2015.HK2015.HK
LOADING
|||
Operator: Hello, ladies and gentlemen. Thank you for standing by for Li Auto's Third Quarter 2025 Earnings Conference Call. [Operator Instructions] Today's conference call is being recorded. I will now turn the call over to your host, Ms. Janet Chang, Investor Relations Director of Li Auto. Please go ahead, Janet.
Janet Chang: Thank you, operator. Good evening, and good morning, everyone. Welcome to Li Auto's Third Quarter 2025 Earnings Conference Call. The company's financial and operating results were published in a press release earlier today and were posted on the company's IR website. On today's call, we will have our Chairman and CEO, Mr. Xiang Li; and our CFO, Mr. Johnny Tie Li, to begin with prepared remarks. Our President, Mr. Donghui Ma; and CTO, Mr. Yan Xie, will join for the Q&A discussion. Before we continue, please be reminded that today's discussion will contain forward-looking statements 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. As such, the company's actual results may be materially different from the views expressed today. Further information regarding risks and uncertainties is included in certain company filings with the U.S. Securities and Exchange Commission and the Stock Exchange of Hong Kong Limited. The company does not assume any obligation to update any forward-looking statements, except as required under applicable law. Please also note that Li Auto's earnings press release and this conference call include discussions of unaudited GAAP financial information as well as unaudited non-GAAP financial measures. Please refer to Li Auto's disclosure documents on the IR section of our website, which contain a reconciliation of the unaudited non-GAAP measures to comparable GAAP measures. Our CEO will start his remarks in Chinese. There will be English translation after he finishes all his remarks. With that, I will now turn the call over to our CEO, Mr. Xiang Li. Please go ahead.
Xiang Li: [Interpreted] Now it's translation for Mr. Li. The third quarter of 2025 was also the first quarter in the second decade of Li Auto. We went through many challenges, including supply chain, product life cycle, PR challenges as well as changing policies. All these factors have had a negative impact on our operations and deliveries. However, today, I want to take this opportunity to talk about our long-term thinking in the next decade and three most important choices that we need to make, organization, products and technology. The first choice we need to make is organization. The challenge we're facing is whether to choose an entrepreneurial model or a professional management model. In the last 10 years of Li Auto, the first 7 of those years, we operated as an entrepreneurial model company. But as we scaled over time to a scale that we've never seen before, especially in terms of revenue, around the time of 2022, many people suggested to us to shift to a professional management model. Because historically, whether it's Mercedes or BMW or any of these 100-year-old car enterprises as well as Microsoft and Apple, which is the tech giants have all operated under this model and have great success. In the last 3 years, we tried very hard to make ourselves used to this professional management model. We -- but after implementation, we realized -- we came to the realization that the entrepreneurial model and the professional management model are fundamentally different, and it is irrelevant to processes and organization structures. The difference really lies in management principles and key operating principles. And also, they are tailored to different stages of growth and industry environment. The professional management model can be very successful, but it relies on three factors. The first one is that the industry and technology cycle has to be relatively stable. And the second is that the enterprise is already in a leading position and the position is relatively stable. And the third one is that the founding -- the founder and the founding team are either lost their motivation or are not actively involved in the company. If all these three criteria are satisfied, a professional management model could be a very ideal choice, whether it's Apple or Microsoft have both flourished after professional management took over and grew from $100 billion in revenue to $1 trillion companies. However, the entrepreneurial model is catered to an entirely different environment. First of all, the industry and technology cycles are going through fundamental changes. And second, the industry is very unstable and the entrepreneur -- and the company enterprise itself is not yet a leader. And thirdly, the founder and the founding team are still devoted to everyday work with their full passion and fully motivated. As AI is shaping many industries today, the environment that we live in and considering the traits of this company, we think that we fit into the entrepreneurial model way better. The entrepreneurial model really is about four things. First of all, there needs to be more conversations as opposed to reports. In a rapidly changing environment, deep conversations is really key to increasing our knowledge and judgment of the world as well as to making bold decisions. And secondly, is focusing on user value as opposed to just short-term deliveries. Only those things that create value for the