Q3 2025 Pony.ai Inc Earnings Call

November 25, 2025

Hey hello, ladies and gentlemen, thank you for standing by and welcome to Pony. AI inks third quarter 2025 earnings conference call. At this time, all participants are in a listen-only mode. After the Management's prepared remarks, there will be a question and answer session. As a reminder, today's conference call is being recorded and a webcast replay will be available on the company's investor relations website at irpp under the news and events section. I will now turn the call over to your host. George Chao head of capital markets and investor relations at Pony AI. Please go ahead. George

George Xiao: Thank you, Operator. Hello, everyone. We appreciate you joining us today for Pony AI's Q3 2025 earnings call. Earlier today, we issued a press release with our financial and operating results, which is available on our investor relations website. An earnings presentation, which we'll refer to during this conference call, can also be accessed and downloaded on our investor relations website. Joining with me on the call today are Dr. James Peng, Chairman of the Board and Chief Executive Officer, Dr. Tiancheng Lu, Chief Technology Officer, and Dr. Liu Wang, Chief Financial Officer of the company. They will provide prepared remarks, followed by a Q&A session. Before we begin, please refer to the safe harbor statement in our earnings release, which applies to this call as we'll be making forward-looking statements.

George Shao: Thank you, Operator. Hello, everyone. We appreciate you joining us today for Pony AI's Q3 2025 earnings call. Earlier today, we issued a press release with our financial and operating results, which is available on our investor relations website. An earnings presentation, which we'll refer to during this conference call, can also be accessed and downloaded on our investor relations website.

We appreciate you joining us today for Pony.ai's third quarter 2025 earnings call.

Earlier today, we issued a press release with our financial and operating results.

Which is available on our investor relations website.

Joining with me on the call today are Dr. James Peng, Chairman of the Board and Chief Executive Officer, Dr. Tiancheng Lu, Chief Technology Officer, and Dr. Liu Wang, Chief Financial Officer of the company. They will provide prepared remarks, followed by a Q&A session. Before we begin, please refer to the safe harbor statement in our earnings release, which applies to this call as we'll be making forward-looking statements.

And the earnings presentation, which will be referred to during this conference call, can also be accessed and downloaded on our Investor Relations website.

Joining me on the call today are Haojun Wang and Jun Peng.

Dr. James Kong, Chairman of the Board and Chief Executive Officer.

Dr. The Engine Low, Chief Technology Officer, and Dr. Leo Wang, Chief Financial Officer of the company.

They will provide prepared remarks, followed by a Q&A session.

Before we begin, please refer to the safe harbor statement in our earnings press release.

George Xiao: Please also note that we'll discuss non-GAAP measures today, which are more thoroughly explained and reconciled to the most comparable measures reported under GAAP in our earnings release, available on our investor relations website and filings with the SEC and Hong Kong Stock Exchange. I will now hand it over to our Chairman and CEO, Dr. James Peng. Please go ahead.

Please also note that we'll discuss non-GAAP measures today, which are more thoroughly explained and reconciled to the most comparable measures reported under GAAP in our earnings release, available on our investor relations website and filings with the SEC and Hong Kong Stock Exchange. I will now hand it over to our Chairman and CEO, Dr. James Peng. Please go ahead.

Which applies to this call, as we will be making four looking statements.

It's also noted that we will discuss non-GAAP measures today.

Which are more thoroughly explained and reconciled to the most comparable measures reported under GAAP in our earnings release available on our investor relations website and following with the ICC and Hong Kong Stock Exchange.

I will now hand it over to our Chairman and CEO, Dr. James Pong. Please go ahead.

James Peng: Thank you, George. Hello, everyone. Thank you for joining our earnings call. I'm excited to share that we have successfully completed the dual primary listing on the Hong Kong Stock Exchange under stock code 2026 on 6 November 2023, just one year after our Nasdaq listing. With strong support from both international and domestic investors, we secured the largest IPO in the global autonomous driving sector this year, raising more than $800 million. This significantly strengthens our balance sheet and provides the dry powder to accelerate mass production and large-scale commercialization. We now expect stronger growth, surpassing 1,000 robotaxi fleet plans by year-end, and expanding to more than 3,000 vehicles for 2026. We have already seen the flywheel in action. Expanded fleet is driving higher user adoption, shorter wait time, more orders, and strong revenue growth. After launching Gen7 Robotaxi, we have already seen a citywide unit economics break-even.

Thank you George. Hello everyone.

Thank you for joining our Q3 2025 Pony.ai Inc. earnings call.

I'm excited to share that we have successfully completed the primary listing on the Hong Kong Stock Exchange.

With strong support from both international and domestic investors.

We secured the largest IPO in the global autonomous driving sector this year.

Raising more than

This significantly strengthens our balance sheet and provides the dry powder to accelerate mass production and large-scale commercialization. We now expect stronger growth, surpassing 1,000 robotaxi fleet plans by year-end, and expanding to more than 3,000 vehicles for 2026. We have already seen the flywheel in action. Expanded fleet is driving higher user adoption, shorter wait time, more orders, and strong revenue growth. After launching Gen7 Robotaxi, we have already seen a citywide unit economics break-even.

800 million US dollars.

And the largest scale, commercialization.

We now expect stronger growth.

Surpassing 1,000 robot taxis by the end of the year and expanding to more than 3,000 vehicles by 2026.

We have already.

Seen the fly. Well, in action, expanded fleet is driving higher user adoption.

Shorter wait times, more orders, and strong revenue growth.

After launching the Gen7 robot taxi, we have already seen a citywide unit economics break even.

James Peng: This, in turn, gives us more room to increase fleet size. The capital we raised also fuels our business development, research and development, making strategic investments in new markets, new applications, and attracting world-class AI talents. All these are set to further propel our technology leadership and the long-term growth. Our Hong Kong IPO also powers our core mission: bringing autonomous mobility to everyone around the world. We're firmly delivering on this commitment. Earlier this month, we officially launched fully driverless commercial service for Gen7 Robotaxis across Guangzhou, Shenzhen, and Beijing. Today, our management team, including myself, actually arrives at our Shenzhen office in a fully driverless Gen7 Robotaxis to host this conference earnings call. This is more than just a normal ride for us. It actually marks a giant leap in autonomous driving's advancement.

This, in turn, gives us more room to increase fleet size. The capital we raised also fuels our business development, research and development, making strategic investments in new markets, new applications, and attracting world-class AI talents. All these are set to further propel our technology leadership and the long-term growth. Our Hong Kong IPO also powers our core mission: bringing autonomous mobility to everyone around the world. We're firmly delivering on this commitment. Earlier this month, we officially launched fully driverless commercial service for Gen7 Robotaxis across Guangzhou, Shenzhen, and Beijing.

This, in turn, gives us more room to increase fleet size.

The capital we raised also fuels our business development.

Research and development.

Market making strategic investments in new markets.

New applications.

And attracting world-class AI talents.

All these are sent to further Propel, our technology leadership, and the long-term growth.

Our Hong Kong IP also powers our core mission.

Bringing autonomous mobility to everyone around the world.

We are firmly delivering on this commitment.

Today, our management team, including myself, actually arrives at our Shenzhen office in a fully driverless Gen7 Robotaxis to host this conference earnings call. This is more than just a normal ride for us. It actually marks a giant leap in autonomous driving's advancement.

Earlier this month, we officially launched fully driverless commercial service for Gen 7 Global Taxis across Guango, Shenzhen, and Beijing.

Today, our management team, including myself, actually arrives at our Shenzhen office in fully driverless Gen 7 RoboTaxis to host this conference earnings call.

This is more than just a normal ride for us. It actually marks a giant leap in Aton's driving advancement.

James Peng: We are making Level 4 autonomy more accessible than ever to a much broader user base. I'm excited to share a critical milestone. Our Gen7 Robotaxis have reached city-level UE break-even in Guangzhou shortly after their official commercial launch. This is pivotal to validate our viable business model. It not only gives us strong confidence to further scale our fleet, but also attracts more and more third-party partners, enabling them to fund our fleet and support our asset-light model. The scaling up of a fleet is key to our growth, as large-scale operational footprint drives efficiency through the economy of scale. Our robotaxi vehicles are essentially moving billboards. In fact, many new users discover and download our Pony Pilot app after spotting our vehicles on the road for daily operation. Fleet expansion serves as a highly efficient, self-reinforcing marketing engine, facilitating user adoption and strengthening brand recognition.

We are making Level 4 autonomy more accessible than ever to a much broader user base. I'm excited to share a critical milestone. Our Gen7 Robotaxis have reached city-level UE break-even in Guangzhou shortly after their official commercial launch. This is pivotal to validate our viable business model. It not only gives us strong confidence to further scale our fleet, but also attracts more and more third-party partners, enabling them to fund our fleet and support our asset-light model.

We are making Level 4 autonomy more accessible than ever to a much broader user base.

