Prepared remarks
Good morning, and good evening, ladies and gentlemen. Thank you for standing by, and welcome to the WeRide Second Quarter and First Half 2026 Earnings Conference Call. Please note that today's event is being recorded. (Operator Instructions) Please note that Chinese interpretation is for convenience purposes only. In the case of any discrepancy, management statements in the 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 Li. 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 the company'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 Factors section of the company's Form 20-F filed with the SEC and the announcement on the website of the Hong Kong Stock Exchange for a full disclosure of these risk factors. 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 on a non-IFRS basis today, which are more thoroughly explained and reconciled to the most comparable measures reported in the company's earnings release and filings with the SEC and the Hong Kong Stock Exchange. 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. (Presentation) 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: overseas acceleration, asset-light scaling and a clear path to self-sustaining cash generation. We made strong progress across all three areas during the quarter, positioning 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 margin 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 improvement in operating efficiency, EBITDA also improved with a loss narrowing by 8% compared with the second quarter of 2025. On operational metrics, our L4 fleet reached approximately 3,400 units, up 22% since the earnings release in April. Within that, our robotaxi fleet grew by 500 units to more than 1,800 vehicles, a 40% growth over the same period. Furthermore, our one-stage end-to-end L2+/L3 solution has progressed from securing design wins to full-scale mass production. Revenue from this business surged nearly 2,600% year-over-year and increased 219% quarter-over-quarter in the second quarter. During the quarter, we delivered approximately 30,000 units of our L2+/L3 solutions, marking the beginning of 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 the second quarter, we further advanced our strategy as a 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 onboard 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, our L2+/L3 solutions. More importantly, this creates a powerful technology flywheel. Our real-world L4 operations generate high-value data that continuously improve safety, robustness and generalization, while our growing L2+/L3 generate additional road data, accelerating L4 model development and expanding coverage of long-tail scenarios. These are not two separate businesses; they are two reinforcing layers of a physical AI platform where every vehicle deployed, and every mile driven makes our technology smarter, safer and more capable. Next, I will walk 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 mode. Our overseas operations are built upon an asset-light model. We do not own operating vehicle assets. Vehicles serve 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 our footprint with significantly lower capital requirements and greater operational flexibility. Based on optimal utilization under normalized fleet operations, we estimate the steady-state annualized technology service revenue for robotaxi could exceed USD 50,000 per vehicle. 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 operational leverage. I would also like to clarify how we define unit economics. Our overseas unit economics is not based on our fleet ownership plus ride-hailing platform model. Their revenue is derived from fare charging at a 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 a recurring fee for autonomous driving technology services and knowledge-based fees. Because our positioning and business model differ fundamentally, the same term 'unit economics' carries very different operational and financial implications from those in traditional ride-hailing platforms. Backed by partners like Grab, Uber, Green Mobility, SBB and others, we are replicating this proven asset-light operational model across the Middle East, Europe and Southeast Asia. This marks that our overseas expansion is now entering a phase of large-scale commercialization. To put more detail on the second quarter, we announced new robotaxi commercial partnerships in Madrid, Spain; Zurich, Switzerland; and Copenhagen, Denmark. In the Middle East, we continued to expand robotaxi operations in Abu Dhabi and Dubai this quarter, now covering over 70% of the core urban areas. In Riyadh, 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 fleet, recurring orders, solid revenue and profitability in overseas markets. This will demonstrate the successful execution of our overseas acceleration and asset-light expansion strategies. For the domestic market, we continue to strengthen our operational capabilities and expand our driverless operation zones in Guangzhou to key areas of Tianhe District, including Zhujiang New Town, and the Haizhu District, including the Canton Fair Complex. This represents a nearly threefold expansion in our ODD compared to the end of 2025. 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 ride-hailing platform with self-operated robotaxis, 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 ride-hailing revenue, further demonstrating 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 robotaxi operations into more cities in the near term. At the same time, we will continue to build Guangzhou as our domestic benchmark with the goal of integrating driverless robotaxi into the public transportation system at scale. Together, these initiatives will provide a strong foundation for the next phase of domestic commercialization. Beyond this, I'd like to take a step back and discuss our regulatory mode. 