves, monetization opportunities will naturally follow. And also, the AI Search brings the native apps that feels intuitive and integrate, enhancing rather than interrupting the user experiences.

So the vast majority of keywords that were previously very difficult to monetize now can be monetized under AI Search, which should be significantly expand our advertisement inventory over time. While initially, we will be very conservative with monetization to ensure we get the user experience right and but the long-term upside is much higher. And during our AI transformation, we are moving from simply generating sales leads to enabling the real-world service delivery. This is a shift made possible by new AI native commercial products such as agents or digital humans. These innovative products allow us to better capture and serve the user needs through interactive conversations while connecting users with service providers in verticals like health care, travel and education, where our agents and digital humans have already proven monetization capabilities.

And over the long term, the ability to fulfill the user needs end-to-end position us well to drive a gradual transition from CPC to CPS, which offers a much higher ceiling for monetization. And in Q2, we have already begun the early testing of the AI Search monetization. While it’s still in early days, we have seen the very encouraging signals, and we believe this trend will continue over time. That said, we always put user experiences first. So we chose very deliberate approach to AI Search monetization and large-scale monetization has not started yet. And at the same time, we have been aggressively accelerating the AI search transformation, including changing those queries with the highest monetization capabilities. So in the near term, we do expect the revenue and margin will remain under significant pressure.

But long term, we believe this positions us well for stronger growth.

Operator: Our next question comes from the line of Miranda Zhuang with Bank of America Securities.

Xiaomeng Zhuang: My question is about cloud and GPU. So how should we assess the sustainability of the AI-driver cloud demand especially against the backdrop of a soft economy and intensifying market competition and also with the easing of the H20 chip restriction, has management seen any meaningful improvement in supply? How do you think about the chip constraint? Will it remain as a limiting factor for growth going forward?

Dou Shen: Miranda, I would do questions. Actually, we were seeing strong and growing demand for AI driven cloud services as the China’s cloud market continues its shift towards AI centric computing. The adoption of Gen AI and foundation models is accelerating, and AI has become a strategic focus for more and more companies. From what we’ve observed, demand is picking up across a wide range of sectors, not only from early adopters like [ Titan ] Internet companies, but also from a broader side of the industries like utilities, financial services and the public sector, where interest in AI- driven cloud solution is rising quickly. Meanwhile, technological advances are filling strong new demand from emerging sectors such as embodied AI.

We are effectively capturing new opportunities and working with leading players in this field, including 20 of China’s promising embodied AI start-ups and 4 of which are China’s top humanoid robot companies. The reason we are able to capture opportunities so quickly is our unique competitive positioning. What differentiates us is our ability to deliver highly cost-effective end-to-end AI cloud products and solutions, thanks to our full stack AI capabilities. Taking our AI infra as an example, we keep improving utilization and efficiency through our industry-leading resource management capabilities. By dynamically allocating computing resources, we can better match workloads with the suitable resources and manage demand fluctuations, delivering better performance at lower cost.

As a result, we can provide cost-efficient, reliable and scalable cloud services that makes it really easy for companies to adopt AI with minimal effort and scale it into real business impact. On your question about chips, our focus remains on building a flexible AI architecture that maximize GPU utilization and supports a variety of chips, including domestic chips. This enables us to better serve customers as the supply environment evolves. Looking ahead, we believe that a self-sufficient supply chain, together with increasingly major homegrown software stacks will form a solid foundation for sustainable innovation in China’s AI ecosystem. And clearly, Baidu is well positioned to lead the transition. Thank you.

Operator: Next question comes from Wei Xiong, UBS.

Wei Xiong: Given the near-term headwinds on ad revenue, and continued investment in AI. I wonder what are the plans for cost optimization and efficiency improvement that can help protect margins? How should we think about the margin trend in 2026 and beyond.