I'm excited to share a critical milestone.

Our Gen 7 global taxes have reached city-level year-over-year break even in Gwangju.

Shortly after their official commercial launch.

This is pivotal to validate our viable business model.

It not only gives us strong confidence to further scale our fleet.

But also attract more and more third-party partners.

The scaling up of a fleet is key to our growth, as large-scale operational footprint drives efficiency through the economy of scale. Our robotaxi vehicles are essentially moving billboards. In fact, many new users discover and download our Pony Pilot app after spotting our vehicles on the road for daily operation. Fleet expansion serves as a highly efficient, self-reinforcing marketing engine, facilitating user adoption and strengthening brand recognition.

Enabling them to find our fleet and the support of our asset-light model.

The scaling up of a fleet is key to our growth on a large scale. Operational footprint drives efficiencies through the economy of scale.

Our RoboTaxi vehicles are essentially moving billboards. In fact, many new users discover and download our Pony Pilots.

App.

After spotting our vehicles on the road for daily operation.

Fleet expansion serves as a highly efficient self-reinforcing marketing engine.

Facilitating user adoption and strengthening brand recognition.

James Peng: This creates a powerful upward spiral, as more vehicles generate greater visibility, which attracts more users and establishes network effects. The results are already evident. Building on that momentum, new registered users nearly doubled within just one week of launching Gen7 from late October, reflecting robust user demand and an effective go-to-market strategy. Now, let me highlight some key advances we've made in recent months in executing our scale-up strategy. First, we have ramped up production at an accelerating pace since the start of production in the middle of this year. By November, more than 600 Gen7 Robotaxis had rolled off our assembly lines, bringing the total fleet size to be over 900 vehicles. Thanks to the streamlined production process, we now expect to outperform our full-year target of 1,000 vehicles, delivering ahead of schedule.

This creates a powerful upward spiral, as more vehicles generate greater visibility, which attracts more users and establishes network effects. The results are already evident. Building on that momentum, new registered users nearly doubled within just one week of launching Gen7 from late October, reflecting robust user demand and an effective go-to-market strategy. Now, let me highlight some key advances we've made in recent months in executing our scale-up strategy.

This creates a powerful upward spiral; more vehicles generate greater visibility, which attracts more users and establishes.

Network effects.

The results are already evident.

Building on that momentum, new registered users nearly doubled within just one week of the event.

launching Gen 7 from late October.

Reflecting robust user demand and the effective go-to-market strategy.

First, we have ramped up production at an accelerating pace since the start of production in the middle of this year. By November, more than 600 Gen7 Robotaxis had rolled off our assembly lines, bringing the total fleet size to be over 900 vehicles. Thanks to the streamlined production process, we now expect to outperform our full-year target of 1,000 vehicles, delivering ahead of schedule. This gives us increasing confidence to sustain robust momentum, driving fleet size to surpass 3,000 vehicles in 2026.

Now, let me highlight some key advancements that were made in recent months in executing our scale-up strategy.

First, we have ramped up production at an accelerating pace.

Since the start of production in the middle of this year.

By November, more than 600 Gen7 RoboTaxis.

Had rolled off.

Our assembly lines.

Bringing the total fleet size to be over 900 vehicles.

The production process, we now expect to outperform our 4-year target of 1,000 vehicles.

Delivering ahead of schedule.

James Peng: This gives us increasing confidence to sustain robust momentum, driving fleet size to surpass 3,000 vehicles in 2026. Second, in Q3, our robotaxi revenue surged by 90% year-over-year, with fare charging revenues delivering over 200% year-over-year growth. This was fueled by rising user adoption across all four Tier 1 cities, improved fleet operational efficiency, and tailored pricing strategies for diverse user segments. We have seen that the higher order density leads to lower users' average waiting time, and, in turn, higher vehicle utilization rate. This allows us to continuously optimize our pricing strategy. Third, we have continued to expand our operational footprint. For example, in Shanghai, we became the city's first company to launch fully driverless commercial robotaxi operations earlier this July, covering the Jinqiao and Huamu areas of Pudong. In Shenzhen, we extended commercial fully driverless operations to more and bigger city areas, including Shekou and Overseas Chinese Town.

This gives us increasing confidence to sustain robust momentum.

Second, in Q3, our robotaxi revenue surged by 90% year-over-year, with fare charging revenues delivering over 200% year-over-year growth. This was fueled by rising user adoption across all four Tier 1 cities, improved fleet operational efficiency, and tailored pricing strategies for diverse user segments. We have seen that the higher order density leads to lower users' average waiting time, and, in turn, higher vehicle utilization rate. This allows us to continuously optimize our pricing strategy.

Driving fleet size to surpass 3,000 vehicles in 2026.

In Q3, our robotaxi revenue...

Searched by 90% year-over-year with fair charging revenues, delivering over 200% year-over-year growth.

This was sealed by rising user adoption across all four Tier 1 cities.

Include fleet, operational efficiency, and payload pricing strategies for diverse user segments.

We have seen that the higher order density leads to lower users' average reading time and, in turn, higher vehicle utilization rate.

Third, we have continued to expand our operational footprint. For example, in Shanghai, we became the city's first company to launch fully driverless commercial robotaxi operations earlier this July, covering the Jinqiao and Huamu areas of Pudong. In Shenzhen, we extended commercial fully driverless operations to more and bigger city areas, including Shekou and Overseas Chinese Town.

This allows us to continuously optimize our pricing strategy.

Third.

We have continued to expand our operational footprint.

For example, in Shanghai, we became the city's first company to launch fully driverless commercial global taxi operations.

Earlier this July.

covering the Jing Chao and the Hu areas of Pluto.

In Shenzhen, we extended commercial, fully driverless operations to more.

And bigger city areas, including Circle and Overseas Chinese Town.

James Peng: Fourth, we're taking major steps toward scalable mobility.

Fourth, we're taking major steps toward scalable mobility.

Both.

Were taking major steps toward.

uh,

scalable Mobility.

Operator: Excuse me, I believe there has been an interruption. Just one moment, please.

Excuse me, I believe there's been an interruption.

just 1 moment, please.

James Peng: Sorry.

Sorry.

Operator: Excuse me. I've rejoined management. Please continue. Thank you.

Excuse me. I've rejoined management. Uh, please continue. Thank you.

James Peng: Sure. I was talking about the scale-up strategy. Following our collaboration with Shenzhen Sihu Group in June, we recently forged another partnership with Sunlight Mobility. These alliances reflect growing market recognition of our business model, with an increasing number of third parties wanting to fund fleet deployment. This actually enables us to speed up further fleet expansion. Now, let me turn to our global expansion. We are deeply dedicated to advanced robotaxi services while strategically expanding our international fleet. Now, we have robotaxi presence established in eight countries across China, the Middle East, East Asia, Europe, and the US. We entered a new market in the Middle East, Qatar, through a partnership with Mowasalat in Q3. Mowasalat is the country's largest transportation service provider. As part of this collaboration, our robotaxis have recently begun testing on public roads in Doha, the capital of Qatar.

Sure, um, I was talking about the, uh, scale-up strategy.

So, following our collaboration with He Who in June, we recently forged another partnership with Sunlight Mobility.

This aligns with the growing market recognition of our business model.

with, uh, increasing number of

Third parties.

Wanting to find Fleet deployment.

Now, let me turn to our global expansion. We are deeply dedicated to advanced robotaxi services while strategically expanding our international fleet. Now, we have robotaxi presence established in eight countries across China, the Middle East, East Asia, Europe, and the US. We entered a new market in the Middle East, Qatar, through a partnership with Mowasalat in Q3. Mowasalat is the country's largest transportation service provider. As part of this collaboration, our robotaxis have recently begun testing on public roads in Doha, the capital of Qatar.

This actually enables us to speed up further fleet expansion.

Now, let me turn to our global expansion.

We are deeply dedicated.

To Advanced Global Taxi Services, while strategically expanding our international fleet.

Now, we have RoboTaxi presence established in 8 countries across China, the Middle East, East Asia, Europe, and the U.S.

We entered.

A new market in the Middle East, Qatar. So, a partnership with Nova Salet in the third quarter.

No, is the country.

Largest transportation service provider.

As part of this collaboration, our robo-taxis have recently begun testing on public roads in Doha, the capital of Qatar.

James Peng: We have also advanced our presence in South Korea by securing nationwide robotaxi permits, enabling operation across the country's autonomous testing and operational zones. Our collaboration with local partners continues to deepen. We are collaborating closely with Mowasalat, the country's largest transportation service provider, to begin road testing. In Luxembourg, we plan to deploy testing vehicles based on the Peugeot e-Traveller through our alliance with Stellantis. It's a European leader in light commercial vehicles. This effort will initially focus on vehicles designed for Europeans' diverse mobility needs, to enable a range of use cases. In addition, we have partnered with global ride-hailing platforms that also participated in our Hong Kong IPO. Those platforms include Uber and Bolt. Bolt is an Estonia-based mobility company operating in over 50 countries and 600 cities.

