Good morning and good evening ladies and gentlemen. Thank you for standing by and welcome to the WeRide's second quarter and third half 2026 earnings conference call. Please note that today's event is being recorded. At this time all participants are in listen-only mode. For today's call, management will use English as the main language. A third party interpreter will provide simultaneous Chinese interpretation. The company will be hosting a question and answer session after the management's prepared remarks. If you wish to listen to the management's original statements or ask a question during the question and answer session, please make sure you are dialed in to the English language line. Please note that Chinese interpretation is for the convenience purposes only. In the case of any discrepancy, management's statements in their original language will prevail. Joining us today are WeRide's founder, chairman and CEO, Dr. Tony Han, and CFO and head of international, Ms. Jennifer Lee. Before we continue, I would like to refer you to the safe harbor statement in the company's earnings press release, which also applies to this call as today's call will include forward-looking statements, including WeRide's strategies and future plans. These forward-looking statements are made under the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995. Forward-looking statements involve inherent risks and uncertainties. The company's actual results could differ materially from those stated or implied by these forward-looking statements as a result of various important factors and please refer to the risk The company does not assume any obligation to update any forward-looking statements except as required under applicable law. Please note that all numbers stated in the management's prepared remarks are in RMB terms and will be discussed non-IFIs The company's unaudited financial and operating results were released earlier today via Newswire and can be found on the company's IR website. With that, we will now begin with the company's video presentation.

In the physical AI era, autonomous driving is evolving from single vehicle intelligence toward an intelligent flywheel connecting data, models, vehicles, and operations. As the global leader in autonomous driving, WeRide continues to advance physical AI toward its next stage of commercialization. In China, we continue to strengthen our operational capabilities. With Beijing and Guangzhou as our core operating hubs, our fully driverless robot taxi coverage continues to expand. Through deployment in complex urban environments and real-world operating scenarios, we continue to enhance system robustness, safety, and operational efficiency. To date, WeRide's autonomous driving footprint has expanded to over 60 cities across 13 countries worldwide. Internationally, WeRide is accelerating expansion across Europe and the Middle East through our asset-light model. In the Middle East, we have achieved fully driverless robot taxi operations in Abu Dhabi and Dubai, while continuing to expand our operations in Riyadh. This proven robotaxi commercialization model is now expanding from the Middle East to Europe. Following our rollout in Slovakia, WeRide is rapidly scaling across Europe. In June, we announced new robotaxi deployments in Madrid and Zurich. In August, we announced plans to deploy Denmark's first autonomous shared mobility services. Within two months, we advanced public commercial operations across three countries, with Denmark representing our sixth European market. At the same time, we are accelerating expansion into right-hand drive markets. In April, we partner with Grab to launch Singapore's first public autonomous driving mobility service. In June, we partnered with Geely, Verizon, and Quincheng Bus to advance right-hand drive robo-taxi commercialization with Hong Kong as the starting point. This marks a major step toward WeRide's robo-taxi mass production and operational capabilities across both left-hand drive and right-hand drive markets. Beyond RoboTaxi, our RoboBus business continues to advance commercialization in Europe with operational progress across France, Belgium, Spain, Switzerland, and other markets. Our L2++ and L3 solutions are scaling rapidly. To date, our single-stage end-to-end platform, RRD 3.0, has won mass production commitments across more than 30 vehicle models, with active road testing and market validation underway in key global markets including Germany, France, and Japan. Behind these commercial achievements is our continuously evolving physical AI technology foundation. We introduce the We Ride Wit, the physical AI cognitive foundation model, pioneering the concept of the minimum physical fact unit and building a new AI understanding framework centered on physical facts. Combined with the Genesis World Model, it connects high-quality real-world driving data, model training, and simulation validation to empower L2++ and L4, accelerating large-scale autonomous driving deployment. Operations validate technology. Technology empowers products. Products drive commercialization. WeRide continues to advance along this intelligent flywheel path, accelerating the global commercialization of autonomous driving.

Now, I would like to pass the floor to the company's founder, chairman and CEO, Dr. Tony Han. Please go ahead, sir.