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 moat that puts us two to three years ahead of the market. This mode is built on three core pillars. First, technology localization and 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 establish 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 accumulates localized real-world data, while our 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 others. This reduces marginal compliance costs, avoids redundant work and creates increasing operating leverage, allowing us to scale our asset-light autonomous driving business globally with greater speed and capital efficiency. There is a growing industry consensus on L4 core barriers that is shared by leading mobility platforms. Technical competitiveness depends not on total driving miles alone, but on the acquisition cost of rare scenarios, scenario diversity and practical data quality. Generic large foundation models cannot satisfy autonomous driving needs by themselves. 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 proprietary end-to-end data tool chain, 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 deployment. Turning to our L2+/L3 business, three things define our progress: industry-leading technology, rapid commercialization at scale and a path towards self-sustaining cash generation. Leveraging 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 proof-of-concept program with Mercedes-Benz, an important validation of our technology by a leading global OEM and further demonstration of strong industry recognition of our capabilities. As of June 30, cumulative diverse 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 0.5 million units in cumulative deliveries next year, positioning us for significant scale in our L2+/L3 ADAS business. Finally, a brief update on our AI infrastructure. This quarter, we officially launched the WIT model, which is a physical-fact foundation large model, completing a full capability loop spanning data comprehension, data generation and end-to-end technical stack. It delivers deep synergy with our Genesis world model. The WIT model extracts and verifies physical facts from road test data to build a cognitive foundation for machines to perceive and understand the real world. Leveraging validated physical facts, Genesis reconstructs diverse extreme operating conditions and 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, they underpin our core business lines of L4 autonomous driving and mass-produced L2+/L3. In closing, in the second quarter we delivered meaningful milestones and strong results across the business, which lead us back to the 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 overseas markets, leveraging our regulatory leadership and permit advantages, we will replicate our proven robotaxi model across Europe and other markets, accelerating the transition from successful validation to scale deployment. 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: secure more OEM partnerships, increase our market share with key OEMs and accelerate deployments at scale. Growth is the key. We will invest where we see clear conviction and meaningful scale potential rather than pursue growth for growth's 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. Beyond the numbers, I would like to thank my team. This is a team that embraces hard problems, confronts reality head-on and remains relentlessly focused on execution. That culture of intellectual honesty and operational excellence is what enables 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 that true intelligence must be grounded in observable, verifiable facts about the physical world. The same holds for 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 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 walk you through our second quarter 2026 financial performance in detail.
Thank you, Tony. Hello, everyone. Let me start with the key message from the quarter. Q2 marked an important inflection point for WeRide with strong revenue growth, continued gross 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, gross margin and capital efficiency. In Q2, we generated RMB 232 million of revenue, up 82% year-over-year and 103% quarter-over-quarter. Importantly, growth is broadening across both our businesses and geographies. Our L4 revenue reached RMB 125 million, up 47% year-over-year, primarily driven by robotaxi. Our focus remains on scaling the core L4 business, particularly robotaxi. Meanwhile, some of our other L4 businesses have natural seasonal cycles with commercial negotiation typically completed in the first half and revenue recognized as deployment takes 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 continued to accelerate rapidly with revenue increasing approximately 26x year-over-year and 219x quarter-over-quarter. This reflects an important transition from project development into mass production and scaled vehicle deployment. As more OEM programs move toward mass production, we expect L2+/L3 to become an increasingly important driver of our overall revenue growth. Overseas markets account for nearly 40% of group revenue and are becoming an increasingly important growth driver as well. Overseas revenue increased 164% year-over-year and approximately 170% quarter-over-quarter. More importantly, the economics of our overseas business are increasingly