We have also advanced our presence in South Korea by securing nationwide robotaxi permits, enabling operation across the country's autonomous testing and operational zones. Our collaboration with local partners continues to deepen. We are collaborating closely with Mowasalat, the country's largest transportation service provider, to begin road testing. In Luxembourg, we plan to deploy testing vehicles based on the Peugeot e-Traveller through our alliance with Stellantis.

We have also advanced our processes in South Korea by securing.

Nationwide Robo, taxi permits.

Enabling operation across the country's autonomous testing and operational zones.

Our collaboration with local partners continues to deepen.

We collaborate closely with confer their growth, the country's largest transportation treat, transportation service provider to begin road testing.

It's a European leader in light commercial vehicles. This effort will initially focus on vehicles designed for Europeans' diverse mobility needs, to enable a range of use cases. In addition, we have partnered with global ride-hailing platforms that also participated in our Hong Kong IPO. Those platforms include Uber and Bolt. Bolt is an Estonia-based mobility company operating in over 50 countries and 600 cities.

Stellantis.

It's a European leader in light commercial vehicles.

This effort will initially focus on vehicles, designed for Europeans' diverse mobility needs to enable a range of use cases.

In addition, we have partnered with global right healing platforms that also participated in our Hong Kong IPO.

Those platforms include Uber and Boat.

A boat is an aeonia-based mobility company operating in over 50 countries and 600 cities.

James Peng: Built upon our collaboration with Uber, we aim to leverage Uber's robust ecosystem to enter the Middle East and then scale into additional international markets. Last but not least, we recently released our fourth-generation robo truck, with production and initial fleet deployment expected in 2026. Featuring fully automotive-grade components, optimized software-hardware integration, and a transition from internal combustion engine vehicles to electric vehicles, the Gen4 Robo Truck delivers a significantly more efficient cost structure and greater energy savings. The new platform fully leverages the technological foundation and operational expertise developed through our Gen7 Robotaxi vehicles. In addition, we deepened our collaboration with SanYi Group, and added Liuzhou Motor as a new partner to have multiple vehicles to support our further operations. To sum up, 2025 is a critical year of mass production and commercialization for Pony AI.

Built upon our collaboration with Uber, we aim to leverage Uber's robust ecosystem to enter the Middle East and then scale into additional international markets. Last but not least, we recently released our fourth-generation robo truck, with production and initial fleet deployment expected in 2026. Featuring fully automotive-grade components, optimized software-hardware integration, and a transition from internal combustion engine vehicles to electric vehicles, the Gen4 Robo Truck delivers a significantly more efficient cost structure and greater energy savings.

Built upon our collaboration with Uber, we aim to leverage Uber's robust ecosystem to enter the Middle East and then scale into additional international markets.

Last but not least, we recently released our fourth-generation Global Truck.

With production and the initial fleet deployment expected in 2026.

Featuring fully Automotive grade components.

Optimized software-hardware integration and the transition from internal combustion engine vehicles.

To electric vehicles.

The Gen 4 robot taxi and robot truck deliver significant advancements.

The new platform fully leverages the technological foundation and operational expertise developed through our Gen7 Robotaxi vehicles. In addition, we deepened our collaboration with SanYi Group, and added Liuzhou Motor as a new partner to have multiple vehicles to support our further operations. To sum up, 2025 is a critical year of mass production and commercialization for Pony AI.

More efficient cost structure and greater energy savings.

The new platform fully leverages the technological foundation and operational expertise.

Developed through our Gen 7 RoboTaxi vehicles.

In addition, we deepened our collaboration with SI Group and added Leo Moto as a new partner to have multiple vehicles.

To support.

Our further operations.

To sum up 2025.

Is the critical year of mass production and commercialization for Pony.ai?

James Peng: We take pride in the progress we have made and are steadily delivering on the promise we have made to our shareholders at the time of our US IPO last year. Our recent Hong Kong listing not only marks a major milestone for our company, but also underscores the promising future of the industry. Moving forward, we will drive technological innovation and create lasting values by scaling fast, efficient, and comfortable autonomous mobility services toward our mission: autonomous mobility everywhere. With that, now I'll hand it over to our CTO, Dr. Tiancheng Lu, to share more about our technology strategies. Tiancheng, please go ahead.

We take pride in the progress we have made and are steadily delivering on the promise we have made to our shareholders at the time of our US IPO last year. Our recent Hong Kong listing not only marks a major milestone for our company, but also underscores the promising future of the industry.

We take pride in the progress we made and in steadily delivering on the promise we made to our shareholders at the time of our U.S. IPO last year.

Our recent Hong Kong listing not only marks a major milestone for our company.

Moving forward, we will drive technological innovation and create lasting values by scaling fast, efficient, and comfortable autonomous mobility services toward our mission: autonomous mobility everywhere. With that, now I'll hand it over to our CTO, Dr. Tiancheng Lu, to share more about our technology strategies. Tiancheng, please go ahead.

But it also underscores the promising future of the industry.

Moving forward, we will drive technological innovation and create lasting value by scaling fast, efficiently, and comfortably in autonomous mobility services.

The word our mission.

Autonomous Mobility everywhere.

With that, now I'll hand it over to our CTO, Dr. Tenten Law, to share more about our technology strategies.

Tent. Please go ahead.

Tiancheng Lou: Thanks, James. Hello everyone. This is Tiancheng. Let me first share my thoughts on our autonomous driving technology stack. From day one, we believed that full-stack integration across software, hardware, and operations was the only way to build a truly scalable autonomous mobility. That conviction has been validated again and again, especially for this critical year of scaling up. With the achievements we've made, it is clear the over-early technology bets help us achieve the leading position, and it will further accelerate our future growth. Our deep foresight into the tech stack is what is positioning us as a leader in the industry today, as we become one of the few companies to operate large-scale fully driverless robotaxi services. As early as 2020, we recognized the importance of training code through based on reinforcement learning unit simulation.

Hello, everyone. This is Tintin.

Let me first share my thoughts on the driving technology stack.

From day one, we believe that full-stack integration across software, hardware, and operations was the only way to build a truly scalable, autonomous mobility.

That conviction is being validated again and again, especially for this critical year of skilling up.

Our deep foresight into the tech stack is what is positioning us as a leader in the industry today, as we become one of the few companies to operate large-scale fully driverless robotaxi services. As early as 2020, we recognized the importance of training code through based on reinforcement learning unit simulation.

With achievement, we made it clear that the early technology best helps us achieve a leading position, and it will further accelerate our future growth.

Over deep foresight into the tech stack, what is positioning us as a leader in the industry today as we become one of the few companies to operate large scale, 40 Drive strong services.

To as early as 2020.

We recognize the importance of training, customer base on reinforced learning unit, simulation.

Tiancheng Lou: In that year, we transitioned our tech stack into a world model, which is what we call the Pony World today. Through years of R&D effort and real-world validation, our autonomous driving model has evolved into closed-loop training. We achieved unsupervised, self-improving iterations. In recent years, we are seeing the broader autonomous and robotic industry coverage converge on the world model, validating the approach we adopt today. This foresight in AI tech stack has given us a meaningful head start, and we are confident that we will stay ahead for multiple years. Let me dive into the three criteria that put us at the frontier forefront of world model development. First, the high-fidelity interactive simulation. This is far beyond the ability to just generate scenarios and render sensor data. Driving is by nature interactive.

In that year, we transitioned our tech stack into a world model, which is what we call the Pony World today. Through years of R&D effort and real-world validation, our autonomous driving model has evolved into closed-loop training. We achieved unsupervised, self-improving iterations. In recent years, we are seeing the broader autonomous and robotic industry coverage converge on the world model, validating the approach we adopt today. This foresight in AI tech stack has given us a meaningful head start, and we are confident that we will stay ahead for multiple years.

In that year, we transitioned transitions over text stack into a world model.

Which is what we call Pony words today.

Through years of R&D effort and real-world validation,

Over our top driving model, we have evolved into a closed-loop training.

We achieved unsupervised self-improving intuitions.

In recent years, we are seeing the broader autonomous and robotic industry coverage converge on the world model validating approach we adopted today.

Let me dive into the three criteria that put us at the frontier forefront of world model development. First, the high-fidelity interactive simulation. This is far beyond the ability to just generate scenarios and render sensor data. Driving is by nature interactive.

Next time, I'll give us a meaningful head start, and we're confident that we will stay ahead for multiple years.

Then let me dive into the three criteria that put us at the forefront of world model development.

First, the high fidelity, inactive simulation. This is far beyond the ability to just generate the scenarios and render sensor data.