users are worthy to be delivered as opposed to only focusing on how many tasks that we delivered on. And third one is keep increasing efficiency as opposed to occupying more resources. For example, if we spend $10 on doing something last year and this year we need to do it with $8. That's how we have, have resources to really spend on projects and investments that do not generate short-term revenue, but really benefit us in the long term. And fourth, the key is to recognizing the key issues as opposed to just creating information asymmetry. And only as we create more value and increase efficiency and solve the key issues, can we really thrive in a highly competitive and rapidly changing environment and consistently meet customer demand? In the last 3 years, me and my team have tried very hard to adapt to the professional managed model, and we have forced ourselves to embrace all kinds of changes. However, we all realize that we became a diminished version of ourselves. NVIDIA and Tesla are still operating as an entrepreneurial company. And if the largest and strongest companies are all operating in the entrepreneurial model, there is no reason for us not to utilize our strength and what we're most used to. Since 1998, I have 27 years of running entrepreneurial companies, and I have never worked in any large corporation as a professional manager. Now we're facing a highly competitive and rapidly change -- an environment with rapidly changing technologies. I personally am passionate about products, about automobiles and about AI. And work is my largest passion. So, why don't I focus on what I'm most used to and what I'm best at to manage Li Auto. And that's how -- that's the most important first choice as we look into our second decade. As a result, starting from Q4 this year, I and my founding team will firmly revert back to the entrepreneurial model and to embrace the new era and new technological challenges. The choice of organizational model is the foundation of everything. Looking into the next decade, the next key question is how we really solve issues for our customers. First of all, what products do we build? And where is technology headed? That's always the essence of everything. First of all, on products. We also need to make an important choice. What kind of products should we really build for our users? Is it electric vehicles? Is it smart devices? Or is it embodied robots? If we only focus on electric vehicles, competition is really all about an arms race in spec sheet. Do you have more -- 20 kilometers of range more? Do you have a car that's 2 centimeters longer in dimensions? And if it's only focused on electric vehicles, it's all about larger space, more range and cheaper prices and maybe copy some proven designs, just like how Li L9 has been copied. Other than that, all R&D investments are waste, stronger sensors, bigger models, more computing power, better active suspension are always waste of cost. And even stronger and stronger computation power and active ride suspension may even have negative impact on range. And secondly, if we choose to focus on smart devices, then we'd automatically be focused more on what happens in the screen. Features that used to belong to smartphones and smart tablets will be migrated to the car environment. In fact, most of the innovations in smart devices is really about moving what's already available in smartphones into vehicles and moving mobile apps into head units, deploying larger language models in head units and even do coding in cars and conduct deep research. But then, we ask ourselves the question, when our users buy our cars, do we really buy it for their work or deliver better life? If certain experience are better -- already better in mobile phones and tablets or computers and more natural, why should we even bother putting them in cars? All these investments create very little incremental value for users. And thirdly, the third route is for us to make our cars into an embodied AI in the physical world or in layman terms, robots. The movie transformer told us that there are broadly two types of robots. The first type looks like human beings and the second type looks like cars. Knight Rider and Cars, these TV shows or movies have clearly showed us car-shaped robots is going to be a mainstream type of -- form factor of robots going forward. So, how do we transform our cars into robots? We need to give it ears and eyes for perception. We need to give it brains and nerves, which is modeling capability. We need to give it heart, which is computing power, and we need to reshape the hardware to make it a stronger physical presence. So, our robots need to have -- need to parallel the top drivers and can not only drive but also pick you up, park for you, have to charge the car up, have to close the door, open the door and meticulously make your life more convenient and safer. It can also play the role of parents, assistants or even flight attendants and to provide you the convenience and take care of you within the sphere of the car, just like first-class cabin and the services on planes. And it's also like when we're a little that our mother takes care of us and make us happy. So, how do we define a good embodied robots? How do they make them to change from passive machines into an automated machine and then further into proactive machines? In the next