XPeng (XPEV) Q2 2026 Earnings Call Transcript

DATE

Monday, Aug. 24, 2026 at 8:00 a.m. ET

CALL PARTICIPANTS

• Head of Capital Markets - Alex Xie
• Co-Founder, Chairman and Chief Executive Officer - He Xiaopeng
• Vice Chairman and President - Brian Gu
• Vice President of Finance and Accounting - James Wu

TAKEAWAYS

• Total Revenues -- RMB 19.74 billion, representing an 8% increase year over year driven by higher vehicle delivery volumes.
• Vehicle Deliveries -- 103,295 units, a 65% increase quarter over quarter reflecting strong demand across SUV segments.
• Vehicle Sales Revenue -- RMB 17.05 billion, up 55% quarter over quarter due to increased delivery numbers.
• Services and Other Revenue -- RMB 2.7 billion, representing a 93.9% year-over-year increase primarily attributable to technical R&D milestones achieved with the Volkswagen Group.
• Gross Margin -- 20.7%, compared with 17.3% in the same period last year, supported by international expansion and service revenue.
• Vehicle Margin -- 12.1%, down from 14.3% year over year reflecting the impact of a product generation transition.
• R&D Expenses -- RMB 2.91 billion, up 32.1% year over year due to the development of new vehicle models and AI-related technologies.
• SG&A Expenses -- RMB 2.5 billion, a 15.2% increase year over year driven by higher marketing, advertising, and franchise commission costs.
• Net Loss -- RMB 1.34 billion, compared with a net loss of RMB 480 million in the prior-year period.
• Cash Position -- RMB 40.48 billion as of June 30, 2026, providing liquidity for physical AI and robotics initiatives.
• Robotics Financing -- $900 million raised in a first round at a post-money valuation of $6.2 billion to support the IRON humanoid robot business.
• Q3 Delivery Guidance -- 115,000 to 121,000 units, representing quarter-over-quarter growth of 11.3% to 17.1%.
• Q3 Revenue Guidance -- RMB 21.7 billion to RMB 23.4 billion, reflecting 9.9% to 18.5% sequential growth.
• Overseas Deliveries -- Exceeding 20,000 units in the second quarter, an 81% year-over-year increase representing over 25% of total revenue in the first half of the year.
• Export Average Selling Price -- Exceeding 40,000 euros, driving higher per-vehicle revenue and gross profit in international markets.
• New Orders -- Increased 50% quarter over quarter in the third quarter, reaching a record high for the company.
• IRON Computing Power -- 2,250 TOPS provided by three Turing AI chips, enabling the physical AI foundation model to run directly on the robot.
• Robot Production Target -- Scaled production planned for year-end 2026, with monthly capacity expected to ramp up to several thousand units in 2027.
• Robot Supply Chain Overlap -- 85% overlap with existing automotive supply chain partners, enhancing cost competitiveness for the robotics division.
• Robot Pricing Strategy -- Anticipated pricing at 2.5 to 3 times the bill of materials, with management expecting higher gross margins than the automotive business.
• VLA 2.0 Parameter Count -- Increased 3.5-fold in the latest version, delivering a 300% improvement in perception sensitivity.

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RISKS

• He stated, "Extreme weather and supply chain disruptions affected our pace of ramping up in delivery," noting impacts on the MONA L03 production ramp.

SUMMARY

Management reported a strategic advancement into physical AI, integrating its established automotive manufacturing capabilities with a new humanoid robotics division. The company secured substantial external financing to support the mass production of its IRON robot, which utilizes the same Turing AI chips and foundation models developed for its autonomous driving platforms. Management stated that the international business has become a primary growth engine, contributing significantly to overall revenue while maintaining higher average selling prices than domestic models. Technical service partnerships, specifically with the Volkswagen Group, continue to diversify revenue streams and support overall margins during product transitions.

• The company expects its IRON humanoid robot to generate recurring revenue through AI model upgrades and software subscriptions, which Chief Executive Officer He noted would yield higher lifetime profit than traditional vehicle sales.
• Management stated that the VLA 2.0 autonomous driving model, trained primarily on data from China, demonstrated high performance on European roads with minimal local training data during recent validation tests.
• The Robotaxi business has completed 2,000 internal test orders in Guangzhou, with the company aiming to begin passenger operations without a safety operator in 2027.
• The MONA L03 model is expected to be the company's first major product to achieve leading sales across multiple international markets, with deliveries starting in the fourth quarter.
• Management indicated that the dexterous hand of the IRON robot features 21 degrees of freedom and is the same size as a human hand, specifically designed to balance safety, reliability, and cost for retail and service sectors.
• The company plans to seek regulatory approval for VLA 2.0 in Europe in the first half of next year to establish a competitive advantage for its global vehicle lineup.