Tiancheng Lou: The robotaxi's action directly affects how surrounding agents behave, such as other vehicles and pedestrians need to react to our driving behavior. It must understand and adapt to new situations and complex physical interactions in real time, mirroring true on-road interactions. It enables robotaxi operations that are safe, smooth, and socially aware. Of the 10 billion kilometers of test miles that Pony World generates each week, more than 99% capture vehicle agent interactions, while less than 1% are substatic environments such as sensor rendering. Okay, second, the ability to reproduce scale and realistic corner cases. While these long-tail scenarios don't occur frequently, they are critical to safety in autonomous driving. More importantly, every scenario must be something that could really happen in the real world, not those useless edge cases with no basic in reality. The third, the AI-based learning evaluator. This is the reward-based evaluation mechanism.

The robotaxi's action directly affects how surrounding agents behave, such as other vehicles and pedestrians need to react to our driving behavior. It must understand and adapt to new situations and complex physical interactions in real time, mirroring true on-road interactions. It enables robotaxi operations that are safe, smooth, and socially aware. Of the 10 billion kilometers of test miles that Pony World generates each week, more than 99% capture vehicle agent interactions, while less than 1% are substatic environments such as sensor rendering.

Driving is, by nature, interactive. The robotics actually affect how surrounding agents behave, such as other vehicles and pedestrians, who need to react to driving behavior.

It must understand and adapt to new situations and complex physical interactions in real time.

During true on road interactions.

It enables robot sex operations that are safe, smooth, and socially aware.

Okay, second, the ability to reproduce scale and realistic corner cases. While these long-tail scenarios don't occur frequently, they are critical to safety in autonomous driving. More importantly, every scenario must be something that could really happen in the real world, not those useless edge cases with no basic in reality.

Of the 10 billion kilometers of test miles that Pony.ai generates each week, more than 99% capture vehicle agent infections, while less than 1% are in static environments, such as sensor rendering.

Okay, second, the ability to reproduce scale and realistic corner cases.

While this long health scenario doesn't occur frequently, the weird ones are critical to safety.

In autopsy.

The third, the AI-based learning evaluator. This is the reward-based evaluation mechanism. Driving is a multiple object optimization problem. What is considered as good driving also changes in various driving scenarios. Within the closed-loop training environment, Pony World and our virtual driver are continuously evaluated on key driving metrics.

More importantly, every scenario must be something that could really have happened in the real world, not those useless age cases with no basic in real reality.

so the third the AI based learning evaluator,

Tiancheng Lou: Driving is a multiple object optimization problem. What is considered as good driving also changes in various driving scenarios. Within the closed-loop training environment, Pony World and our virtual driver are continuously evaluated on key driving metrics. This assessment does not rely on real-world data, human-labeled data, or rules. Instead, it uses an AI-powered model to learn what good driving looks like directly from outcomes, turning real and simulated experiences into a powerful cycle of self-improvement. A best-in-class world model must meet all three criteria to enable truly unsupervised and self-improving closed-loop training. This is critical to realizing large-scale driverless autonomous driving. Leveraging our full-stack technology as a core strength, I will now turn to how to drive business progress during Q3. First, on cost and operational efficiency.

This is the reward-based evaluation mechanism.

Driving is a multiple objects organization problem. What is considered good driving also changes in various driving scenarios.

This assessment does not rely on real-world data, human-labeled data, or rules. Instead, it uses an AI-powered model to learn what good driving looks like directly from outcomes, turning real and simulated experiences into a powerful cycle of self-improvement. A best-in-class world model must meet all three criteria to enable truly unsupervised and self-improving closed-loop training.

Within the cross-soap training environment, the pointing word and over-virtual driver are continuously evaluated on key driving metrics. This assessment does not rely on real-world data. Human labor data are rules.

Instead, it uses an AI-powered model to learn what a good driver looks like directly from the outcomes.

Turning real and simulated experience into a powerful cycle of self-improvement.

This is critical to realizing large-scale driverless autonomous driving. Leveraging our full-stack technology as a core strength, I will now turn to how to drive business progress during Q3. First, on cost and operational efficiency. We pioneered 100% automotive-grade autonomous driving kits for Gen7 robotaxis, which optimized the design, reducing BOM cost by 70% compared with the previous generation.

A backing class would model must meet all three criteria to enable truly unsupervised and self-improving closed-loop training.

This is critical to realizing large scale driveways out of driving.

And leveraging full stack technology as a core strength, I will now turn to how to drive business progress during the third quarter.

First on cost and operational efficiency.

Tiancheng Lou: We pioneered 100% automotive-grade autonomous driving kits for Gen7 robotaxis, which optimized the design, reducing BOM cost by 70% compared with the previous generation. The Gen7 vehicle has been officially operating for the public in Guangzhou, Shenzhen, and Beijing, fully validating our safety standards and operational efficiency. We built on our momentum and delivered further progress. Driven by scaled production and enhanced R&D, we've already realized an additional 20% reduction in the autonomous driving kit BOM cost for the Gen7 platform designed for 2026 production compared with the 2025 baseline. This lies in the foundation for sustained cost savings. Our robust AI algorithm and fleet management expertise has proven effective at driving operational efficiency. To better identify user demand in hotspot areas during rush hours, we enhance our algorithm for order dispatch, matching, and scheduling, thereby ensuring sustained, efficient robotaxi utilization.

We pioneered a 100% automotive grade auto driving kit for Gen7 Rob taxis.

The Gen7 vehicle has been officially operating for the public in Guangzhou, Shenzhen, and Beijing, fully validating our safety standards and operational efficiency. We built on our momentum and delivered further progress. Driven by scaled production and enhanced R&D, we've already realized an additional 20% reduction in the autonomous driving kit BOM cost for the Gen7 platform designed for 2026 production compared with the 2025 baseline. This lies in the foundation for sustained cost savings.

Without optimizing the design, we reduced the volume cost by 70% compared with the previous generation.

The Gen 7 V has been officially operating for public use in Guangzhou and Beijing, fully validating our safety standards and our personnel efficiency.

We build on our momentum and deliver further progress.

Driving by scaled production and enhancing IMD, we expect to realize an additional 20% reduction in the atom driving kit cost for the JSON platform designed for 2026 production compared with the 2025 baseline.

Our robust AI algorithm and fleet management expertise has proven effective at driving operational efficiency. To better identify user demand in hotspot areas during rush hours, we enhance our algorithm for order dispatch, matching, and scheduling, thereby ensuring sustained, efficient robotaxi utilization.

This slide foundation for sustained cost is $6.

Our robust AI algorithm and free management expertise have proven effective at driving operational efficiency.

Tiancheng Lou: We have also improved our virtual driver to recognize more and more complex scenarios. This allows us to improve our remote assistance to vehicle ratios substantially, on the track to reach 1:230 by year-end. Our superior service experience has become the key reason users choose Pony AI Robotaxi. After the launch of Gen7 Robotaxis, we've earned widespread positive feedback and generated great social media buzz from users. As we deliver high-quality experience, users are increasingly willing to pay a premium for the enhanced effort, reliability, and safety of our autonomous journey. For ride comfort, our advanced interactive planning capability intelligently optimizes for the frequency and magnitude of acceleration, braking, and steering. This delivers smooth, natural motion control tailored to the electric vehicles and the ride-sharing market, offering consistent comfort experience for every Pony AI Robotaxi ride.

We have also improved our virtual driver to recognize more and more complex scenarios. This allows us to improve our remote assistance to vehicle ratios substantially, on the track to reach 1:230 by year-end. Our superior service experience has become the key reason users choose Pony AI Robotaxi. After the launch of Gen7 Robotaxis, we've earned widespread positive feedback and generated great social media buzz from users. As we deliver high-quality experience, users are increasingly willing to pay a premium for the enhanced effort, reliability, and safety of our autonomous journey.

To better identify user demand in hotspot areas during rush hours, we enhance our algorithm for all the dispatch matching and scheduling. Thereby, insurance is sustained, different sustained, sustained, sustained, efficient Global Tax utilization.

We have also improved our virtual driver to recognize more and more complex scenarios. This allows us to improve the remote assistance to vehicle ratio, subsequently on the track to reach 1 to 1 to 30 by year-end.

Our superior server service experience has become the key reason users choose Flutter over taxis.

After the launch of June 7th taxes, we will earn worldwide, a wide spread of positive feedback and generate great social media buzz from users.

For ride comfort, our advanced interactive planning capability intelligently optimizes for the frequency and magnitude of acceleration, braking, and steering. This delivers smooth, natural motion control tailored to the electric vehicles and the ride-sharing market, offering consistent comfort experience for every Pony AI Robotaxi ride.

As we deliver a high-quality experience, users are increasingly willing to pay a premium for the enhanced effort, reliability, and safety of the over Atmos training.

For the right comfort, we are focusing on device inactivations planning, optimizing capabilities intelligently for the frequency and the magnitude of acceleration, braking, and selling.