decade, the most valuable embodied AI products is going to be vehicles that are automated as well as proactive. And competition is really to how automated and proactive can we make these products and how can we fuse them into high-frequency life experiences something that once we get used to, we can never go back. So, whether it's electric vehicles or smart devices, these are not necessarily bad choices, but we think they're not sufficient. And only if we choose the embodied AI, which is the hardest about these three problems, can we really change the life of our users and really provide automated and proactive services that only embodied AI products can provide. And it's really like what you see in Transformers movies, they're car-shaped robots or what we see in Cars or Knight Riders, they are robots that are shaped in cars. And I believe that this is the biggest challenge and opportunity that we entrepreneurs see in this new era. And the next choice is about technology or more specifically, our full stack AI system. What do we choose? What kind of technology do we choose to power this full stack AI system? Is this something that's language-based that's faced towards the digital world? Or is this something faced towards the physical world? These two options require completely different system capabilities. If we want to build a good embodied AI, we need to build an AI system that's completely different from language-based AI models, including perception like eyes and ears, including the model itself like brain, including the operating system like nerves and including the computation power, which is like hearts and also the physical body itself, just like human body. At this moment, there's no third-party supplier that can provide the full-stack system. And in fact, not any company can provide even part of this system. And the focus of large language models is really focusing on the model itself and computation. Larger models and more computation power is always going to generate stronger capabilities. However, for embodied AI, we need to better understand the physical world. And the model is also built on our understanding of the physical world. Accuracy is the first priority and generalization only comes next. Operating system needs to make sure the optimal integration is made between the hardware and the software and also provide higher frequency and also the system needs to be fast and precise. And also this computation power that powers the perception, the model and the operating system needs to reside on the device side as opposed to the cloud side. And lastly, we also need to modify the hardware itself to become a really embodied hardware. And for example, our active suspension, it's just like a 3D nerve system -- nerve control, and it can increase the efficiency and precision of execution in the physical world. So, if we look at this entire AI system through the lens of embodied AI, you will see that there are so many changes that needs to happen and desperately need to happen. The first change comes in perception. Based on the current model and the computation power that can be deployed on the device, the current 3D BEV or occupancy network or 2D Vision Transformer, the effective range of perception, I'm talking about the effective as opposed to theoretical maximum is only just about over 100 meters, which is way less than human eyes. However, if we upgrade it to 3D Vision Transformer, which is just similar to how human eyes works, this range can be increased by 2x, 3x, and it can solve more than 50% of the common issues we see in autonomous driving. 3D Vision Transformer is not only limited to autonomous driving, but it can also benefit interactions with the car inside and outside of the car. These can also all become possible. So that requires fundamental breakthroughs in perception models, both in research and also development. And also requires tailored chips for embodied AI, just like M100, which we have developed and also requires a very strong compiler team and high-efficiency cooperation. The next area of improvement is in models. It's only with 3D Vision Transformer can we really understand the world. The VL in the BLA is really -- can really understand and perceive the world better and human data can be more effectively used for training and world model can also be used more effectively for training. For example, in the status quo computation platform, a 4-billion parameter MOE model can only run at 10 hertz. But the execution frequency is 60 hertz. So, we can increase the frequency of the model by 2x to 3x. It can also automatically solve many issues, including comfort and speed of reaction in autonomous driving. And it also requires us to fundamentally modify and customize the traditional GPU architecture and to have a dedicated operating system. And M100 again, is really designed for solving these embodied AI problems. And lastly is the embodied hardware itself. A human being can typically react to braking and steering in about 450 milliseconds. And for a typical autonomous driving system from perception to execution, the entire closed loop takes about 550 milliseconds. So, for a typical driver today, they can easily -- it's very obvious to them that autonomous driving is much slower. It's like an elderly driving car. The drive-by-wire system can reduce the response time to about 350 