Haijian He: Thank you. This is Henry. First of all, on the AI investment, we remain committed to investing in AI and have made substantial investments throughout this year particularly in AI transformation of Search. As Julius mentioned earlier, our core legacy product search is ongoing a radical transformation. Over the past several quarters, we have ramped up investments to accelerate this transformation, which we believe is critical to drive long-term value. However, since the AI search monetization is still in very early stages and has yet to scale, our revenue and margins are on the considerable pressure in the near term with Q3 expected to be especially challenging. To help pushing the near-term impact, we will actively drive internal efficiency gains.

This includes strengthening resource coordination efforts across different business groups and improving overall resource utilization efficiency. But also on the other hand, while we are remaining committed to long-term AI investment, we’ll be very prudent in managing the pace to avoid future deterioration of fluctuation in margins. Looking further ahead, we see potential for margin improvement as our core advertising business recovers and stabilized and our non-advertising business both expand their revenue share and improving their own profitability. We believe our strategic direction and the disciplined execution should support a gradual recovery in profitability over time. Obviously, on the outlook front, I think before or around end of this year, we expect to have a greater visibility into next year.

And at that time, we will have — we will provide a clear outlook beyond the current quarters for the long term. In parallel, we are carefully assessing different approaches to present and to unlock the hidden and unstated value of our assets. By doing so, we aim to strengthen our portfolio, create significant long-term value for shareholders, but also support sustainable growth over the long term of business. Thank you.

Operator: The next question comes from Thomas Chong, Jefferies.

Thomas Chong: My question is about the global autonomous driving landscape. We see it becomes increasingly competitive — how does Apollo Go assess its long-term differentiation against peers? And how do the recent Uber and its partnership fits into your global expansion strategy? And what is the road map for achieving sustainable profitability.

Yanhong Li: Yes. I think autonomous driving is one of the most exciting frontiers where AI is transforming the physical world. and success in this field requires cutting-edge technology, massive sustained investment and disciplined execution over many years to achieve commercial operations at scale. One of the earliest entrants, we have built an unparalleled foundation across all these areas and become an undisputed global leader in this field. With our business model validated, our current focus is on running real-world operations at scale. And we have established global leadership in both left-hand and the right-hand drive robotaxi market. In the left-hand drive market, we were the first to achieve UE breakeven and all of our current operations in China, in Mainland China are fully driverless.

Globally, we are among the very few capable of scaled fully driverless and commercial operations in a single complex, large population area. And in the right-hand drive market, we lead the industry globally. In Hong Kong, we’ve rapidly expanded our operating of testing and advanced into increasing the complex urban scenarios following regulatory approval. Our technology stack and operational expertise are highly transferable across geographies, allowing us to adapt efficiently to new markets and regulatory environment. We also built a major advantage with RT6, the world’s first and only production vehicle designed especially for level 4 autonomous driving from day one. Unlike some retrofitted cars, RT6 is a purpose built from the ground up is a focus on safety system integration and cost efficiency.

It has the lowest unit cost globally for Level 4 and is already running on our commercial operations at scale, giving us a big edge for broader rollouts with this strength, we are confident about expanding to more cities worldwide, especially those with higher ride fares. Here’s the picture. We have the lowest cost level 4 vehicle and most efficient operation. We first achieved UE breakeven in Wuhan where taxi fares over 30% cheaper than the Tier 1 cities in China and far below many overseas markets. Yet we still managed to prove our business model there. Such operational excellence and cost efficiency is unmatched globally. For us, expanding overseas means going from low fare markets to high fare markets. Often with fares several times higher.

Our huge cost advantage can deliver much stronger unit economics in most major cities worldwide. To accelerate our global expansion, we are also taking a proactive approach to global partnerships. As we mentioned in our prepared remarks, we announced a partnership with Uber in July and followed by Lyft in August. Our partnerships with this world’s leading mobility platforms will help us enter and scale more quickly into global markets like Middle East, like Asia, like Europe. Looking ahead, we anticipate accelerating growth in ride volumes with our global operational fleet size multiplying. With that momentum, we are confident that Apollo Go will continue to lead the market and stay at the forefront of autonomous driving worldwide. Thank you.

Operator: That does conclude our conference for today. Thank you for participating. You may now disconnect.