Hello, everyone. Thanks for joining us today. We had a great second quarter this year. To begin, I'd like to highlight three key factors that define our strong performance in the second quarter and emphasize the exciting progress we are making today. That is, overseas acceleration, asset life scaling, and a clear path to self-sustaining cash generation. We made strong progress across all three areas during the quarter. positioned the company for the next phase of growth. Turning to our financial performance, total revenue delivered robust growth, nearly doubling year-over-year and more than doubling quarter-over-quarter, with growth of 103%. Overseas revenue increased 164% year-over-year and approximately 170% quarter-over-quarter. Meanwhile, Gross margins reached a record high of 38%, representing an improvement of approximately 10 percentage points compared with the second quarter of last year. Benefiting from continued improvements in operating efficiency, EBITDA also improved, with the loss narrowing by 8% compared with the second quarter of 2025. Our operational metrics Our L4 fleet reached approximately 3,400 units, up 22% since Erlin's release in April. Within that, our robot taxi fleet grew by 500 units to more than 1,800 vehicles, making a 40% growth over the same period. Furthermore, our one-stage end-to-end L2++-L3 solution has progressed from securing design reams to full-scale mass production. Revenue from this business surged nearly 2,600% year-over-year and increased 219% quarter-over-quarter in second quarter. During the quarter, we delivered approximately 30,000 units of our L2++ solutions. making the beginning of a scaled high-growth commercialization for our L2++-L3 business. Across the industry, we believe we are uniquely positioned with both mature technology stacks and large-scale commercial deployment for both product lines. The multi-sensor fusion L4 autonomous driving solution and the proprietary one-stage end-to-end L2++-L3 solution for mass production. Turning to our strategy, this quarter we segmented our business into three areas, L4, L2-L3 ADAS, and AI infrastructure to provide greater clarity into our long-term strategic planning. In second quarter, we further advanced our strategy as physical AI company built on proprietary infrastructure and foundation models. with autonomous driving representing the most commercially advanced application of physical AI. Our physical AI infrastructure enables us to distill the capabilities of large foundation models into efficient, lightweight on-board models. The key lies in our ability to transfer the underlying knowledge and the representations learned by large-scale models, not merely their outputs, into smaller models. while preserving the intelligence, generalization, and decision-making capabilities required for real-world autonomous driving. This enables us to bring increasingly powerful AI capabilities to cost-efficient onboard systems, supporting both the scaling of our L4 business and the continuous evolution of our WRD 3.0, i.e. our L2++-L3 solution. More importantly, This creates a powerful technology flywheel. Our real-world L4 operations generate high-value data that continuously improves safety, robustness, and generalization, while our growing L2++-L3 feeds generate additional role data, accelerating L4 model development and the expanding coverage of long-tail scenarios. There are two separate businesses. These are not two separate businesses. They are two reinforcing layers of one physical AI platform where every vehicle deployed and every mile driven makes our technology smarter, safer, and more capable. Next, I will work through our specific progress this quarter across technology development and commercial deployment. Starting with our L4 business, specifically Robotaxi. Our core themes are asset-light overseas acceleration and strengthening regulatory modes. Our overseas operations are built upon an asset-light model. We do not own operating vehicle assets. Vehicle serves as a hardware entry point for market expansion while we work with local partners to deploy and operate the business. This model allows us to scale out to scale our footprint with significantly lower capital requirements and greater operational flexibility. Based on optimal utilization under normalized driverless operations, we estimate the steady-state annualized technology service revenue per robotaxi could exceed $50,000. As our fleet scales, we expect increasing benefits from the data network effects cross-market learning and algorithm generalization which should further improve vehicle level economics and create meaningful operation leverage. I would also like to classify how we define unit economics. Our overseas UE is not based on a fleet ownership plus ride-hailing platform model. Their revenue is derived from fare charging at the gross level. Instead, our economics are based on a licensed virtual driver technology model. We provide regulated, locally verified, and recognized autonomous driving capability and charge our recurring fee from autonomous driving technology services and mileage-based fees. Because our positioning and our business model differ fundamentally, the same term UE carries very different operational and financial implications from those in traditional ride-hailing platforms. Backed by partners like Grab, Uber, Green Mobility, SBB, and etc., we are replicating this proven satellite operational model across Mideast, Europe, and Southeast Asia. This marks that our overseas expansion is now entering a phase of large-scale commercialization. To put into more details, in the second quarter, we announced new robotaxi commercial partnerships in Madrid, Spain, and Zurich, Switzerland, and Copenhagen, Denmark. In the Middle East, we continue to expand full driverless robotaxi operations in Abu Dhabi and Dubai this quarter, now covering over 70% of the core urban areas. In Riad, our robotaxi operation zone has expanded to the airport, terminals, and surrounding central business districts. By the end of 2026, we will be fully entering a phase of meaningful growth supported by secure licenses, expanding fleets, recurring orders, solid revenue, and profitability in overseas markets. This will demonstrate the successful for the execution of our oversea acceleration and asset-light expansion strategies. For the domestic markets, we continue to strengthen our operational capabilities and expand our driverless operation zones in Guangzhou to key areas of Tianhe District, including Zhujian New Town and Haizhou District, including the Canton Fair Complex. This represents a nearly three-fold expansion in our ODD compared to the end of 2026. More importantly, our operating efficiency continued to improve meaningfully during the quarter. Average daily rides per vehicle reached 21, up by 24% quarter over quarter. While peak daily rides completed per vehicle climbed to 28, As a reading-healing platform with self-operated Robotext fleet, we recorded nearly 35% quarter-over-quarter growth in registered users in China. This simultaneous expansion in scale, utilization, and user base drove a 140% sequential surge in our write-healing revenue. further