milliseconds. And the difference of 200 milliseconds is not to be underestimated. It can roughly reduce the accident rate by over 50% and it also feels better even than driving by themselves, and it's also safer. It's safer both in the subjective as well as the objective sense. So based on these needs, all the entire control mechanism will be different. And if we only focus on increasing the scale of model just like we did in language models, for example, if we increase the size of model 2x and with a corresponding increase in computation power, the really performance increase is only going to be 5% to 10%. But if we look at this from an embodied AI perspective and to solve the key issues in every stack -- on every level of stack, the next-generation autonomous driving can really increase the performance by 5- to 10-fold. And that is what can power embodied AI to perform fast and accurate and valuable services. And that's the difference between 0 to 1. In the past 3 years, we have made a lot of progress in technology and systems for embodied AI. And that makes us very confident about the next-generation products. The start of embodied AI robots starts with car robots and starting this year, I believe, and hundreds of billions of revenue is only a starting point. So, the above three key strategic choices really laid the foundation for the next decade of our development. It's more challenging than the last decade. And we're deeply aware that real competition isn't really about short-term wins. It's about staying on the right path over the long term and having the dedication to keep investing in it. Backed by a strong financial foundation, we will stay focused, embrace our beloved entrepreneurial management style and build leading body intelligence products. So Li Auto can navigate market cycles, lead technological transformation and become a company that creates unique lasting value for users and society in the long run. Finally, I will also look forward to engaging with you guys in this manner moving forward rather than presenting a quarterly report in a fixed format. And I want to express my gratitude to all of you for your support and trust, especially during our most challenging times. We're fully committed to making Li Auto the best performing company in embodied intelligence and the greatest creator of user value within the next 3 to 5 years. Thank you.
Tie Li: Thank you, Xiang. Hello, everyone. I will now walk you through some of our third quarter financials. Given time constraints, my remarks today will be limited to the financial highlights. All figures will be called in RMB, unless otherwise stated. For further details, we encourage you to refer to our earnings press release. Total revenues in the third quarter were RMB 27.4 billion, decreased 36.2% year-over-year and 9.5% quarter-over-quarter. This included RMB 25.9 billion from vehicle sales, decreased 37.4% year-over-year and 10.4% quarter-over-quarter, mainly due to lower vehicle deliveries. The sequential decline was partially offset by a higher average selling price due to the different product mix. Cost of sales in the third quarter was RMB 22.9 billion, down 22% (sic) [ 32% ] year-over-year and 5.3% quarter-over-quarter. Gross profit in the third quarter was RMB 4.5 billion, down 51.6% year-over-year and 26.3% quarter-over-quarter. Vehicle margin in the third quarter was 15.5% versus 20.9% in the same period last year and 19.4% in the prior quarter. The year-over-year decrease was mainly due to estimated Li MEGA recall cost and the higher per unit manufacturing cost from lower production volume. The sequential decline was mainly due to the same recall-related costs. Excluding such recall costs, vehicle margin would have been 19.8% in the third quarter. Gross margin in the third quarter was 16.3% versus 21.5% in the same period last year and 20.1% in the prior quarter. Excluding the above-mentioned Li MEGA recall cost, gross margin would have been 20.4% in the third quarter. Operating expenses in the third quarter were RMB 5.6 billion, down 2.5% year-over-year and up 7.8% quarter-over-quarter. R&D expenses in the third quarter were RMB 3 billion, up 15% year-over-year and 5.8% quarter-over-quarter. The year-over-year increase was mainly due to the impact of the pace of new vehicle programs and increased investments in expanding our product portfolio and technology, along with expenses from the product configuration adjustment. The sequential increase was mainly due to those same product configuration adjustment expenses. SG&A expenses in the third quarter were RMB 2.8 billion, down 17.6% year-over-year and up 1.9% quarter-over-quarter. The year-over-year decrease was mainly due to the recognition of share-based compensation expenses regarding the CEO's performance-based awards in the third quarter of last year. Loss from operations in the third quarter was RMB 1.2 billion versus RMB 3.4 billion income from operations in the same period last year and RMB 827 million income from operations in the prior quarter. Operating margin in the third quarter was negative 4.3% versus 8% in the same period last year and 2.7% in the prior quarter. Net loss in the third quarter was RMB 624.4 million versus RMB 2.8 billion net income in the same period last year and RMB 1.1 billion net income in the prior quarter. Diluted net loss per ADS attributable to our