INDUSTRY GLOSSARY

• ADAS: Advanced Driver Assistance Systems, electronic systems that help with monitoring, braking, and steering.
• BOM: Bill of Materials, a list of the raw materials, sub-assemblies, and components needed to manufacture a product.
• IRON: The brand name for XPeng's general-purpose humanoid robot.
• MONA: A series of smart electric vehicle models by XPeng focused on high-volume segments.
• SDK: Software Development Kit, a set of tools that allows third-party developers to create applications for a specific platform.
• TOPS: Tera Operations Per Second, a unit of measurement for the computing power of AI chips.
• Turing AI Chips: In-house designed chips optimized for processing physical AI and autonomous driving models.
• VLA 2.0: Vision-Language-Action architecture, an advanced AI model that integrates perception and decision-making for robots and vehicles.

Full Conference Call Transcript

Operator: Hello, ladies and gentlemen. Thank you for standing by for the Second Quarter 2026 Earnings Conference Call for XPeng Inc. [Operator Instructions] Today's conference call is being recorded. I will now turn the call over to your host, Mr. Alex Xie, Head of Capital Markets of the company. Please go ahead, Alex.

Alex Xie: Thank you. Hello, everyone, and welcome to XPeng's Second Quarter 2026 Earnings Conference Call. Our financial and operating results were issued via Newswire services earlier today and available online. You can also view the earnings press release by visiting the IR section of our website at ir.xiaopeng.com. Participants on today's call from our management team will include Co-Founder, Chairman and CEO, Mr. He Xiaopeng; Vice Chairman and President, Dr. Brian Gu; Vice President of Finance and Accounting, Mr. James Wu; and myself. Management will begin with prepared remarks, and the call will conclude with a Q&A session. A webcast replay of this conference call will be available on the IR section of our website.

Before we continue, please note 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 results may be materially different from the views expressed today. Further information regarding these and other risks and uncertainties is included in the relevant public filings of the company as filed with the U.S. Securities and Exchange Commission. The company does not assume any obligation to update any forward-looking statements, except as required under applicable law.

Please also note that XPeng's earnings press release and this conference call include the disclosure of unaudited GAAP financial measures as well as unaudited non-GAAP financial measures. XPeng's earnings press release contains a reconciliation of the unaudited non-GAAP measures to the unaudited GAAP measures. I will now turn the call over to our Co-Founder, Chairman and CEO, Mr. He Xiaopeng. Please go ahead.

He Xiaopeng: [Interpreted] Good evening, everyone. I am pleased to share with our shareholders and investors that we have just announced the first round of financing for XPeng Robotics business. The business raised over USD 900 million at over USD 6.2 billion post-money valuation. This round was initiated by leading global investors, led by IDG Capital with participation from Gaorong Ventures in support from Tencent and Alibaba as strategic investors. Both the size and valuation of the first round of financing have set a new private financing record in China's humanoid robotic industry, underscoring the capital markets' strong endorsement of XPeng's leadership in physical AI technology road map, ability to manufacture at scale and long-term commercial value.

The financing will provide ample capital to support the mass production and continued development of our advanced general purpose humanoid robot IRON. We will accelerate our progress towards the ChatGPT moment for physical AI whilst bringing additional strategic resources to strengthen the robotics ecosystem and expand real-world applications. As a global leader in physical AI, XPeng will not only lead the large-scale deployment and commercialization of autonomous driving worldwide, but also build the world's most valuable humanoid robot company. Today, we're very happy to see that we have taken another important step towards that goal. Since June, alongside my responsibilities as CEO of XPeng, I have also taken up on the role of the CEO of our Robotics business.

Over the past 12 years, XPeng has remained committed to full stack in-house R&D across both software and hardware, building a solid technological and commercial foundation for the physical AI era. We are able to bring together and integrate the strengths and resources of the entire group. These include the supply chain, automotive grade manufacturing capabilities and global footprint developed through our automobile business as well as the Turing AI chips. AI infrastructure and world foundation models developed through our ADAS business. By applying these capabilities to our robotic business, I believe that we can accelerate the mass production and commercialization of XPeng's humanoid robots.