demonstrating the scalability and strengthening the profitability of our operations. Looking ahead, as China's regulatory framework for autonomous driving continues to mature, we expect to further expand our robot taxi operations into more cities in near term. At the same time, we will continue to build Guangzhou as our domestic benchmark with the goal of integrating driverless robotaxi into public transportation system at scale. Together, these initiatives will provide a strong foundation for the next phase of domestic commercialization. Beyond this, I would like to take a step back and discuss our regulatory modes. The operational licenses we have secured overseas are by no means simple administrative approvals. They are a combination of years of technology adaptation, ecosystem integration, and rigorous safety validation. This creates a core competitive mode that puts us two to three years ahead of the market. This mode is built on three core pillars. First, the technology localization and the regulatory engagement. We adapt our technology to local traffic laws, Road Conditions and Driving Behaviors, while working closely with regulators throughout the process. Second, ecosystem and infrastructure integration. We established deep technical integration with local operators and service providers, supported by strong on-the-ground execution. Third, rigorous field validation and safety performance. Our fleet continuously accumulate localized real-world data, while safety framework and track record provide the foundation for earning regulatory trust and securing commercial licenses. Importantly, as regulatory frameworks become increasingly aligned across markets, our experience and validation in one jurisdiction can help accelerate approvals in the others. These reduce margin compliance costs, avoid redundant work, and create increasing operating leverage, allowing us to scale our asset-light autonomous driving business globally with greater speed and capital efficiency. As a growing industry, consensus on L4 core barriers was also shared by the same mobility platform during its Q2 investor presentation. Technical competitiveness depends not on total driving miles, but on the acquisition cost of rare scenarios, scenario diversity, and practical data quality. Besides, generic large foundation models cannot satisfy autonomous driving needs. AV systems rely on exclusive vehicle hardware and strict regulatory oversight, which demands customized models matching hardware specifications and compliance requirements. Backed by our robust, appropriate end-to-end data toolchain, diversified dataset accumulated from long-term cross-border L4 operations and outstanding self-developed algorithms, we keep upgrading vehicle engineering safety. Our field-proven safety performance earns sustained trust from global regulators, accelerates regional expansion, and builds an exclusive core advantage for global layout. Then turning to our L2++ slash L3 business, three themes define our progress. Industry-leading technology, rapid commercialization at scale, and a path toward self-sustaining cash generation. Leveraging on our leading technology advantage in L2++-L3 algorithms, we have secured six consecutive championships at China's intelligent driving competition, reinforcing our leadership position in intelligent driving technology. Commercially, we are entering a clear acceleration phase with multiple OEM mass production programs advancing steadily. Recently, we launched an L3 autonomous driving POC program with Mercedes-Benz, making an important validation of our technology by leading global OEM and further demonstrating strong industrial recognition of our technological capabilities. As of June 30, Cumulative delivery of vehicles equipped with our one-stage end-to-end L2++-L3 solution has exceeded 30,000 units during the reporting period. Looking ahead, we expect the number of vehicles powered by our solution to exceed 100,000 by year-end and surpass half million units in cumulative deliveries next year. positioning us for significant scale up in our L2++ ADAS business. Finally, I will provide a brief update on our AI infrastructure. In this quarter, we officially launched the WIT model, which is a physical fact foundation large model, completing a full capability loop spanning data comprehension are all experts in data generation and end-to-end technical stack. It delivers deep synergy with our Genesys world model. The WIT model extracts and verifies physical facts from raw test data to build a cognitive foundation for machines to perceive and understand the real world. Leveraging validated physical facts, Genesys reconstructs diverse extreme operating conditions and the long tail scenarios via simulation. The two models work in tandem to perform a closed loop covering data generation, simulation, and algorithm iteration, driving continuous upgrades to autonomous driving technology. Currently, it underpins our two core business lines of L4 autonomous driving and mass produced L2++ slash L3. In closing, in the second quarter, we delivered meaningful milestones and strong results across the business, which lead us to return to three key themes I highlighted at the beginning of today's call. Overseas acceleration, asset light expansion, and self-sustaining cash generation. Looking ahead, our focus remains clear. On the L4 side, In China, we will continue to expand our deep market strategy building benchmark operations that are fully integrated into urban transportation systems before expanding in a disciplined and repeatable manner across major cities nationwide. On the L2++-L3 side, our top priority is straightforward with more OEM partnerships, increase our market share with key OEMs, and accelerate deployments at scale. growth installed vehicles in our ultimate objective. I'm sorry, growth is the key. We will invest where we see clear conviction and a meaningful scale potential rather than pursue growth for growth sake. At the same time, we will remain focused on both long-term cash flow generation and profitability. rather than expand simply for the sake of expansion. Here, beyond the numbers, I would like to thank my team. This is a team that embraces hard problems, confronts reality head-on, and remain relentlessly focused on execution. That culture of intellectual honesty and operational excellence is what enabled us to consistently turn vision into products, products into services, and services into large-scale commercial value, even in uncertain environments. Just as our physical AI foundation model, the WIT, World Intelligence Toward Truth, reminds us true intelligence must be grounded in observable, verifiable facts about the physical world. The same holds our business. What ultimately matters is not what we claim, but what we continue to deliver in the real world. Narratives may change, technologies may evolve, and the market cycles may come and go, but facts endure. Real-world performance endures, and a proven track record remains the most powerful language of all. Next, I will turn the call over to our CFO, Jennifer, who will work through will give you our second quarter 2026 financial performance in detail.