ordinary shareholders was RMB 0.62 in the third quarter versus diluted net earnings of RMB 2.66 in the same period last year and RMB 1.03 in the prior quarter. Turning to our balance sheet and cash flow. Our cash position remains strong with a quarter ended balance of RMB 98.9 billion. Net cash used in operating activities in the third quarter was RMB 7.4 billion versus RMB 11 billion provided in the same period last year and RMB 3 billion used in the prior quarter. Free cash flow was negative RMB 8.9 billion in the third quarter versus RMB 9.1 billion in the same period last year and negative RMB 3.8 billion in the prior quarter. And now for our business outlook. For the fourth quarter of 2025, the company expects the deliveries to be between 100,000 and 110,000 vehicles and quarterly total revenues to be between RMB 36.5 billion (sic) [ RMB 26.5 billion ] and RMB 29.2 billion. This business outlook reflects the company's current and preliminary view on its business situation and market conditions, which is subject to change. That concludes our prepared remarks. I will now turn the call over to the operator and start our Q&A session. Thank you.
Operator: [Operator Instructions] Your first question comes from Yingbo Xu at CITIC.
Yingbo Xu: [Foreign Language] So, I have two questions. The first question is about -- we are very glad to hear the company's return to entrepreneurship and next decade plan. But any R&D and development needs time. So my first question is that if we just say next year 2026, what kind of technology or product progress can we expect? And also from the investors' perspective, how long can we really see a technology or product jump in future? How long? And the second question related to BEV. The company's transition from EREV to BEV, it's challenges. So can we please give us more information or confidence in the BEV part, how we prepare for the effective technology reserve and supply chain preparation?
Xiang Li: [Interpreted] On your first question about 2026, next year, we'll be launching our AI system based on our internally developed M100 chips. And once this system gets in the car, that's where we will start to see real value and change of user experience. As I mentioned earlier, our products would go from a passive -- a machine that passively takes orders to a more automated machine and even a proactive machine that can provide services for the users. So, unlike large language models, which can conduct deep research or video generation, this embodies AI products and really benefit our users in their everyday use at a very high frequency. And on the second part about the next 10 years, unlike programming or traditional rule-based programming, we do not have a feature list or a list of functions. Instead, AI really -- for a complex AI system, if we can solve key issues in some important areas and improve performances in some bottleneck points, then we will start to see a series of changes that are unimagined before. And that's our late understanding of embodied AI and AI system. And this is really the room for imagination for the next 10 years. On the key in-house BEV-related technologies, we focus on three areas: electric drive, battery systems, and electronic control. First of all, on the electric drive system, our focus is on efficiency and user experience. We have an in-house developed and outsourced our manufacturing of silicon carbide power chips and in-house developed and in-house manufacturing of power modules and motor controllers, but also establish our own dedicated drive motor factory. We have built a full chain in-house development capability stemming from silicon carbide power chips, power modules to electric motor assemblies. Our electric drive technology covers all BEV and EREV models, ensuring quiet and smooth driving experience while also optimizing for energy consumption and vehicle driving range. And secondly, on the battery system, our focus is on ultrafast charging and safety. We have built a full stack in-house capability around 5C ultrafast charging batteries with full control over self-chemistry, BMS control modules and algorithms as well as battery pack layouts and structural design and achieving three core advantages across ultrafast charging, long driving range, and long service life. On the supply front, we also have a combined strategy of external procurement and in-house development. Li Auto's own 5C batteries will enter mass production next year. This industrialization of in-house developed technology will further strengthen our battery safety and also improve user experience. And thirdly, on the electronic control system, our goal is to provide the best driving experience also through in-house developed hardware and software. On the software side, we have full stack in-house development capability of powertrain control, power management and engine calibration. On the hardware side, our core domain controller PCB layout are all developed in now as well as the underlying software. Together with our in-house chassis technology, and we were able to enhance driving smoothness and comfort and make the drive experience easy and intuitive to our users. So, through a combination of three electrical technology, including battery electric control and electric drive, we provide our users with a special fast charging long-range and smooth and safe driving experience.