We have been conducting our research and development in the area of robotics for more than 8 years, and I have always believed that the technological challenges and level of innovation required for advanced general purpose humanoid robots are far greater than those for smart EVs by at least 20x. To accomplish something that is this difficult, we need to have a broad and deep R&D and system integration capabilities across design and styling, hardware and chips, software and AI, data and control systems and quality and manufacturing. Only then can we succeed. XPeng is the only robot company in China with such comprehensive in-house R&D capabilities across the entire technological stack.

This is why XPeng IRON fundamentally stands apart from other humanoid robots currently on the market with differentiated capabilities across multiple areas. Currently, our full in-house technology stack covers IRON's body, brain, cerebellum, data and infrastructure. On the hardware front, XPeng IRON features the industry's most human-like form and design. XPeng pioneered the industry's first fully enclosed flexible lattice structure for IRON, combining aesthetic appeal with enhanced safety with 76 degrees of freedom across the body and 21 degrees of freedom in each hand, both are at industry-leading levels. XPeng has independently designed and developed an AI-native hardware platform and all core components specifically for embodied intelligence, including chips, controllers, motion modules and dexterous hands.

Leveraging our established smart EV R&D and manufacturing capabilities, we can achieve automotive grade quality and build the capability to manufacture and deliver at scale. In terms of intelligence, XPeng IRON is powered by three Turing AI chips, delivering effective computing power of up to 2,250 TOPS. With the industry's highest level of edge computing power, XPeng's physical AI foundation model runs directly on IRON, enabling it to autonomously perform complex work tasks without [ teleoperation ] whilst ensuring low latency inference and data security. IRON's highly human-like hardware platform provides a natural advantage in scaling data.

It allows us to maximize the reuse of behavioral data generated in people's everyday lives and rapidly adapt to a broad range of environments designed for humans. As XPeng IRON moves ahead to mass production and real-world deployment, we will gain access to vast amounts of real-world and human demonstration data, accelerating the training and iteration of our AI models. In turn, continued improvements in model capabilities will allow IRON to enter more scenarios and generate more high-quality data, creating a flywheel across data models and applications that will accelerate IRON's evolution in the real world. XPeng IRON combines an exceptionally human-like design. The most intelligent AI brain and the highest standards of safety and quality.

Only by doing so, can IRON become a trusted companion to people and truly become a part of everyday working life. We have recently achieved several major milestones in the development of the mass production version. Starting from September, we will unveil and demonstrate a series of distinctive capabilities. We plan to enter scaled production by year-end with initial commercial deployments in XPeng stores and campuses. In 2027, XPeng IRON will officially launch and begin large-scale deliveries in China and overseas to external customers in the retail and service sectors. Next year, monthly production capacities can rapidly ramp up to several thousand units in response to market demand.

I believe the technological barriers to advanced general purpose humanoid robots are exceptionally high, while the supply of high-quality humanoid robots remain limited. As a result, the lifetime revenue and gross profit contribution of each IRON, including hardware sales and recurring revenue from upgrades to its AI model capabilities will be substantially higher than the current average selling price and gross profit per vehicle of our automotive business. I expect the commercialization of humanoid robots to scale rapidly in China and overseas following mass production, generating meaningful gross profit growth, supporting our investment in physical AI R&D and further widening our technological lead. Now I would like to come back to our automotive business.

In the second quarter, our vehicle deliveries reached 103,295 units, up 65% quarter-over-quarter, and we achieved year-over-year growth ahead of the broader industry despite industry-wide cost pressures. Our operations remained resilient, supported by our progress in the premium segment in international markets, company's gross margin remained above 20% in the second quarter. Our tech-defined luxury flagship model, GX, stood out among a wave of large 6-seat SUVs launched this year. Domestic deliveries exceeded 7,000 units in July, making it one of the top three models in China's NEV SUV segment priced above RMB 300,000.

MONA L03, the first SUV in the MONA series became a breakout hit immediately after its launch with orders setting a new record for any XPeng model. In the third quarter, new uncancelable orders increased by 50% -- 50% quarter-over-quarter to a record high. Extreme weather and supply chain disruptions affected our pace of ramping up in delivery. Here, I would like to especially express my sincere appreciation to our customers for their patience. We have started two shift production for the MONA L03 and are working closely with our supply chain partners to accelerate the capacity ramp. I expect that L03 deliveries will increase substantially over the coming months and continue to trend upward.