Thank you, Tony. Hello, everyone. Let me start with a key message from the quarter. Q2 marks an important inflection point for V-Ride, with strong revenue growth, continued growth margin expansion, and increasing operating leverage across the businesses. Importantly, this growth was driven by three areas where we believe we can support a more sustainable financial model over time. the acceleration of our overseas business, the scaling of our asset-light L4 model, and the rapid commercialization of our L2++ L3 business. We're increasingly seeing the benefit of the strategy in our financial results, particularly revenue growth, growth margin, and capital efficiency. In Q2, WeRide generated RMB 232 million of revenue, up 82% year-over-year, and 103% quarter over quarter. Importantly, growth is bordering across both our businesses and geographies. Our L4 revenue reached RMB 125 million, up 47% year over year, primarily driven by robo taxi. Our focus remain on scaling the core L4 business, particularly robo taxi. Meanwhile, some of our other L4 businesses have natural seasonal cycle, with commercial negotiation typically complete in the first half and revenue recognized as deployment take place in the second half of the year. As those projects move into deployment, we expect stronger contribution from our broader L4 portfolio in the second half of this year. Our L2++ L3 business continue to accelerate rapidly with revenue increasing approximately 26 times year over year. and 219 times quarter-over-quarter. This reflects an important transition from project development into mass production and scaled vehicle deployment. As more OEM programs move towards mass production, we expect L2++ L3 to become an increasingly important driver of our overall revenue growth. Oversea market account for nearly 40% of group revenue and it's becoming an increase in important growth driver as well. Oversea revenue increase 164% year over year and approximately 170% quarter over quarter. More importantly, the economic of our overseas business are increasingly attractive. Our asset-light model allows us to scale through local partners and operating ecosystems without requiring a proportional increase in our own balance sheet investment. This gives us three important advantages. Faster geographic expansion, improving margin as operation scales, and lower incremental capital requirements. We believe this model is an important foundation for our long-term path towards self-sustained growth. turning to profitability at the growth profit level. Growth profit increased 143% year over year to RMB 87 million, while growth margin expanded 9.4 percentage points to 37.5% compared to 28.1% in the same quarter last year. The improvement was driven by continuous scaling of our high margin asset light over the L4 business, rapid growth in the L2++, and an overall shift towards higher value AI service oriented revenue. As this mix continues to improve, we believe gross profit can grow even faster than the revenue over time. Total operating expense were RMB 533 million in Q2, slightly up 9.2% year over year, slightly slower than the revenue growth. This is an early indication that operating leverage is taking hold. R&D expense increased 36% year over year to RMB 434 million, primarily reflecting our additional investments in AI infrastructure and foundation models. At the same time, a much slower growth in the total operating expense demonstrate that we are beginning to achieve greater efficiency as business scales. G&A declined significantly to RMB 69 million, mainly due to lower share based compensation and professional fee. while selling expense only increased to 29 million as we expand our commercial activities. Overall, we are seeing increasing operating leverage while operating expense growing well below the revenue. Putting all this together, our net loss narrowed 1% year over year to RMB 401 million in Q2, while EBITDA loss narrowed 8.1% year over year to RMB 335 million. These results reflect the early benefit of our SLI model and increasing operating leverage, particularly as we scale our overseas business and reinforce our path towards sustained cash generation. Finally, as of June 30th, we have approximately RMB 5.4 billion in cash and other liquid financial resources. This provides us a strong financial foundation for continued expansion. Let me close with four key takeaways first. Revenue growth is accelerating and becoming increasingly diversified. Second, our revenue mix is shifting towards higher-margin, physical AI service-oriented business. Third, operating leverage is beginning to emerge, with expense growing significantly slower than revenue. And fourth, our strong balance sheet and asset-light model provide a capital-efficient foundation for continued expansion. We believe Q2 demonstrates an early financial benefit of the model and we have been building. Global expansion, asset-light deployment, higher physical AI service revenue, and increasing operating leverage. Looking ahead, our focus is to convert our commercial pipeline into scale deployment, continue improving margin, and progressively translating revenue growth into stronger cash generation. We believe these are the key building blocks for durable capital efficient growth, a leading position in global autonomous driving, and a sustained path to profitability. With that operator, we are now ready to take Thank you.