attractive. Our asset-light model allows us to scale through local partners and the operating ecosystem without requiring a proportional increase in our own balance sheet investments. This gives us three important advantages: faster geographic expansion, improving margin as operations scale and lower incremental capital requirements. We believe this model is an important foundation for our long-term path toward self-sustained growth. Turning to profitability at the gross profit level. Gross profit increased 143% year-over-year to RMB 87 million, while gross margin expanded 9.4 percentage points to 37.5% compared to 28.1% in the same quarter last year. The improvement was driven by continued scaling of our high-margin asset-light overseas L4 business, rapid growth in L2+/L3 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 revenue over time. Total operating expenses were RMB 533 million in Q2, slightly up 9.2% year-over-year, slightly slower than 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 investment in AI infrastructure and foundation models. At the same time, the much slower growth in total operating expense demonstrates 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 fees, while selling expense increased to RMB 29 million as we expand our commercial activities. Overall, we are seeing increasing operating leverage with operating expense growing well below 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. This result reflects the early benefit of our asset-light model and increasing operating leverage, particularly as we scale our overseas business and reinforce our path towards sustained cash generation. Finally, as of June 30, we have approximately RMB 5.4 billion in cash and other liquid financial resources. This provides 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 translate 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 questions.
Questions and answers
(Operator Instructions) And now we're going to take our first question. The question comes from the line of Jeff Chung from Citi.
Congratulations on the great results. My first question is that we note WeRide currently has a diversified business portfolio spanning L4, L2+/L3 as well as AI infrastructure. How does management prioritize resource allocation across different businesses and regions? And what are your goals for the second half of this year?
Okay. Thanks for the question. Let me start with an explanation about our financial and technology model. Over the past several years, advances in large models and AI have changed the landscape. With our foundation models — particularly Genesis and WIT — we can create strong data synergies across L4, L2+/L3 ADAS and AI infrastructure. WIT segments video into minimal factual units and lets us analyze each video at an atomic fact level. Combined with Genesis, we can generate diverse and targeted training data and long-tail scenarios. This capability drastically reduces the resources required to develop and scale our solutions. With one infrastructure investment, we can support our L4 operations, L2+/L3 ADAS and AI infrastructure, creating what we call a double data flywheel. This flywheel is why we believe we are the only company globally to achieve large-scale driverless vehicle operations while also having broad ADAS adoption by OEMs. For our goals in the second half of the year, first, we are pursuing our cumulative 0.5 million installations target for ADAS. We want to push for more OEMs to adopt our ADAS system. Second, we will continue to expand our robotaxi fleet in targeted markets. Third, for our AI infrastructure, we want more companies in robotics and related industries to adopt our foundation models and tools. We will invest where we see clear conviction and meaningful scale potential, not for growth for growth's sake. Those are the main priorities.
Now we're going to take our next question. The question comes from the line of Tim Hsiao from Morgan Stanley.
This is Tim from Morgan Stanley. Congratulations on the robust top-line growth and the global expansion during the quarter. A quick question about the overseas business: management highlighted accelerating overseas expansion and large-scale commercialization. Could you share more detail on how we should view your overseas strategy? And can it be replicated across different regions?
Thank you, Tim. Overseas markets are an important growth engine for us, contributing approximately 40% of group revenue and with significant room to run. The markets we enter face labor shortages and rising labor costs, creating natural demand for autonomous mobility. In Q2 we launched three new robotaxi deployments in Europe and expanded operations in the Middle East. Our robotaxi fleet roughly doubled to around 400 vehicles since last quarter. Our model is differentiated because we operate asset-light overseas: we do not own the vehicles in operation. Instead, we handle localized technology adaptation and regulatory compliance, and we license our digital AI driver to local partners. This allows us to capture recurring technology service revenue as operations scale, expand quickly without heavy capital, and maintain good margins. We estimate annualized recurring revenue per vehicle can exceed USD 40,000 to USD 60,000, with meaningful upside as density builds in each city. Our playbook is disciplined and repeatable: secure permits, adapt technology locally, set up a benchmark project, and then replicate at a lower marginal cost. Today, we have active operations across 12 countries. We are confident in the model and our pipeline, and we look forward to serving passengers in more markets.