The success of the GX and MONA L03 gives us more confidence in our upcoming models. We are translating our competitive strengths in the best-in-class intelligence and standout design into higher sales targets and stronger brand momentum. Our flagship 5-seat SUV, the G9L will officially launch and begin delivery in September. The MONA L05 will also launch in China in the fourth quarter. With the launch of 4 brand-new SUV models, we will cover all major SUV segments. We believe XPeng's deliveries to increase significantly in the fourth quarter with monthly deliveries targeting more than 60,000 units. Our international business is the second growth engine for XPeng's automotive business and also an important driver of improving profitability.

Overseas quarterly deliveries exceeded 20,000 units for the first time in the second quarter, up 81% year-over-year. In the first half of the year, our international business accounted for more than 25% of total revenues. Furthermore, our overseas operations boast exceptional quality with an average selling price of our exports exceeding EUR 40,000, placing our per value revenue and gross profit at the forefront of Chinese automakers expanding globally. Since its global launch in Munich in July, the MONA L03 has attracted significant attention and earned high praise from overseas consumers for its intelligent technology, distinctive styling and spacious interior. I believe MONA L03 will become XPeng's first major model to achieve leading sales across multiple international markets.

Overseas delivery of the MONA L03 are expected to begin in the fourth quarter, driving firm-wide quarterly overseas deliveries to exceed 40,000 units. In 2027, we will also introduce multiple star models, including extended range EV models in overseas markets, further expanding our geographic coverage and market share. Starting from end of August, we will roll out a major upgrade to VLA 2.0, once again validating the stating law in ADAS and delivering substantial improvements in both user experience and safety. With the new 6.3.0 major version, the number of parameters in the VLA 2.0 on-device model will increase by 3.5x, putting its parameter count in order of magnitude above that of small models commonly used in the industry.

The new version delivers a 300% improvement in perception sensitivity, introduces ultra-long horizon reasoning and predictive capabilities and operates at an industry-leading frame rate. This enables the AI driver to see accurately, think ahead and respond quickly. The new version will also integrate ADAS and smart cockpit capabilities powered by VLA and VLM, bringing selected L4 level capabilities developed for XPeng Robotaxi to our passenger vehicles. One example is voice-activated pull over parking. Users simply give a voice command and VLA 2.0 will autonomously find a suitable roadside parking space and park the vehicle without exiting ADAS mode.

Recently, together with my colleagues, we test drove XPeng's VLA 2.0 and the latest ADAS from a leading global peer in China, Europe and North America, respectively. In my view, VLA 2.0 is already on par with the world's leading ADAS on major roads. In narrow roads when negotiating as well as in campuses and parking facilities, the user experience delivered by VLA 2.0 is even better. It can navigate directly to a parking space with both efficiency and safety.

I believe that as we upgrade computing power and model capabilities, VLA 2.0 will develop even more powerful capabilities over the next several version upgrades, delivering an L4 level ADAS experience in mass-produced vehicles, surpassing peers and establishing a generational lead. We continue to enhance VLA 2.0's model capabilities whilst accelerating its global deployment. Recently, my team and I completed on-road validation of VLA 2.0 in Germany and which was particularly encouraging was that the model primarily trained on data from China performed nearly as well on the European urban roads as it did in China with almost no additional local training data.

We aim to obtain regulatory approval for VLA 2.0 in Europe first in the first half of next year and roll out VLA 2.0, bringing a safer, more comfortable and more convenient driving experience to users worldwide. After deploying in overseas market, VLA 2.0 will compete directly with the world's leading ADAS and become XPeng's defining competitive advantage for our global products. At the same time, we will actively explore new software-based business models, creating a positive cycle in which commercialization and technology development reinforce each other.

As of now, our pre-installed mass-produced Robotaxi powered by VLA 2.0 has completed more than 2,000 internal test orders in Guangzhou and validated the full end-to-end process for trial passenger operations, laying the groundwork for commercial operations. Recently, we have completed the development of our cloud remote takeover platform, and our goal is to begin passenger operations without a safety operator in the car next year. In 2027, XPeng will continue strengthening the technology and cost competitiveness of our Robotaxi while partnering with leading domestic and international mobility platforms to expand our Robotaxi business across key cities in China and around the world. This will create greater commercial value through vehicle sales technological services and revenue sharing from operations.