Thank you. We will now begin the question and answer session. As a reminder, we only accept questions in the English language line. To ask a question, please dial in into the English line and then press star 11 on your cell phone touchstone keypad. If you have any follow-up questions, please run to the queue. Thank you. And now we're going to take our first question. Just give us a moment. And the question comes from Jeff Chang from CT. Your line is open. Please ask your question.

Hi, Tony, Jennifer. Congratulations with the great result. And my first question is that we note that we ride currently has a diversified business portfolio spanning L4, L2++, L3 as well as the AI infrastructure. And the question for me is how does management prioritize resources allocation across different business and regions? And what are your goals for the second half this year? Thank you.

Okay. Thanks for the question. So first, let me start with a detailed, a little bit explanation about our financial model. As you have noticed, like these days, I think almost every industry has their capability boost. Like back to five years ago, without large language model and AI programs, and I don't think any company in this world can do L4 and L2++, L3 and AI infrastructure simultaneously but recently we noticed like with our boost in the AI model especially our genesis and the width and we found suddenly like we can build a lot of technology into data synergies By the way, I want to explain a little bit about the name of the WIT. This model, WITT, we announced in the 2026 AI World Conference. It is a solution to a famous German philosopher, I think the greatest philosopher, Ludwig Wittgenstein. His meaning, his famous words like, the limit of my language is the limit of my world. is exactly what we just learned. We can segment every video into what we call so-called minimal fact units. And we basically can defect every video and analyze every video into very atomic facts. And combined with our genesis model, we finally find out we can generate all kinds of data as we desired. Just like in the matrix, one day Leo just noticed he see the nature of the of the world. So we have this kind of feeling. And so, drastically, we reduce the resource we need. And, you know, we can just with one investment, we can do three things. That is L4 and the L2++ slash L3 AS and AI infra. So we build up our infra very, very strongly. And and generate the data from L4 and also generate data from ADAS and make these two things complement each other, build up what we call the double data flywheel. Actually, this flywheel is why we are the only company globally that has achieved driverless vehicle operation at large scale. At the same time, we have many car OEMs adopt our ADAS system. For the goal of our second quarter, we have several aspects one is like we want to toward accumulated half million installation goal to work and we want to really push forward to have a lot of cloud OEMs adopting our ADA system and hopefully you know in the fourth quarter Tesla FSD may enter China and we want to do a directly head-to-head comparison against FSD because I'm a are heavily FSD users in California. And I drove our own AIDA system, our own cars based on WeRide AIDA system, WRD 3.0. I think these two things are comparable. So I want to see more car OEMs adopt AIDA system. And meanwhile, we'll continue to expand our robot taxi fleet. and 30 for our AI infrastructure. We want more companies in the robotic industry, humanized robot industry to adopt our infrastructure. That's the goal. Here I conclude my answer.

Thank you. Thank you. No more questions. Thank you. Thank you.

Thank you. Now we're going to take our next question. And the question comes from Tim Hsiao from Morgan Stanley. Your line is open. Please ask your question.

Hi, this is Tim from Morgan Stanley. Thanks for taking my question. First of all, congratulations on the robust top-line growth and the global expansion during the quarter. Just a quick question about the overseas business. I think on the call, The management has highlighted accelerating overseas expansion and large-scale commercialization. So just wondering, could you share more detail? How should we view your overseas strategy? In the meantime, can it be replicated across different regions? That's my question. Thank you.

Thank you, Tim. So yeah, like we just mentioned, oversea market is an important co-driver engine for us. And it's already contributed approximately for almost 40% of the group revenue. And we do believe there is significant room to run. And the structure case is very compelling. Those markets we're entering into, they're all facing acute labor shortage and rising labor costs. which creates a strong natural demand for autonomous mobility. So if we can, let me give you a sense of the pace. So for the Q2 in the past quarter, we launched three new robo-taxi deployment in Spain and in Switzerland and in Denmark. And in the Middle East, our robo-taxi fleet has roughly doubled to around 400 vehicles since last quarter. So if you recall from the Q1 like earnings, so at that time we have like around 200 and even like even given the considering the recent geopolitical tension in the region and we have doubled the fleet in the quarter. So the momentum is real and it's accelerating. So and also on the rapid capability. So this is where we think our model generally differentiated. So we operate overseas. We don't own any of the vehicles in operation. So what we do is we handle the localized tax adaptation and the regulatory compliance. Then we license our physical AI driver to local partners. So we capture the recurring technological service revenue, especially as our operation scales. So this can lead us to let us expand very quickly without having heavy capital. and also we can maintain a good margin and good cash flow. And what's more important if we're looking at on the unit economics, the annualized recurring revenue per vehicle exceeds 40 to 50,000 US dollars. And it also has many full upside as density builds up in each city. So for us, our primary goal is just to increase the fleet size in cities where we already operate. We're very disciplined about where we go next. Usually, we pick the market with proven commercial potential and a reasonable regulatory barrier to entry. And the playbook is well established. Everywhere we go, we secure the permits. We adapt the technology locally. We set up a benchmark project in the region and a flagship project in the region. And then we replicate at a lower marginal cost. So we generally believe this is going to be repeatable at scale, and today we have active L4 operations across 12 countries, all well on track. We are confident in the model and in our pipeline, and we look forward in serving passengers in more markets soon. Thank you.