Tiancheng Lou: This enhancement has reflected near-measurable improvements for Gen7, such as emergency brakes and steering over the past few months. Additionally, our robotaxi features are superior in cabin experience. We also pioneered the innovative smart repositioning feature. With one tap, users can remotely adjust their vehicle position for more convenient pickup and drop-off. We introduced voice-activated features we call the Pony AI Voice Assist, allowing users to do star trips and control air conditioning, etc. We will continuously upgrade the cabin into an AI-powered mobility terminal. Together, this upgrade creates a more accessible and streamlined user experience. Third, our tech stack is also built for generalization. The L4 native tech architecture allows us to adapt quickly to new markets and platforms. In terms of cross-region generalization, our virtual driver and showings can quickly understand and adapt to diverse traffic conditions around the world.

This enhancement has reflected near-measurable improvements for Gen7, such as emergency brakes and steering over the past few months. Additionally, our robotaxi features are superior in cabin experience. We also pioneered the innovative smart repositioning feature. With one tap, users can remotely adjust their vehicle position for more convenient pickup and drop-off. We introduced voice-activated features we call the Pony AI Voice Assist, allowing users to do star trips and control air conditioning, etc. We will continuously upgrade the cabin into an AI-powered mobility terminal.

Tell me, do the electronic vehicles and the ride-sharing market often provide a consistent comfort experience for every taxi ride?

This enhancement has reflected a magical improvement for June 7th in emergency brakes and steering over the past few months.

Additionally, our road tax features are superior in carbon experience.

We also pioneered the innovative smart positioning feature, allowing users to remotely adjust their vehicle positions with one tap for more convenient pickup and drop-off.

We introduced the Voice active features, which we call the Popo Voice Assist, allowing users to start trips and check country conditions, etc.

Together, this upgrade creates a more accessible and streamlined user experience. Third, our tech stack is also built for generalization. The L4 native tech architecture allows us to adapt quickly to new markets and platforms. In terms of cross-region generalization, our virtual driver and showings can quickly understand and adapt to diverse traffic conditions around the world.

We will continue the upgrade to the cabin into our AI-powered mobility terminal together. This upgrade creates a more accessible and streamlined user experience.

So, the third overall tech stack is also a beautiful generalization.

The L4 native tech architecture allows us to adapt quickly to new markets and platforms.

Tiancheng Lou: For example, leveraging our high-fidelity training environment and evaluation mechanism powered by Pony World, we extend our fully driverless coverage in Pudong District in just a few weeks. In addition, when expanding to Europe, the system intelligently identifies and adapts to key differences in local road conditions, such as unique traffic signals configuration and various driving patterns. Our technology boosts generalization power across platforms as well. The latest-generation robo truck will commence production and operations from next year. This demonstrates our capability to create synergy between robotaxi and robo truck tech stack. Looking ahead, we will leverage our success at Hong Kong listing to reinforce our technological leadership, increasing R&D investment, and attract top AI talent to advance our robotaxi, robo truck, and new market initiatives. We will continue pushing the frontier of autonomous mobility and refining what is possible in transportation. Okay, this concludes my prepared remarks.

For example, leveraging our high-fidelity training environment and evaluation mechanism powered by Pony World, we extend our fully driverless coverage in Pudong District in just a few weeks. In addition, when expanding to Europe, the system intelligently identifies and adapts to key differences in local road conditions, such as unique traffic signals configuration and various driving patterns.

In terms of cross-region generalization, or Virtual Drive as the show is, we can quickly understand and adapt to diverse traffic conditions around the world. For example, leveraging a high-fidelity training environment and evaluation mechanism powered by Pony.ai, we extended over 40 drivers' coverage in Furong District in just a few weeks.

Our technology boosts generalization power across platforms as well. The latest-generation robo truck will commence production and operations from next year. This demonstrates our capability to create synergy between robotaxi and robo truck tech stack. Looking ahead, we will leverage our success at Hong Kong listing to reinforce our technological leadership, increasing R&D investment, and attract top AI talent to advance our robotaxi, robo truck, and new market initiatives.

Yeah, when sending to Europe, the system of intelligence is identified and adapted. Key differences include local road conditions, as well as unique traffic signal configurations and various driving behavior patterns.

Over technology, boost generation power across platforms as well.

The latest generation of robot trucks will commence production and operations next year. This demonstrates our capability to create synergy between robotics and the robot truck tech stack.

We will continue pushing the frontier of autonomous mobility and refining what is possible in transportation. Okay, this concludes my prepared remarks. I will now pass the call over to our CFO, Dr. Liu Wang, for a closer look at our financial results. Liu, please go ahead.

Looking ahead, we will leverage our success. Hong Kong is listening to reinforce our technological leadership. We will increase R&D investment and attract top AI talent to advance our robot taxi, Google trucks, and new market initiatives.

We will continue pushing the frontier of automated mobility and refining what is possible in transportation.

Tiancheng Lou: I will now pass the call over to our CFO, Dr. Liu Wang, for a closer look at our financial results. Liu, please go ahead.

Okay, this concludes my prepared remarks.

I will now pass the call over to our Salesforce, Dr. Leo Wong, for a closer look at our financial results. Leo, please go ahead.

Leo Wang: Thank you, Tiancheng. Hello everyone. This is Liu. I will focus on year-over-year comparisons for Q3 unless otherwise noted. Q3 2025 was a landmark quarter. We delivered robust revenue growth, specifically with solid progress in robotaxi large-scale commercialization. We now expect to outperform our full-year fleet target of 1,000 vehicles. Moreover, our newly deployed Gen7 Robotaxi fleet has reached a pivotal city-wide unit economic break-even milestone. This lays out a solid foundation for further scaling up, and the implementation of our satellite business model, which will be further accelerated by our successful Hong Kong IPO capital raise. In this quarter, revenue finished at $25.4 million, growing by 72%. This strong performance was primarily driven by the continuous optimization of our robotaxi services, and the sustained demand in our licensing and application business.

Thank you, Kenton. Uh, hello everyone. This is Leo.

I will focus on year-over-year comparisons for the third quarter unless otherwise noted.

Q3 2025 was a landmark order.

We delivered robust revenue growth.

Specifically, we have made solid progress in our Robo-taxi large-scale commercialization.

And now we expect to outperform our full-year fleet target of 1,000 vehicles.

This lays out a solid foundation for further scaling up, and the implementation of our satellite business model, which will be further accelerated by our successful Hong Kong IPO capital raise. In this quarter, revenue finished at $25.4 million, growing by 72%. This strong performance was primarily driven by the continuous optimization of our robotaxi services, and the sustained demand in our licensing and application business.

Moreover, our newly deposited J7 robot taxi fleet has reached a pivotal citywide unit economic break-even milestone.

This layout provides a solid foundation for further scaling up and the implementation of an asset-light business model.

What, which will be further accelerated by our successful Hong Kong IPO capital raise.

In this quarter.

Revenue finished at $25.4 million.

Growing by 72%.

This strong performance was primarily driven by the continuous optimization of our robotaxi services and the sustained demand in our licensing and application business.

Leo Wang: Firstly, robotaxi services revenue reached $6.7 million, representing a remarkable growth of 89.5% year-over-year and 338.7% quarter-over-quarter. Specifically, fare charging revenue continued to deliver a triple-digit growth, surging 233.3%. This was achieved even before the commercial rollout of our Gen7 Robotaxi vehicles. Supported by a stable commercial fleet of our Gen5 and Gen6 vehicles, the strong growth during Q2 and Q3 stemmed from growing user demand in Tier 1 cities in China. Our continuous effort to optimize fleet operation and pricing strategy altogether led to increased fleet utilization and efficiency. This is a testament to growing user recognition and brand loyalty to Pony Pilot service. Going forward, as we follow this strong momentum towards a significant fleet expansion of over 3,000 vehicles by 2026, we expect robotaxi revenue growth to accelerate even further, driving more orders, and a higher operational efficiency.

Firstly, robotaxi services revenue reached $6.7 million, representing a remarkable growth of 89.5% year-over-year and 338.7% quarter-over-quarter. Specifically, fare charging revenue continued to deliver a triple-digit growth, surging 233.3%. This was achieved even before the commercial rollout of our Gen7 Robotaxi vehicles. Supported by a stable commercial fleet of our Gen5 and Gen6 vehicles, the strong growth during Q2 and Q3 stemmed from growing user demand in Tier 1 cities in China.

Firstly, RoboTaxi service revenue reached $6.7 million.

Representing a remarkable growth of 89.5% year-over-year.

And the 338.7% quarter-over-quarter.

Specifically.

Fair charging revenue continued to deliver triple-digit growth, surging 233.3%.

This was achieved even before the commercial rollout of our Gen 7 Robo taxis.

Supported by a stable commercial fleet of our Gen 5 and Gen 6 vehicles.