In the meantime, we believe that the large-scale application of physical AI requires more than technological breakthroughs, an open and collaborative technology and business ecosystem that creates value for multiple participants is equally important. To accelerate the commercialization of physical AI, we recently established a group level business development team within the group and are actively engaging with the partners in China and overseas to bring our industry-leading Turing AI chips, VLA 2.0, Robotaxi and humanoid robots technologies to global markets more quickly. For the third quarter of 2026, we expect deliveries to be approximately 115,000 to 121,000 units, representing quarter-over-quarter growth of 11.3% to 17.1%.

Revenue is expected to be approximately RMB 21.7 billion to RMB 23.4 billion, representing quarter-over-quarter growth of 9.9% to 18.5%. I believe XPeng is entering a period of accelerating momentum across multiple business in the second half of the year. Both domestic and overseas vehicle deliveries are expected to reach new highs. We also expect to be among the first globally to achieve scaled mass production and commercialization of advanced general-purpose humanoid robots. We also expect to be among the first to deploy advanced ADAS technologies in overseas markets, and we will establish new business models around the physical AI ecosystem, creating greater value for customers and shareholders worldwide. Thank you, everyone.

With that, I will now turn over the call to our VP of Finance, James, who will walk you through our financial performance for the second quarter of 2026.

Jiaming Wu: Thank you, Xiaopeng. Now let me provide a brief overview of our financial results for the second quarter of 2026. I will reference RMB only in my discussion today, unless otherwise stated. Our total revenues were RMB 19.74 billion for the second quarter of 2026, an increase of 8% year-over-year and an increase of 51.5% quarter-over-quarter. Revenues from vehicle sales were RMB 17.05 billion for the second quarter of 2026, an increase of 1% year-over-year and an increase of 55% quarter-over-quarter. The quarter-over-quarter increase was mainly attributable to higher vehicle deliveries. Revenues from services and others were RMB 2.7 billion for the second quarter of 2026, representing an increase of 93.9% year-over-year and an increase of 32.6% quarter-over-quarter.

The year-over-year and quarter-over-quarter increases were primarily attributable to the increased revenues from, first, technical R&D services rendered to the Volkswagen Group due to the successful achievement of certain key milestones and secondly, parts and accessory sales. Gross margin was 20.7% for the second quarter of 2026 compared with 17.3% for the same period of 2025 and 20.6% for the first quarter of 2026. Vehicle margin was 12.1% for the second quarter of 2026 compared with 14.3% for the same period of 2025 and 12.1% for the first quarter of 2026. The year-over-year decrease was primarily due to the production generation transition.

R&D expenses were RMB 2.91 billion for the second quarter of 2026, representing an increase of 32.1% year-over-year and an increase of 0.3% quarter-over-quarter. The year-over-year increase was mainly due to higher expenses related to the development of new vehicle models and AI-related technologies as the company expanded its product portfolio to support the future growth. SG&A expenses were RMB 2.5 billion for the second quarter of 2026, representing an increase of 15.2% year-over-year and an increase of 32.5% quarter-over-quarter. The year-over-year increase was primarily due to higher marketing and advertising expenses the quarter-over-quarter increase was primarily due to the higher commission to the franchise stores and higher marketing and advertising expenses.

As a result of the foregoing, loss of operations was RMB 1.14 billion for the second quarter of 2026 compared with RMB 0.93 billion year-over-year and RMB 1.87 billion quarter-over-quarter. Net loss was RMB 1.34 billion for the second quarter of 2026 compared with net loss of RMB 0.48 billion year-over-year and net loss of RMB 1.7 billion quarter-over-quarter. As of June 30, 2026, our cash position was RMB 40.48 billion. To be mindful of the length of the earnings call, I would encourage listeners to refer to our earnings press release for more details on our second quarter 2026 financial results. This concludes our prepared remarks. We'll now open the call to questions. Operator, please go ahead.

Operator: [Operator Instructions] Your first question today comes from Tim Hsiao with Morgan Stanley.

Tim Hsiao: [Foreign Language] So my first question is about volume and production target. So what is the projected production capacity for XPeng humanoid robot IRON upon entering commercial mass production by late 2026? And what is the target delivery volume for fiscal year 2027? That's my first question.