Great. Thank you very much for sharing all these details. It's really helpful. That's all my questions. Thank you.

Thank you, Tim.

Thank you. Now we're going to take our next question. And the question comes to the line of Paul Gong from UBS. Your line is open. Please ask your question.

Thanks, Tony, Jennifer. I have two questions. The first question is regarding the ADA. Can you please update the latest progress and future plan for your military class and military visitors? And given the relative small size of the U.S. team on this front, what is your competitive advantage in this highly Thank you so much for this

There are two important questions. Let me answer them one by one. Okay. The first question is about our latest progress and plan for our L2++ slash L3 ADA system. So to make it short, I'll just use the ADA to mean our business. So including both L2++ and L3 system. And also the question is about our currently competitive edge. So first of all, I think I have to say the competition in ADA system in China and also globally is quite intensive. And now everybody is trying to compare their ADA system to the FSD version 14. And according to our internal evaluation, I think we are currently definitely in a I'm not sure whether you have noticed or not. Just last week, I did a live stream with our ADAS experience in the Pearl Harbor Newtown, which is the central CBD area in Guangzhou. And I drove the N60 based on our WRD 3.0 ADAS system. At the same time, I do the live stream answering the questions from all the audience from my live stream room. And I do this live stream for two hours and just driving rush hour in Guangzhou without any intervention. Okay, the video is online, you can check it. I think, according to my best knowledge, this is the first time a founder of an ADAS company or autonomous driving company do a live stream in Russia, our first-tier city, without any intervention and answering questions. That shows the breakthrough of our technology. And in terms of the installation units, our revenue grows by 2,600%, that is 26 times year-over-year, and 220% quarter-over-quarter. and we have already in a very short time, we have already had like 30,000 units installed in a quarter. But our goal this year is to get 100,000 units installed. And next year, accumulatively, we want to get to half a million. And this is by far the fastest speed I have ever noticed in the ADAS growth in terms of the installation unit. And this is actually why can we do that thank you for your high praise like we are doing with a very relatively small team the key the secret sauce is our two important large language model genesis model and which model and i do believe as you guys already noticed with ai people sometimes call people can form a one-person company and with a very with our very good ai infrastructure and the foundation model we can actually built the best ADA solution in China and in the world with a team of 200 or 300 people. That's the power of AI. So that is what I want to mention about our current progress. The second question, thank you, it's an outstanding question. That is, we have seen many OEMs which, you know, Carl Yams or some company with Ada Solutions claim, like, you know, very high tone that we are entering robo taxi sector and we will do great things, lots of PR. So my answer to this kind of claim, this goal is actually, first of all, we welcome this kind of competition. and because this competition will make us stronger we ride as the leader and the first mover in robot taxi industry uh we expand globally and we know we also have a very strong background in ADAS we know the big difference we know we know the requirements for redundancy for the reliability uh you know there is a one thousand times difference so I just want to, as I mentioned at the beginning of this year, I proposed a qualification threshold for robo-taxi. That is, a company needs to operate at least for half a year with a fleet of 100 private robo-taxi without any significant accident. Without severe accidents, they can claim themselves a robo-taxi company. Otherwise, it's just a claim, you know, people make claim every day. And I don't need to respond to this kind of claim. But I just want to mention, like, there's a big difference between ADA system and L4 Robotaxi. And people will say, okay, with this progress in large language model, we can solve the problems like previously takes like 10 years of your efforts, we can solve probably half year. Now I make another claim that is hallucination in digital AI may be entertaining, but it is fatal in physical AI. So in physical AI, our society, our public growth cannot stand a fatal accident if we can avoid it. But in digital world, you just restart computer or just do it again. but in the real world, a life lost is lost. You can never get it back. So with this kind of philosophy, with this kind of priority on safety, we know that we have very, very strong competitive edge. We have very deep moat for our L4 business. Okay, here are my answers to your two great questions. Thank you.