Operator: Your next question comes from Tim Hsiao from Morgan Stanley.
Tim Hsiao: [Foreign Language] So, I have two quick questions focusing on the near-term operation. So, the first one about the product, Li i Series. Could the management team share the latest update on orders and deliveries of Li i8 and i6? And in the meantime, how and when could you start the current supply bottleneck of the Li i6 and i8? And how should we think about the normalized sales volume of the two i Series models in the following months? Second question is about cash flow. Li Auto actually registered increasing operating cash outflow of about RMB 7.4 billion or free cash outflow of RMB 8.9 billion during this quarter. So, this caused quite a significant drop in company's cash reserve drained away. Why is that? And how should we think about the cash flow in the following quarters? That's my second question.
Xiang Li: [Interpreted] This year, we established our BEV portfolio with i8 and i6 models. And respectively, they cover the mainstream and premium segments for the family BEV market. These new cars create a solid foundation for the long-term stable growth of our BEV business. We also deployed our products to support the dual energy strategy, namely EREV and BEV, which effectively complement each other and to meet the diverse needs of our users. A key highlight that's worth mentioning is that we have made breakthroughs in key regional markets. The i-Series has successfully entered core BEV markets such as Beijing, Shanghai, Jiangsu and Zhejiang, with orders in these areas starting to increase significantly from September. Li i8 and i6 are steadily going through the path of production ramp-up, delivery acceleration and market penetration. And starting in November to address production ramp-up challenges, we will officially start to begin a dual supplier strategy for our batteries on Li i6. We will ensure consistent performance and quality standards between these two suppliers. We will expect monthly Li i6 production capacity to steadily increase to about 20,000 units starting from early next year. We sincerely apologize to customers who placed orders on i6 and still waiting for the cars to be delivered. Due to constraints in the supply chain planning of key components and the pace of production ramp-up, your vehicle is still -- the delivery schedule has been affected. We deeply appreciate your trust and choice in Li Auto, and we kindly ask for your continued understanding and patience. Our team is working around the clock to accelerate production and expedite the delivery process.
Tie Li: And for the second question, Tim, this is Johnny. I think for the operating cash flow, it's about two reasons. First, as we guided in the last earnings release, the third quarter, we faced great pressure on the deliveries and the delivery decrease will make the revenue decrease, which will finally impact the operating cash flow and also the impact of shortening of the payment cycle to suppliers. And this is, as you may know, it's due to the government's authority starting from good in the national wide. Actually, we value our partnership with our supply chain partners and actively respond to their requirements. Currently, the settlement period for all our accounts payable is 60 days and the payment is either through bank transfer or bank notes without any business notes or some kind of certificates from the OEM, just the normal bank notes.
Operator: Your next question comes from Ming-Hsun Lee from BofA.