He Xiaopeng: [Interpreted] Thank you for your question. This is Xiaopeng speaking. In terms of robot capacities versus automobile capacities, from our perspective, we do think that there is quite a large difference between those two. I think that when it comes to the capacities of the supply chain of robots, it is rather broad and deep. But in our company, we emphasize on multiple areas of full-stack research and development. And I think when it comes to about the challenges of capacities in the early stage, it is about quality. And in the later stage, it is about sales.

In terms of mass production for 2026, and we expect that by year-end of 2026, we will see mass production at scale kicking in. For IRON, this product, and we believe that we will see the commercialization of the robot itself first starting with our stores. And in 2027, we will see that the commercialization will take place in the different areas of our own self-operated scenarios and rolling out as well as picking up the speed to external commercialization and user case scenarios.

In terms of R&D, and I think that we are looking at starting from the mid and second half of next year in 2027, we will pick up the R&D development and the mass production units will be at multiple of several thousand units per month and further picking up the speed. One final part that I would like to supplement, which is that for the IRON robot deliveries, and this will mainly be rolled out in the areas of retail and services, both in China and abroad. And same as our automotive business, the delivery of our robots and sales will be authentic and genuine data and the figures that we will share.

In terms of the quality of our robots services that it can provide, I believe that versus the other peers out there in the market when it comes to either the shopping assistance perspective or the intelligence level, we will definitely be better and stronger than the others as well as to be able to be used in a more wider and broader more adaptive environment.

Tim Hsiao: [Foreign Language ] My second question is about the unit economics and margin profile. So what is the estimated unit cost for the mass production variant of IRON? And what go-to-market pricing strategy does management intend to deploy? And what is the anticipated gross profit margin trajectory, especially after the full-scale ramp? That's my second question.

He Xiaopeng: [Interpreted] Thank you for your question. With respect to the mass produced robots, and I think that we are looking at from the perspective of innovation, quality, capacity and all of these for both our hardware and software. We're looking at doing the R&D research all in-house. And when it comes to the supply chain of all these parts, actually, over 85% of the supply chain partners that we work with actually overlap with the existing supply chain partners for our automotive business. I believe the cost of our robots, IRON robots competitiveness will definitely be leading in this area.

At the moment, in terms of the pricing for robots in the market, generally speaking, it's about 2.5 to 3x of the [ BOM ] material. For IRON, given that this is a general purpose robot and there is a very limited supply in the market, and I do believe that for our gross margins of the hardwares will definitely be better than the existing automotive business. In the meantime, not only that we are relying on the sales of the hardware, there will also be sales of our different models and the software services, subscriptions, et cetera. These we believe will all bring in profits for our business. Those Concludes my answers to your questions.

Operator: Your next question comes from Ming-Hsun Lee with Bank of America.

Ming-Hsun Lee: [Foreign Language ] Which part of your robot foundation model can be highly synergistic with autonomous driving, which modules are shared and which are developed relatively independently?

He Xiaopeng: [Interpreted] Thank you for your question. And in order to answer this question, in our industry, for instance, many people will say that in robots, generally, all they need is one brain and one large model that will be enough. Perhaps this is possible many years later, but I don't think that is viable as of now. In terms of the different large models, and there are different types. For instance, we have the super fast models, and those are operating at 100 frame per second or even several hundred frame per second. There are these medium speed models, large models and which are operating at 10 frames to 20 frames per second.

And there are also the slow ones and slow large models, we call them the thinking large models. They operate at 1 frame per second. When it comes to the VLA and VLM and for instance, and those are the ones adopted in our automotive business. I believe there are similarities. And for instance, the currently VLA adopted in the automotive business when it comes to the roaming in non-planned roads, and that will be quite similar to the roaming or moving around of the robots.

For robots, on the other hand, I also believe that some of the thinking capabilities of robots such as on the open platform next year can also be put into use for our XPeng’s automotive business. So you can see that there are definitely some synergistic commonalities there. In the meantime, there are also some unique perspective and the points of the robots and such as the different mode for safety. And for instance, there are the models of safety such as data privacy and safety about prevention of [ falling ] and data safety about lack of running out of electricity, et cetera.