Our continuous effort to optimize fleet operation and pricing strategy altogether led to increased fleet utilization and efficiency. This is a testament to growing user recognition and brand loyalty to Pony Pilot service. Going forward, as we follow this strong momentum towards a significant fleet expansion of over 3,000 vehicles by 2026, we expect robotaxi revenue growth to accelerate even further, driving more orders, and a higher operational efficiency.

The strong growth during Q2 and Q3 stemmed from growing user demand in T1 cities in China.

Our continuous effort to optimize fleet operation and the pricing strategy.

Complete utilization and efficiency.

This is a testament to growing user recognition and the brand loyalty to Pony.ai's Pilot service.

Going forward, as we follow this strong momentum towards a significant fleet expansion of over 3,000 vehicles by 2026.

We expect RoboTaxi revenue growth to accelerate, further driving more orders and higher operational efficiency.

Leo Wang: In Q3, another key robotaxi update is the implementation of our satellite model for fleet expansion. As we have shown promising numbers in vehicle unit economics, we received strong interest from third parties who are willing to purchase Gen7 vehicles to run as robotaxi operators. Such partners include, but are not limited to, leading ride-hailing or taxi operators, for instance, Shenzhen Sihu Group and Sunlight Mobility. The satellite model has contributed revenues through technology licensing fees and vehicle sales, while giving us further leverage and capital efficiency for further fleet expansion. Aside from strong top-line growth domestically, we are also seeing fast growth of robotaxi revenues from overseas markets. Moving forward, we expect robotaxi revenues from overseas markets to continue to grow. Currently, our robotaxi footprint has already expanded into eight countries globally, serving as a promising foundation in our exploration of the international opportunities. Secondly, moving to robo truck.

In Q3, another key robotaxi update is the implementation of our satellite model for fleet expansion. As we have shown promising numbers in vehicle unit economics, we received strong interest from third parties who are willing to purchase Gen7 vehicles to run as robotaxi operators. Such partners include, but are not limited to, leading ride-hailing or taxi operators, for instance, Shenzhen Sihu Group and Sunlight Mobility.

In Q3, another key robotaxi update is the implementation of our asset-light model for fleet expansion.

As we have shown promising numbers in vehicle unit economics, we received strong interest from third parties who are willing to purchase Gen 7 vehicles to operate as Robo-taxi operators.

The satellite model has contributed revenues through technology licensing fees and vehicle sales, while giving us further leverage and capital efficiency for further fleet expansion. Aside from strong top-line growth domestically, we are also seeing fast growth of robotaxi revenues from overseas markets. Moving forward, we expect robotaxi revenues from overseas markets to continue to grow. Currently, our robotaxi footprint has already expanded into eight countries globally, serving as a promising foundation in our exploration of the international opportunities.

Such partners include, but are not limited to, leading ride-hailing or taxi operators, for instance, the Shenzhen Group and Sunlight Mobility.

The asset-light model has contributed revenues through technology licensing fees and vehicle sales.

While giving us further leverage and capital efficiency for further fleet expansion.

Aside from strong top-line growth domestically, we are also seeing fast growth of Robo taxi revenues from overseas markets.

Moving forward, we expect Robo-taxi revenues from overseas markets to continue to grow.

Secondly, moving to robo truck. Robo truck service revenues were $10.2 million, growing by 8.7%. Moreover, as we launch our Gen4 fully auto-grade robo truck, we expect to reduce the bump cost of its ADK, autonomous driving hardware kit, by 70% and reach a 1,000-unit scale of robo truck fleet going forward. This new generation of robo truck will powerfully accelerate the progress of robo truck commercialization at scale.

Currently, our Robo taxi footprint has already expanded into 8 countries globally, serving as a promising foundation in our exploration of international opportunities.

Leo Wang: Robo truck service revenues were $10.2 million, growing by 8.7%. Moreover, as we launch our Gen4 fully auto-grade robo truck, we expect to reduce the bump cost of its ADK, autonomous driving hardware kit, by 70% and reach a 1,000-unit scale of robo truck fleet going forward. This new generation of robo truck will powerfully accelerate the progress of robo truck commercialization at scale. Thirdly, licensing and application revenues were $8.6 million, growing significantly by 354.6%. We continue to see robust and growing demand for our autonomous domain controller, primarily from robo delivery clients. Turning to gross margin, we delivered a significant gross profit margin improvement from 9.2% in Q3 2024 to 18.4% in Q3 2025, with gross profit of $4.7 million in Q3.

Secondly, moving to Robo truck.

Robot truck service revenues were $10.2 million, growing by 8.7%.

Thirdly, licensing and application revenues were $8.6 million, growing significantly by 354.6%. We continue to see robust and growing demand for our autonomous domain controller, primarily from robo delivery clients. Turning to gross margin, we delivered a significant gross profit margin improvement from 9.2% in Q3 2024 to 18.4% in Q3 2025, with gross profit of $4.7 million in Q3.

Moreover, as we launch our Gen 4, fully autograde Robo truck, we expect to reduce the BOM cost of its ADK, Autumn Driving Hardware kit, by 70% and reach a 1,000-unit scale of our robot truck fleet going forward. This new generation of robot truck will powerfully accelerate the progress of robot truck commercialization at scale.

Thirdly, licensing and application revenues were $8.6 million, growing significantly by 354.6%.

We continue to see robust and growing demand in our atoms domain, Controller.

Primary from Robo delivery clients.

Turning to gross margin, we delivered significant growth in profit, with margin improvement from 9.2% in Q3 2024 to 18.4% in Q3 2025.

with gross profit of

Leo Wang: This remarkable improvement was firstly driven by our strategic initiatives to optimize the revenue mix, and secondly by a greater contribution from robotaxi services, which carry a relatively higher margin. The unique economic break-even achievement validates our dual focus on go-to-market execution and optimized operational efficiency. Since the launch of Gen7 commercial operations in Guangzhou, the daily net revenue per vehicle has reached RMB 299. The net revenue refers to the total RMB value generated from ride-hailing services after deducting discounts and refunds. Notably, daily average orders per vehicle have reached 23, fueled by robust, widespread user demands and our operational optimization. Meanwhile, we have also optimized hardware depreciation as well as operational costs, including charging, remote assistance, ground support, service and maintenance, insurance, parking, and network costs. This will further improve our margin down the road. The total operating expenses were $74.3 million, up by 76.7%.

This remarkable improvement was firstly driven by our strategic initiatives to optimize the revenue mix, and secondly by a greater contribution from robotaxi services, which carry a relatively higher margin. The unique economic break-even achievement validates our dual focus on go-to-market execution and optimized operational efficiency.

$4.7 million in the third quarter.

This remarkable improvement was driven first by our strategic initiatives to optimize the revenue mix, and secondly by a greater contribution from robot taxi services, which carry a relatively higher margin.

Since the launch of Gen7 commercial operations in Guangzhou, the daily net revenue per vehicle has reached RMB 299. The net revenue refers to the total RMB value generated from ride-hailing services after deducting discounts and refunds. Notably, daily average orders per vehicle have reached 23, fueled by robust, widespread user demands and our operational optimization.

The UEE, the Unique Economic Break Even achievement, validates our due focus on go-to-market execution and optimized operational efficiency.

Since the launch of J7 commercial operations in Guango, the daily net revenue per vehicle has reached ¥299.

The net revenue refers to the total R&B value generated from Wright Heating Services.

After deducting discounts and the refunds.

Notably, daily average orders per vehicle have reached 23.

Meanwhile, we have also optimized hardware depreciation as well as operational costs, including charging, remote assistance, ground support, service and maintenance, insurance, parking, and network costs. This will further improve our margin down the road. The total operating expenses were $74.3 million, up by 76.7%.

billed by robust, widespread user demands and our operational optimization.

Meanwhile, we have also optimized hardware depreciation, as well as operational costs, including charging, remote assistance, ground support services, maintenance insurance, parking, and network costs.

This will further improve our margins down the road.

Leo Wang: Excluding share-based compensation expenses, non-GAAP operating expenses were $67.7 million, up 63.7%. The increase primarily reflects the win of R&D investment in Gen7 vehicles, and the expansion of our R&D personnel, critical to securing and extending our technological leadership. Specifically, approximately half of the increase in research and development expenses stemmed from a one-time customized development fee of $12.7 million for Gen7 vehicles. Net loss for Q3 was $61.6 million, compared to $42.1 million in the same period of last year. Non-GAAP net loss was $55 million, compared to $41.4 million last year. Looking ahead, we expect to sustain disciplined investment to accelerate large-scale commercial deployment.

Excluding share-based compensation expenses, non-GAAP operating expenses were $67.7 million, up 63.7%. The increase primarily reflects the win of R&D investment in Gen7 vehicles, and the expansion of our R&D personnel, critical to securing and extending our technological leadership.

The total operating expenses for the 7-day period were $4.3 million, up by 76.7%.