Thank you very much. That's very clear. Thank you.

Thank you. Now we're going to take our next question. And the question comes from Tianyu Lu from City Securities. Your line is open. Please ask your question.

Hi, Tonya and Jennifer. This is Tianyu from City Securities. I have only one question. How about management will the overall trajectory of future operating expenses, particularly R&D expense? Thank you.

Hi, Kenny. I'll take your question. Well, so like we just explained our financial result, you can see the operating average is already emerging. So revenue grew 87% this quarter and R&D only increased like 36%. And our R&D is largely shared like a technology platform supporting L4, L2++, L3, and all the other product categories. So it does not really scale linearly with revenue or the vehicle deployment. So as we can see, as we scale across different business, the R&D cost per vehicle will continue to decline. We have also moved past the peak investment phase for the AI infrastructure build up. and where the city deployment costs taper significantly once operations are established. So looking ahead, we think we will remain very disciplined in R&D spending and continue to invest in the technology mode, like say for the foundation model, like on the genesis and width of what Tony just described. As our light L4 business scales and L2++, L3 enter into mass commercialization, we expect the operating leverage to accelerate. So we remain very well on track to achieve a positive cash flow in a single quarter by 2028. And we aim to have like a break even in the full year 2029. Thank you.

Okay. Thank you very much.

Thank you. Now we're going to take our next question. And the question comes line of Mai Liu from HSBC. Your line is open. Please ask your question.

Thank you for taking my questions. Yeah, the company just launched the WICT model. So, Tony, could you please share more about all this? Thanks.

Okay, I would like to share more about the WIT model. Okay, you can see from the WIT model, so basically, I will say the key part of the WIT model is trying, it provides WRide a unique analysis tool for video, and combined with Genesys model in tandem, we can, so first of all, if your video, it has many facts. and you cannot simply do causal inference across different videos. And so it's just like I give you a machine and which model can help you to defect the machine and find out the relationship between different components. And Genesys gives you another capability of learning the functionality of components and put them together to build another machine. So basically, just like if I give you a Lego toy of maybe, say, for example, a Lego toy of a Jeep, and then I can dissect it and make it into a cargo ship. OK, so by putting these two together, we find a very unique path to analyze hundreds of videos, thousands, billions of videos and find out the causal relationship between all the facts and then use them to generate the relevant data or very long tail data for our autonomous driving. By this way, we actually boost our training capability and lower our training cost. and build up the desired distilled onboard model. In the urban challenge, we won six consecutive championships. Our domain controller is relatively slower and the TOPS is much lower than our competitors. they may have 2,000 TOPS domain controller. We only have a 200 TOPS controller. But we are winning. Why? Because we can distill model according to our special needs. And we can get multiple long tail. So that's the power of our tool foundation model. I will stop here. If you have further questions, you can also ask.

Thanks, Tony. That's super clear. Thank you. Thank you.

Thank you. Now we're going to take our next question. And the question comes from Ming Sun Li from Bank of America. Your line is open. Please ask your question.

Thank you, Tony and Jennifer, for giving me the opportunity to ask. I just only have one question. We have noted that measurement emphasized your competitive advantages. The market's view on the industry are currently split. could management articulate your competitive modes? Thank you.

So I want to understand what are the splits? Can you be a little bit more specific? So what kind of split will?

What I mean is that I think the industry currently I think the competition is getting more intensified. So I think that's why the capstone market has a different view on the industry competitive landscape. So yeah, I just want the management team can articulate more about your competitive modes.

Okay, I got you. Okay, thank you for the clarification. I think, you know, just like I mentioned, it's playing the foundation model we developed, right? The Rita and the Genesis. And I think people may want to try to do the same thing, but we have all the same objectives. But like everybody wants to build electric cars, but in the company who will build up the best motor, the best battery, who has the best design aerodynamics, will win big orders. And for ADAS, I think there's a grand challenge. I keep on saying that we won six consecutive championships. That is a challenge. We compete against all the top-notch ADAS system company. And also, our leverage, our L4 capability, We have a very large scale of our driverless operations fleet and it also operates globally in the Middle East, in Europe and in China. We can gather all kinds of different data and improve our model. And I think the only company in this world has so-called dual flywheel dual flywheel mechanism that is getting data from L4 RoboTaxi to help to improve L2-L3 ADAS system and also get from L2-L3 ADAS data and help to improve L4 because with V-Ride design, they are built on the same foundation model based on the same, very similar sensor configuration. We can use these two things in tandem to build help leverage on each other and boost on each other. So with this, I think we have our unique competitive edge and our results, our financial numbers, our competition numbers, our evaluation numbers have already show like we really in a leading position. Just a simple question. which company else have their founder have their ADA system doing live stream video and in the in the tier one city for two hours without any intervention parking lot to parking lot to me I'm the only guy who who first tried and next month I'm going to try it again So I think all the results make it quite straightforward that WeRide is a leader in both L2++ and L4, and we have a very strong competitive edge.