So as you can see, there are commonalities and all of these features we are developing under the large XPeng system altogether. And even so and if we look at the further underlying system, and there are many other areas that are quite similar, for instance, the generation of the generative models and as well as the mimicking and the simulation models, et cetera. So those are the similarities.

Sorry, before you move on to your second question, and I would also like to supplement that apart from the models and whether it is about the AI applications or the applications of the overall architecture and structure, and these are also the ones that we do share across the two different parts of the business.

Ming-Hsun Lee: [Foreign Language ] What Differentiated advantages does XPeng have in robot data collection, training and closed-loop iteration?

He Xiaopeng: [Interpreted ] Thank you. That is a great question. And I do believe that in terms of the physical AI and in the future and data is, of course, the key. Many people say that as long as you have enough data and that will help with the integration of the services. It is a necessary condition. However, it is not yet the full condition. And what we would see is that for XPeng and what we are good at is that we have much better data and the training of the data, we also have a higher quality of the data.

For XPeng, for instance, we have been in the area of autonomous driving for over 10 years within not only our R&D for the past over a decade of experience as well as the data that we have collected, we are absolutely leading in the industry among our peers. In terms of the robots, it is the same. For the robots data management, data training and data quality, all of these are being developed under the same ecosystem at our company.

And I believe that apart from the hardwares being different in terms of the collection of the data and all the way to the application of the data at our company for our 2 different lines of business would be the same. For IRON, again, once these products become mass produced and launched into the market, not only that we will be further continuing to collect real-world data as well as the human demonstrated data and which are both sets of high-quality data, and this will further drive the development and R&D of our product. And this is different from the low-quality data and which are not helpful at all.

So I believe that by having all of these, we'll actually be able to create a flywheel of the high-quality data and the R&D that we are conducting and continue to contribute to the development of our products. That's all my answer for your question. Thank you.

Operator: The next question comes from Jeff Chung with Citi.

Ming Chung: [Foreign Language] My first question is about why did XPeng Robotics select the salesperson, the tour guide scenario as an initial real-world deployment. Who are the target customers? Why would customers buy IRON? And most importantly, are there follow-up plans to expand into industrial and home use cases?

He Xiaopeng: [Interpreted ] Thank you very much for your question. For XPeng's robots, yes, indeed, when it comes to commercialization, we have gone down a different route versus other competitors. Many other competitors, they are focusing on breaking into the market by ways of entering into factories, home usage and mainly for [ B2B ] business. What we are looking at is that we are focusing on the large-scale Cs as well as the small and medium Bs. And that is, so to speak, we start entering into the market with business commercialization cases followed by industries and home uses at a later stage with the smaller SKUs. The reason we have picked the salespersons and tour guides, et cetera.

It is because that we believe both in China and abroad, and there are 4 major comprehensive capabilities of our robots that are very helpful and would be able to be reflected very well in these sectors. And the 4 comprehensive capabilities are as follows: Number one is the main body and the main hardware of the robots itself; number two, the environment; number three, the business that it provides; and number four, the emotional values that it brings. Therefore, starting from commercial usage cases and starting from the smaller type of business and the smaller and medium type of business industries that we go in.

And later on with IRON, of course, when it starts opening up the market, and we will also open up SDKs to enable secondary development as well as further expand its user cases. With these commercial use scenarios for collaboration, and we believe that this will also open up more channels for XPeng's robots business, not only for offline sales, but as well as for online sales so that our customers would be able to see the use cases for our robots and not only for the big customers but as well as for the small and medium business. So this is our thinking in the regard and which is different from our peers.

Ming Chung: [Foreign Language] The second question is about the latest progress on the company's self-developed dexterous hand. What overall design approach has been adopted? And how does it compare with peers in terms of performance and cost?

He Xiaopeng: [Interpreted ] Thank you very much for your question. And yes, indeed, dexterous hand is an extremely important part for robots. And for our robots, and we have one set of hardware, one set of software as well as 3 sets of different perceptive systems. In terms of the specific mass production plans, we will be communicating with the analysts by year-end. We are not only just conducting the R&D of dexterous hand, and we have also invested greatly into the manufacturing of the processing of dexterous hand as well as the equipment in this regard.

The dexterous hand for our robots, and we have 21 degrees of freedom, as mentioned earlier, in terms of the size of the product of the dexterous hand, it is the exact same size as the hand of an adult. And when it comes to the load-bearing capabilities as well as grasping and gripping, we believe that our dexterous hand is in the leading position versus the other peers. I know that in the industry that people often talk about another type of hand, and we do not think that is the smart choice to go for. We are not focusing on the force or the accuracy itself of dexterous hand.