Million US Dollars up. 63.7%

The increased primary reflects the 1 1 of R&D investment in gen 7 vehicles, and the expansion of our R&D personnel,

Specifically, approximately half of the increase in research and development expenses stemmed from a one-time customized development fee of $12.7 million for Gen7 vehicles. Net loss for Q3 was $61.6 million, compared to $42.1 million in the same period of last year. Non-GAAP net loss was $55 million, compared to $41.4 million last year. Looking ahead, we expect to sustain disciplined investment to accelerate large-scale commercial deployment.

Critical to securing and extending our technological leadership.

Specifically, approximately half of the increase.

In research and development expenses, this stemmed from a one-time, customized development fee.

$12.7 million for Gen 7 vehicles.

Net loss for the third quarter was $61.6 million compared to $42.1 million in the same period of last year.

Non-GAAP net loss was $55 million compared to $41.4 million last year.

Looking ahead, we expect to sustain disciplined investment to accelerate large-scale commercial deployment.

Leo Wang: Turning to the balance sheet, our cash and cash equivalents, short-term investments, restricted cash, and long-term debt instrument for wealth management were $587.7 million as of 30 September 2025, compared to the balance as of 30 June 2025 of $747.7 million. Around half of this decrease comes from one-off cash outflow, including capital injection to JFeng, our joint venture with Toyota to support Gen7 mass production and deployment. All of the capital commitment in JFeng has been completed. The remaining cash balance reduction primarily reflects our mass production and large-scale deployment status, including, firstly, ongoing operational cash outflow, and secondly, capital expenditure for the procurement of Gen7 vehicles in Q3 to support our goal of a 1,000 vehicle fleet by year-end. For the nine months ending 30 September 2025, we have an accumulated free cash outflow of $173.6 million.

Turning to the balance sheet, our cash and cash equivalents, short-term investments, restricted cash, and long-term debt instrument for wealth management were $587.7 million as of 30 September 2025, compared to the balance as of 30 June 2025 of $747.7 million. Around half of this decrease comes from one-off cash outflow, including capital injection to JFeng, our joint venture with Toyota to support Gen7 mass production and deployment. All of the capital commitment in JFeng has been completed.

Turning to the balance sheet, our cash and cash equivalents, and short-term investments.

Restrict the cash and long-term debt instruments for wealth management, which were $587.7 million as of September 30, 2025.

Compared to the balance as of June 30, 2025, of $747.7 million.

Around half of this creates discrete.

Comes from $1 of cash outflow, including capital injection to Dre Phone.

Our joint venture with Toyota to support the Gen7 mass production and deployment.

The remaining cash balance reduction primarily reflects our mass production and large-scale deployment status, including, firstly, ongoing operational cash outflow, and secondly, capital expenditure for the procurement of Gen7 vehicles in Q3 to support our goal of a 1,000 vehicle fleet by year-end. For the nine months ending 30 September 2025, we have an accumulated free cash outflow of $173.6 million.

Of the capital commitment in Jung, has been completed.

The remaining cash balance reduction primarily reflects our mass production and the large-scale deployment status, including firstly, ongoing operational cash outflow, and secondly, capital expenditure for the procurement of Gen7 vehicles in Q3 to support our goal of a fleet of 1,000 vehicles by year-end.

Leo Wang: With the completion of our recent Hong Kong IPO, we have over $800 million US dollars cash newly added, providing us with substantial fuel for the next phase of growth. The IPO proceeds will help us accelerate fleet expansion into key addressable markets, further optimize our platform for scale, and deepen our R&D investments to further solidify our technology moat. Looking ahead, our mass production momentum continues to strengthen, and we are on track to exceed our full-year vehicle target of 1,000, achieving this milestone ahead of schedule. This acceleration reinforces our confidence in scaling rapidly, and we now anticipate to grow our fleet to be more than 3,000 vehicles by 2026. In addition, we've already transitioned to a satellite model for a meaningful portion of our new vehicles. This will enhance our capital expenditure efficiency, and provide greater leverage for scalable fleet expansion.

With the completion of our recent Hong Kong IPO, we have over $800 million US dollars cash newly added, providing us with substantial fuel for the next phase of growth. The IPO proceeds will help us accelerate fleet expansion into key addressable markets, further optimize our platform for scale, and deepen our R&D investments to further solidify our technology moat.

For the 9 months ending September 30, 2025, we have a cumulative free cash outflow of $173.6 million.

With the completion of our recent Hong Kong IPO, we have over $800 million in cash, newly added.

Providing us with substantial fuel for the next phase of growth.

Looking ahead, our mass production momentum continues to strengthen, and we are on track to exceed our full-year vehicle target of 1,000, achieving this milestone ahead of schedule. This acceleration reinforces our confidence in scaling rapidly, and we now anticipate to grow our fleet to be more than 3,000 vehicles by 2026. In addition, we've already transitioned to a satellite model for a meaningful portion of our new vehicles. This will enhance our capital expenditure efficiency, and provide greater leverage for scalable fleet expansion.

The IPO proceeds will help us accelerate fleet expansion into key addressable markets further, optimize our platform for scale, and deepen our R&D investments to further solidify our technology moat.

Looking ahead.

Our mass production momentum continues to strengthen, and we are on track to exceed our full-year vehicle target of 1,000, achieving this milestone ahead of schedule.

This acceleration reinforces our confidence in scaling rapidly.

And we now anticipate growing our fleet to be more than 3,000 vehicles by 2026.

In addition, we've already transitioned to an asset-light model for a meaningful portion of our new vehicles.

Leo Wang: With the proven operational model and the financial runway from the recent Hong Kong IPO, we are uniquely positioned to accelerate our business plan, turning momentum into sustained profitable growth. I will now turn the call over to the operator to begin our Q&A session. Thank you. Thank you. We will now begin the question and answer session. To ask a question, you may press star then one on your telephone keypad. If you're using a speakerphone, please pick up your handset before pressing the keys. To withdraw your question, please press star then two. For the benefit of all participants on today's call, please limit yourself to one question. If you have more questions, please re-enter the question queue. If you ask questions in Chinese, please repeat them in English. The first question comes from Ming Shun Li with Bank of America. Please go ahead.

With the proven operational model and the financial runway from the recent Hong Kong IPO, we are uniquely positioned to accelerate our business plan, turning momentum into sustained profitable growth. I will now turn the call over to the operator to begin our Q&A session. Thank you.

This will enhance our capital expenditure efficiency and provide a greater leverage for scalable feet expansion with the proven operational model.

And with the financial runway from the recent Hong Kong IPO, we are uniquely positioned to accelerate our business plan.

Turning momentum into sustained profitable growth.

Operator: Thank you. We will now begin the question and answer session. To ask a question, you may press star then one on your telephone keypad. If you're using a speakerphone, please pick up your handset before pressing the keys. To withdraw your question, please press star then two. For the benefit of all participants on today's call, please limit yourself to one question. If you have more questions, please re-enter the question queue. If you ask questions in Chinese, please repeat them in English. The first question comes from Ming Shun Li with Bank of America. Please go ahead.

I will now turn the call over to the operator to begin our Q&A session. Thank you.

Thank you. We will now begin the question and answer session. To ask a question, you may press star then 1 on your telephone keypad. If you're using a speakerphone, please pick up your handset before pressing the keys to withdraw your question. Please press star then 2. For the benefit of all participants on today's call, please limit yourself to 1 question. If you have more questions, please re-enter the question queue.

If you ask questions in Chinese please, repeat them in English.

And the first question comes from Ming Shun Lee with Bank of America. Please go ahead.

Leo Wang: Thank you, thank you, management, to give the opportunity for me to ask a question. I just have one question. Could the management team give us more updates on the fleet size for this year and also the outlook in 2026? For the new vehicles added, what is the fleet deployment plan across different cities? Thank you. This is James. I'll take this one. As you can see, since the launch of our Gen7 Robotaxi, we actually have seen a much faster-than-expected production and deployment. For this year, we certainly expect to outperform our previous target of 1,000 robotaxis by the year-end. We certainly expect this strong momentum to continue into 2026, now with a conservative target of over 3,000 vehicles. This is mainly because we have already seen an upward spiral with the launch of our Gen7 vehicles.

Ming Hsun Li: Thank you, thank you, management, to give the opportunity for me to ask a question. I just have one question. Could the management team give us more updates on the fleet size for this year and also the outlook in 2026? For the new vehicles added, what is the fleet deployment plan across different cities? Thank you.

James Peng: This is James. I'll take this one. As you can see, since the launch of our Gen7 Robotaxi, we actually have seen a much faster-than-expected production and deployment. For this year, we certainly expect to outperform our previous target of 1,000 robotaxis by the year-end. We certainly expect this strong momentum to continue into 2026, now with a conservative target of over 3,000 vehicles. This is mainly because we have already seen an upward spiral with the launch of our Gen7 vehicles.