Ming-Hsun Lee: [Foreign Language] So, my first question is that because next year, the trade-in subsidy policy will change and also the EV purchase tax will increase from 0% to 5%. If the subsidy decline next year, what will be your sales strategy for 2026? [Foreign Language] So, my next -- second question is that in 2026, your Li i and Li L series will have a new generation. So what can we expect the most -- the new features, specs and what will be the new advantages for your new models?
Xiang Li: [Interpreted] We believe this change marks the auto industry's transformation from policy-driven adoption to organic market-driven adoption. And it is precisely during this phase that the value of stronger players can really stand out. As the purchase tax policy phases out, there will be fluctuations in the first short term, we believe. We expect to see a pull-forward effect, namely as customers rush to lock in their incentives at the end of 2025, that will naturally lead to a substantial dip in deliveries in Q1 2026. Looking into the longer term, we are optimistic about the penetration rate of NEVs. In 2026, the NEV penetration rate in the domestic Chinese market will probably reach between 55% to 60% with the rate in the premium segment exceeding 60%. At the Auto, our response strategy is to guarantee user benefits and adapt to new standards with our new vehicles rolling out during the transition period. And for the transition period, we have a peace of mind purchase program covering the purchase tax difference for i6 customers who locked in their orders in 2025, but take deliveries in 2026. All of our 2026 models meet the new standards for gas and energy consumption, so they will qualify for 2026 incentives. In the longer term, we will continue to be dedicated to user value and offset policy impacts through technology advancements. For example, we will be fully adopting 800-volt high-voltage platform and 5C ultrafast batteries to enhance efficiency and reduce energy consumption in 2026. We aim to operate about 4,800 supercharging stations by 2026, with 35% of which will be on highway service stations. We'll continue to deepen our supply chain localization and leverage economies of scale to stabilize pricing, while accelerate product iteration to keep all 2026 models at the forefront of product competitiveness. As the product strength, we must accelerate model innovation and accelerate further. In summary, this policy phase out marks a watershed moment for the industry's shift from -- towards high-quality development. Li Auto is poised to achieve a historic breakthrough in deliveries in 2026, and we will navigate this cycle through superior product strength and user value, thereby consolidating our leadership in the premium market. Usually, on product release dates and more details, we need to choose an appropriate time to release publicly. But today, I still want to take the opportunity to give a glimpse on our product rollout for next year. The next year for L Series is going to be a major generational upgrade. And the changes are based on deep research of users and their feedback as well as our accumulation of technology over the years, and we want to build a very strong product that's also fundamentally different from the current generation. And all this is to support our goal of reclaiming leadership in the EREV market in 2026. In terms of model configuration, we'll be going back to the simplified SKU approach, which balances market coverage as well as supply chain efficiency. So, even the base model will not compromise in terms of user experience and will have all features as standards. And in terms of design upgrades, while retaining our iconic design DNA, we will be upgrading the premium deal and craftsmanship. We'll strike a balance between strong brand identity and fresh user appeal and to refine our products to better serve the needs of family users. On the core technology front, 5C standard supercharging will be standard on all models and seamlessly integrating with our existing charging network to efficiently address range anxiety. And at the same time, we will reinforce our position as the EREV leader, building on our first-mover advantage and deep expertise in EREVs. The 2026 L Series refresh is about responding to market uncertainty with certainties on technological upgrades, delivery cadence and user value. We will announce the specific launch timing and further details at the appropriate time. Please stay tuned.
Operator: Your next question comes from Paul Gong at UBS.
Paul Gong: [Foreign Language] So let me translate. I have two questions. The first one is regarding the recall of the MEGA. I noticed this was announced in Q4. Why are you booking it in Q3? And how did you determine the amount and the sharing between yourself and the supply chain? What's the impact for the Q4 GP margin? And if possible, please also update us about the latest situation of the callback of the recall as well as the latest order of MEGA. My second question is regarding the AI. Can you please update us the latest development of VLA, large model and the user feedback. If possible, please also give more color for the future targets and upgrades process.