Thank you very much, Tony. Thank you.

Thank you. And now we're going to take our final question for today. and the question comes from the line of Walter Patrick from Light Shed. The line is open. Please ask the question.

Thanks for taking the question. On the asset light model and the platform relationships, under this structure, your partners own the vehicles and the platforms basically own the riders. So we ride basically sitting in the middle licensing the driver. That makes the durability of those relationships kind of a whole thing. and then on Uber, one of your partners, obviously in some markets, their track record here is obviously had them rotating Waymo out in Phoenix. They just wound down their serve robotics relationship. So I guess if you can just review what exclusivity or minimum volume commitments that you have in the Uber markets and in the asset light model where you don't own the cars or the customers, What ends up being your leverage if the platform, Uber or whoever, decides to route demand to other partners?

Chet, do you want to take this question or you want me to take this question?

Sure, I can take this question. So first of all, Water, we have this athletic business model so that we can expand relatively faster in the global market. and especially wherever we go we try to build like an ecosystem with the local partners and of course also with the platform partners and so we work with multiple platform partners and we work with multiple and local partners so for us and this is really a huge market out there this is really at the beginning and we want we think setting up like a healthy ecosystem It's going to set a good foundation for everybody. And if you are looking at the real deployment figures globally, we believe we have the largest robo-taxi fleet outside China and the US among all of the AV competitors by a lot. And we think that our strategic mode is not only like just deploying the asset there and that's it. So basically, if you're looking at what we do everywhere, we sell the assets and to the local partners or the fleet operators. And then we, because we do have like a bomb advantage from China. So we're gonna keep have that advantage. And then what's more importantly, because V-Ride has a superior like safety record That's why we can get autonomous driving license in so many countries. Right now, we have autonomous driving license, official license, from eight countries. We operate in 12 countries. Nobody else, based on my knowledge, has such an operation scale. And for us, the responsibility is also, the key responsibility is to get the regulatory permit. So that responsibility is with the ride. and that's going to be the key for the longer term and everyone can can be on the platform but not everyone can get the regulatory permit and for regulator everything is um it's a marriage basis so for the for the av player who have who keeps having like the good safety record locally globally they definitely can get more permit as business skills but for some of them who doesn't have such a good record in fact some of the competitors are getting like, they will get questions, get suspension from the regulator when their safety accident continues to happen. So we have a strong confidence in our tech capability, in our local deployment capability, our regulator communication and our safety capability, and we have strong confidence in V-Ride's safety record. So with all of that, that's how we build this strategic mode globally. Yeah. I hope that answers it.

That's very helpful. No, that's actually very helpful, especially on the regulator side in terms of who has the power in the market. I just have one follow up on the OEM side and specifically with Mercedes. On the call, you just framed the L3 proof of concept as kind of a validation of the leading OEMs. But then Mercedes is also an NVIDIA are the flagship partner doing this autonomous program on the full NVIDIA stack, so they're not just using NVIDIA's open model, they're obviously doing the full stack. Can you just help us understand how this OEM, as an example, is evaluating WeRide, which NVIDIA wouldn't already cover? Is this just a Chinese market thing difference where NVIDIA stack wouldn't necessarily will be accepted? Is it about cost? Is it again on the regulatory? Is it that the OEMs will have multiple sources for L3 or L4 or L2++, whatever it is? And then I guess the bigger question is, over time, if NVIDIA has a lot of money and they mature, what's ultimately going to have your software win at a company like Mercedes?

you know obviously NVIDIA with this open model and doing everything else you know whether that's China regulatory or just cost okay let me answer this question i think uh you know first of all under the contracts we cannot reveal too many detailed things but i really appreciate this question i always make a joke internally i said look if you look at the internal nature of the company we write doing solve lots of things it's just like deep seek I think previously I always heard Sam Edelman answer the questions from an Indian engineer saying, OK, if you don't have such amount of money, I don't remember that exact figure. It's like maybe if you don't have $20 billion, never think about trying a large language model. But look what Deepseat has done, OK? So I always believe the genius, the great engineers, the great minds can be found, OK? That's why I like Silicon Valley. I believe the creativity of human nature. Therefore, I think WeRide is such a company with a great creativity, with a lot of genius, and we will build out the best ADA system, the best robo taxi, which have already proved by the market. Look at the resource we put in our company and look at results we have got so far. I think the answer to this question is Very straightforward, and I really appreciate this great question. Hello? Can you hear me?

Thank you. Yes, we do. So thank you so much.

Thank you very much.

Thank you. Due to time constraints, I will conclude today's call. Thank you for your participation in today's conference. This does conclude the program.