Now we will take our next question. The question comes from the line of Paul Gong from UBS.
I have two questions. First, could you update the latest progress and future plan for your ADAS business? Given the relatively small size of the team on this front, what is your competitive advantage in this highly intensive competition? Second, how do you see OEMs and ADAS companies leveraging ADAS data to build robotaxi businesses? Does this trend pose a threat to your robotaxi business?
Thank you for those two important questions. First, on our ADAS (including both L2+ and L3): competition in ADAS is intense globally, and many benchmark their systems against FSD. Based on our internal evaluation, in urban scenarios in China our system is competitive with FSD. Recently I did a two-hour live stream driving our N60 equipped with WRD 3.0 ADAS through rush-hour Guangzhou without intervention; the video is online. Commercially, revenue grew about 26x year-over-year and 219% quarter-over-quarter and we delivered about 30,000 units in the reporting period. Our goal is 100,000 installations this year, and cumulative deliveries to exceed 0.5 million next year. How can we grow rapidly with a relatively small team? The secret is our foundation models: Genesis and WIT. These tools let us automate much of the data analysis, generation and model distillation, enabling high-performing ADAS with a lean team. AI allows us to scale engineering productivity dramatically. Second, on whether OEMs or ADAS companies building robotaxis is a threat: we welcome competition. But there is a substantial gap between ADAS and L4 robotaxi — in redundancy requirements, regulatory burden and validation — effectively orders of magnitude difference in safety and reliability. I have proposed a practical qualification threshold: a company should operate at least six months with a fleet of 100 driverless robotaxis without significant accidents before claiming to be a robotaxi operator. Hallucination may be entertaining in digital AI, but it is fatal in physical AI. In the physical world, safety is paramount. Our focus on rigorous safety, regulatory engagement and large-scale validated operations creates a deep moat for our L4 business. Thank you.
Now we will take our next question. The question comes from the line of Tianyu Lu from Citic Securities.
I have one question. How does management view the overall trajectory of future operating expenses, particularly R&D spend?
Tianyu, thanks for the question. As we showed in the quarter, operating leverage is already emerging: revenue grew 87% while R&D only increased 36%. Our R&D largely supports the shared technology platform for L4, L2+/L3 and other products, so it does not scale linearly with vehicle deployments. As we scale across businesses, R&D cost per vehicle will continue to decline. We have moved past the peak investment phase for AI infrastructure buildout; steady-state deployment costs taper significantly once operations are established. Looking ahead, we will remain disciplined in R&D spending while continuing to invest in foundation models like Genesis and WIT. As our asset-light L4 business scales and L2+/L3 enters mass commercialization, we expect operating leverage to accelerate. We remain on track to achieve positive cash flow in a single quarter by 2028 and aim for full-year breakeven in 2029.
Now we will take our next question. The question comes from the line of Mai Liu from HSBC.
The company just launched the WIT model. Tony, could you please share more about it?
I would like to share more about the WIT model. The key function of WIT is to provide a unique analysis tool for video data. A single video contains many facts that are not easily related across clips. WIT detects minimal factual units in video and helps identify relationships between components and events. Genesis complements this by learning component functionality and composing those to reconstruct complex scenes. Together, WIT and Genesis enable us to analyze hundreds of millions of videos, discover causal relationships among facts, and generate relevant long-tail data for autonomous driving training. This boosts our training capability, lowers training cost and enables effective distillation to onboard models for urban challenges. For perspective, our onboard controllers are much lower compute (e.g., around 200 TOPS) than some competitors at 2,000 TOPS, yet we win in competitions because we distill models specifically for our needs and obtain long-tail data efficiently. That is the power of our tool-backed foundation models.