Tie Li: Paul, this is Johnny. I think, I will shortly and we will respond to your question very shortly. First, we recognized this in Q3 is just we regard this event as a subsequent event. So it will be accrued in the most recent quarter, we can recall. So, it's a bit accounting standard. And for the recall, I think we have announcement. I don't want to repeat most of the details covered. And currently, we just make all the battery pack to fulfill the recall requirement, the demand and which means we lower the delivery of our 2025 MEGA delivery. So, which means all the battery pack, we shipped most of them to replace the 2024 recall. I think that best serve the customers' benefit. And that's the company's value proposition.
Xiang Li: [Interpreted] We rolled out our VLA Driver to all of our AD Max vehicles in September. And with the strong migration capability of our model across all releases, all of our AD Max users have access to this new model, including the new i Series users as well as the Li L9 users who bought the car back in 2012, and they're able to experience its core capabilities across the board. User feedback and data analysis have very clearly showed the effectiveness and the level of experience improvement. We can see that Li L Series and i Series owners have a strong -- Vi i Series owners have a stronger willingness to use VLA Driver with both DAU and MPI showing improvements. In the meantime, users generally report the VLA to be smoother, especially in longitudinal control and more proactive and decisive in detours and more accurate in route selection at complex intersections. And with ongoing iterations, the functions of VLA will continue to achieve further breakthroughs. For OTA 8.0, which is our first full-scale rollout, the priority is mostly focused on safety. And in early December, we will release the OTA 8.1, which further enhances VLA perception capabilities for more precise and responsive behavior. And by year-end, we will deploy an architecture upgrade to strengthen language behavior interaction and streamline the decision-making process, which will be compatible with our upcoming in-house developed M100 chip. Beyond core system improvements, we're rolling out a series of innovations, including the industry's first defensive driving AES feature to enhance safety capability and any point to any point full scenario automated parking and a smart finder to find charging stations and park automatically. And all this completes the smart mobility ecosystem.
Operator: Your next question comes from Tina Hou from GS.
Tina Hou: [Foreign Language] Thanks management for taking my questions. So, I just have one question. What is the progress in terms of our in-house developed SoC as well as the operating system and then the progress in terms of open source and future development?
Tie Li: Let me answer your question. We believe that AI inference system is a core foundation for intelligent vehicles. To achieve this efficiency, the system must be designed as integrated architecture, not as separate parts. Our in-house design controller hardware and operating system have enabled us to reduce development time from industry average of 15 months to 9 months, while lowering cost by 20%. Many modules in the inference stack still come from suppliers. To innovate faster together, we open source to Halo OS, enabling collaborative development with our partners and ecosystem. In September, we established the Halo OS Technical Steering Committee, and assisting companies across intelligent vehicle value chain signed the community charter, including OEMs, chip makers, software and hardware service providers and component suppliers. At the same time, we are undergoing our own vehicle foundation model for physical AI. Our focus is to improve perception, understanding and response, so the model can see further, understand better and react faster. The AI inference chip is the computing engine of this system. Our controller built with our in-house design chip M100 is now undergoing large-scale system testing. We expected commercial development to take place in the next year. Co-designed with our foundation model, compiler and software system, we expect that the M100 within our next-generation VLA-based autonomous driving system to achieve at least 3x the performance to cost ratio of today's high-end chips. On the basis of highly efficient AI inference and execution systems, our next priority will be faster iteration, continuous performance improvement and lower cost. Development of our next-generation platform and chip has already begun. Thank you.
Operator: Thank you. As we are now reaching the end of our conference call today, I would like to turn the call back over to the company for closing remarks. Ms. Janet Chang, please go ahead.
Janet Chang: Thank you once again for joining us today. If you have further questions, please feel free to contact Li Auto's Investor Relations team. That's all for today. Thank you. [Portions of this transcript that are marked [Interpreted] were spoken by an interpreter present on the live call.]