And what we are focusing on rather is on striking a good balance of safety, reliability, easy to maintain and cost. And for instance, our dexterous hand also has a very nice set of skin that is very similar to the human hand.

Operator: Your next question comes from Nick Lai with JPMorgan.

Y.C. Lai: [Foreign Language] First question is really about the ADAS technology chairman mentioned that in first half '27, we'll start to deploy a model in overseas market, starting from Germany with the VLA 2.0 technology. I wonder how many models will be equipped with such technology in overseas market? And also, can you elaborate a bit more about our business model, including subscription and onetime payment strategy in the long term in overseas market.

He Xiaopeng: [Interpreted] Thank you very much for your question. Given that the signal wasn't coming through very clearly, and I could only hear some keywords of your questions. So I'll try my best to answer your question based on what I have heard. Number one, with respect to the Turing AI chips, and this has already been deployed to our L03 vehicles for the ones that which are launched to the overseas market as well, and all of these will have the Ultra version. For VLA, and this will be deployed in L03 models across all different markets.

And in the meantime, we're also catching up and working with the compliance and local laws and regulations and localization work, testing, all of these are being done at the same time in tandem. And in the meantime, we are looking at for instance, about the subscription service of the software for our customers and such updates will be announced and shared with you all in due course. We have also established another BD team, and this team is actively discussing with our partners and with respect to the VLA usage or even further expanded into other areas.

Operator: Your next question comes from Tina Hou with Goldman Sachs.

Tina Hou: [Foreign Language] So my first question is regarding -- so with the volume production of our humanoid robot product. And also congratulations on the announced equity raising today. Just wondering what would be the expected time line of profitability for humanoid robot business? Or in other words, what level of sales volume should we achieve in order to become profitable? Also related to that, do we have any plans to report our profit level separately for the humanoid robot as well as the auto business so that I think the market investors could have a better understanding of the profitability of these 2 separate businesses.

Gui Hongdi: Tina, it's Brian. Let me address your question. With regard to the financial outlook of the robotic business, I think it's bit too early for us to comment. I would say we are now focused on the milestones that Xiaopeng shared, which is reach SOP for our robots for volume production capability by the end of this year and also start deploying first in our internal scenarios and gradually offer to external customers starting, I would say, the first half of next year and gradually ramp up from that. So that's our goal. I would say it's too early for us to provide a volume prediction guidance.

On the profitability, we anticipate the product of human robot will achieve much higher gross profit potential compared to the automotive business. In fact, I would say it's -- the hardware is already much higher than the automotive business. In addition to that, we think there will be significant opportunities to add on future AI model training, upgrade, software capability related revenues, which is much higher margin as well. So given the high profitability, I would say, expectation as well as, I would say, much smaller investment and CapEx requirement for robotic business. I would say once volume ramp-up is achieved, I would say probability can become reality much faster than the auto business. So that's our projection.

And also to answer your question regarding the potential separation of the businesses. At the moment, actually, the business are operating together. In fact, we have not started any separation of the business. We obviously, according to the announcement you saw, we actually have a period of 18 months that gradually allow us to achieve a separation. But in the meantime, what we're going to be focused on still achieving high degrees of synergy because we talked about leveraging the capabilities in AI, the capability on sort of advanced manufacturing, powertrain, supply chain, so forth. So actually, the 2 business can both achieve high efficiency and greater, I would say, capabilities.

So with that, I think the near-term expectation is it will still be mostly viewed together as a business. And also as the volume production and also as the commercialization scenarios become more clear, we'll probably think about more likely separations. But in any event, given the ownership structure, this business will be 100% consolidated. It will not impact our financials going forward, even though the business may start to separate based on the plan. So I think in short, we still see the group consolidating all the financials of the robotic business. At the same time, we'll really think about the most efficient and also most synergistic way to run the business.

Operator: That concludes the question-and-answer session. Now I'd like to turn the call back over to the company for closing remarks.

Alex Xie: Thank you once again for joining us today. If you have further questions, please feel free to contact XPeng's IR team through the contact information provided on our website or the Piacente Financial Communications.

Operator: This concludes today's conference call. You may now disconnect your line. Thank you.

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