The next question comes from the line of Ming-Hsun Lee from Bank of America.
We have noted management's emphasis on competitive advantages. The market view on the industry is currently split. Could management articulate your competitive moat?
Thanks for the clarification. Our competitive moat is built on several pillars. First, our foundation models — WIT and Genesis — and our end-to-end data tool chain provide a unique capability to analyze, generate and simulate long-tail scenarios efficiently. Second, we have a dual flywheel: large-scale L4 robotaxi operations generate high-value data to improve our ADAS systems, and mass-deployed ADAS generates additional road data to improve L4. This mutual reinforcement is unique. Third, we have proven performance: six consecutive championships in intelligent driving competitions and large-scale validated deployments globally. Fourth, regulatory trust and operational safety are core to our moat: we have official autonomous driving licenses in multiple countries and an established safety record that regulators rely on. Finally, the results — deployment scale, financials and third-party evaluations — demonstrate our leadership. These factors together create a strong, defensible position in both L2+/L3 and L4.
Now we will take our final question for today. The question comes from the line of Walter Patrick from LightShed.
On the asset-light model and platform relationships: under this structure your partners own the vehicles and platform partners basically own the riders, while WeRide licenses the driver. How durable are those relationships? Specifically, with partners like Uber who have rotated through robotics partnerships in the past, what exclusivity or minimum volume commitments do you have in Uber markets? In an asset-light model where you don't own the cars or the customers, what leverage do you have if a platform decides to route demand to other partners?
I can take this question. Our asset-light model allows faster global expansion and flexibility. We build ecosystems with local partners and platform partners in each market. We work with multiple platform and local partners rather than rely on a single partner. The market opportunity is very large and at an early stage, so we focus on building healthy ecosystems that benefit all parties. Operationally, we sell or provide vehicles to local partners or fleet operators and maintain a BOM advantage from China. More importantly, our superior safety record enables us to secure autonomous driving licenses in many countries. Today we operate in 12 countries and hold official licenses in eight. Securing regulatory permits is a key responsibility and differentiator. While many companies can be on a platform, not everyone can obtain regulatory permits; regulators approve operations based on merit and safety performance. Players with strong local safety records will be able to scale permits; others may face suspensions if safety incidents continue. Our confidence in our technology, local deployment capability, regulatory engagement and safety record is the foundation of our strategic moat globally.
That's helpful on the regulator side. One follow-up on the OEM side and specifically Mercedes: you framed the L3 proof-of-concept as validation by a leading OEM. Mercedes is also an NVIDIA flagship partner with a full NVIDIA stack in their autonomous program. How is Mercedes evaluating WeRide relative to what NVIDIA already provides? Is this a China market difference, cost, regulatory suitability, or is it typical for OEMs to source multiple suppliers? Over time, if NVIDIA matures, how does WeRide's software win at a company like Mercedes?
Let me answer that. We cannot disclose contract specifics, but I appreciate the question. Great OEMs evaluate many dimensions: technology performance, cost, integration capability, regulatory alignment and long-term partnership. We believe our results demonstrate that world-class engineering and creative teams can outperform expectations. NVIDIA provides valuable platforms and compute stacks, but OEMs often evaluate multiple software and system providers to meet region-specific regulatory requirements, cost targets and integration needs. In some cases, local regulatory acceptance, localization of behavior, and validated safety performance play decisive roles. WeRide brings deep experience in localization, regulatory engagement, field validation and a full-stack approach in sensors, perception, planning and control, plus our foundation-model-driven data capabilities. That combination is attractive to OEMs seeking differentiated, market-ready solutions. Ultimately, the market will choose suppliers that deliver validated safety, integration and business value. We have demonstrated those capabilities so far.
Due to time constraints, I will conclude today's call. Thank you for your participation in today's conference. This does conclude the program. You may now disconnect.
Thank you very much. Bye.