Thank you. Uh uh, thank you management to give uh the opportunity for me to ask a question. So I just have 1 question. So could the management team, give us more updates on the free size for this year and also the Outlook in 2026 uh, for the new vehicles. Uh aided. Uh, what is the uh uh Fleet deployment, uh, plan, across different city? Uh, thank you.

Uh, this is James. Um, I'll take this one. So, as you can see, since the launch of our Gen 7 Robo Taxi,

We have actually seen a much faster-than-expected production and deployment.

Uh, so for this year, we certainly expect to outperform our previous target of 1,000 robot taxis by the year end.

Uh, we certainly expect this strong momentum to continue into 2026. Now, with a conservative target of over 3,000 vehicles.

Leo Wang: Essentially, the fleet density creates a much shorter wait time for the passengers, which creates a better user experience. The user experience leads to much higher utilization for our vehicles, and we can actually then charge a better pricing. This spiral really created a strong momentum for us to expand much faster. In addition, we also started experimenting with the satellite model by collaborating with fleet managers such as Sihu, Sunlight, and certainly will add more partners. This satellite model allows us to deploy at a much larger fleet with less CapEx. This is our growth plan. In terms of the fleet deployment plan, we'll go deeper on our existing markets, and at the same time, we'll go much wider to explore some new opportunities.

Essentially, the fleet density creates a much shorter wait time for the passengers, which creates a better user experience. The user experience leads to much higher utilization for our vehicles, and we can actually then charge a better pricing. This spiral really created a strong momentum for us to expand much faster. In addition, we also started experimenting with the satellite model by collaborating with fleet managers such as Sihu, Sunlight, and certainly will add more partners.

Uh, this is mainly because we have already seen an upward spiral with the launch of our Gen7 vehicles. Essentially, the fleet density creates a much shorter wait time for the passengers.

And then that creates a better user experience, and the user experience leads to much higher utilization for our vehicles. Then we can actually charge a better price.

So, this spiral really created, uh,

a strong momentum for us to

expand much faster.

In addition, we also started experimenting with the asset-light model by collaborating with Fleet managers such as Shiu Sunlight.

This satellite model allows us to deploy at a much larger fleet with less CapEx. This is our growth plan. In terms of the fleet deployment plan, we'll go deeper on our existing markets, and at the same time, we'll go much wider to explore some new opportunities.

Uh, and certainly, we will add more partners. This asset-light model allows us to deploy at a much.

Larger fleet with, uh, less CPAX.

So, this is our growth plan. Then, in terms of the, uh, fleet deployment plan, uh, we will...

Go deeper on our existing markets.

And at the same time, we'll go much wider to explore some new opportunities.

Leo Wang: The city-wide UE break-even for the Gen7 in Guangzhou, in my view, is a pivotal milestone to validate our business model. This gives us huge confidence and allows us to deepen our collaboration and our operation in the existing markets, which are the Tier 1 cities in China. This is because, as I already mentioned, expanded fleet size creates an upward spiral. At the same time, we also expand into many more domestic cities and also the overseas markets. We see those for our future growth. Our go-to-market strategy on those markets is that we'll collaborate deeply with the local partners and the local government agencies to establish presence and prepare for our future growth. Stay tuned. I think we'll have great news ahead of us. With that, back to the operator. Thank you. The next question comes from Bin Wang with Deutsche Bank. Please go ahead.

The city-wide UE break-even for the Gen7 in Guangzhou, in my view, is a pivotal milestone to validate our business model. This gives us huge confidence and allows us to deepen our collaboration and our operation in the existing markets, which are the Tier 1 cities in China. This is because, as I already mentioned, expanded fleet size creates an upward spiral. At the same time, we also expand into many more domestic cities and also the overseas markets.

Uh, the Citywide UE break-even for the Gen 7 in Guango.

Uh, in my view, it's a pivotal milestone to validate our business model.

uh,

This gives us a huge confidence and, uh,

Allow us to deepen our collaboration and our operation in the existing markets, which are the Tier 1 cities in China.

Uh, this is because, as already mentioned, expanding the fleet size creates upward spirals.

But at the same time, we also expand into many more.

We see those for our future growth. Our go-to-market strategy on those markets is that we'll collaborate deeply with the local partners and the local government agencies to establish presence and prepare for our future growth. Stay tuned. I think we'll have great news ahead of us. With that, back to the operator.

Domestic cities and also the overseas markets.

Uh, we see those, uh, for our future growth.

Uh, our go to market strategy. On those markets is that we will collaborate deeply with the local partners and the local government agencies.

To establish presence and prepare for our future growth.

So, stay tuned. I think we'll have great news ahead of us.

Operator: Thank you. The next question comes from Bin Wang with Deutsche Bank. Please go ahead.

With that, back to the operator.

Thank you. The next question comes from Ben Wong with Deutsche Bank. Please go ahead.

Leo Wang: Hi, management. Thank you for taking my question. I just have one question, which is about the fare charging. I'd like to know if fare charging revenues will level another growth in Q2 2025. What is the outlook for fare charging revenues as we deploy more vehicles? Thank you. Yeah, this is Leo. I'll take this question. Yes, in Q3, our fare charging revenue actually surged even faster. It was growing about 233%, though at that time, our fleet were still with the Gen5 and Gen6 vehicles. We believe such growth was driven by both the demand side, as well as the operational side. On the demand side, we have been continuously doing our effort to improve the whole riding experience and also the user experience. With this effort, we've seen robust and organic user demand in Tier 1 cities.

Bin Wang: Hi, management. Thank you for taking my question. I just have one question, which is about the fare charging. I'd like to know if fare charging revenues will level another growth in Q2 2025. What is the outlook for fare charging revenues as we deploy more vehicles? Thank you.

Leo Wang: Yeah, this is Leo. I'll take this question. Yes, in Q3, our fare charging revenue actually surged even faster. It was growing about 233%, though at that time, our fleet were still with the Gen5 and Gen6 vehicles. We believe such growth was driven by both the demand side, as well as the operational side. On the demand side, we have been continuously doing our effort to improve the whole riding experience and also the user experience. With this effort, we've seen robust and organic user demand in Tier 1 cities.

High management, uh, thank you for taking my question. I just have one question, uh, which is about the fair charging. I would like to know where charging revenue is delivered in Mara growth in 3225. So what is the allocation for fair charging revenues as we deploy more vehicles? Thank you.

Yeah. Uh, this is Leo. I'll take this question. Uh, yes, in Q3, our fair charging revenue actually surged even faster. It was growing about 233 percent.

Uh, though at that time our fleet was still with the GM5 and Gen 6 vehicles.

So, we believe such a growth was driven by both the demand side as well as the operational side.

On the demand side, we have been continuously making efforts to improve the whole writing experience and also the user experience.

Leo Wang: This is also a signal of a strong consumer adoption of our robotaxi service. For example, the total registered user was more than doubled year over year in Q3. On the operational side, we have also been optimizing the fleet operation to improve our vehicle utilization and order fulfillment, as Tiancheng already mentioned in his remarks. For example, we enhanced our fleet dispatching and deployment. This has consistently reduced our wait time. It's approximately 50% shorter compared to the same period in 2024. We also continue to expand our pickup and drop-off points to create a much more smooth user experience. For example, in Shenzhen, now we have more than 10,000 such points, more than 300% increase since the end of June this year.

This is also a signal of a strong consumer adoption of our robotaxi service. For example, the total registered user was more than doubled year over year in Q3. On the operational side, we have also been optimizing the fleet operation to improve our vehicle utilization and order fulfillment, as Tiancheng already mentioned in his remarks. For example, we enhanced our fleet dispatching and deployment.

So, with this effort, we've seen robust and organic user demand in one city.

I'll follow a robot taxi service.

Uh, giving you an example that the total registered users more than doubled year over year in Q3.

And on the operational side, we have also been optimizing fleet operations to improve our vehicle utilization and order fulfillment, as Tension already mentioned in his remarks.

This has consistently reduced our wait time. It's approximately 50% shorter compared to the same period in 2024. We also continue to expand our pickup and drop-off points to create a much more smooth user experience. For example, in Shenzhen, now we have more than 10,000 such points, more than 300% increase since the end of June this year.

So, for example, we enhanced our fleet dispatching and the deployment.

Uh, this has consistently reduced our wait time.

It's approximately 50% shorter compared to the same period in 2024.

And we also continue to expand our pickup and drop-off points.

To create a much smoother user experience,

For example, in Shenzhen, we now have more than 10,000 such points.

More than a 300% increase since the end of June this year.

Leo Wang: With all this demand side and operational side improvement, I believe we could see sustained strong growth momentum through the continuous fleet expansion with more and more Gen7 vehicles into our service. First of all, we expect that our fleet has been growing exponentially from 270 last year to be more than 1,000 this year, and a target of more than 3,000 next year. This scaling up would also create a better network fence, which means shorter wait time, higher vehicle utilization, and higher user adoption. We would also progressively expand our service area in cities such as Shanghai, Shenzhen. We've already been doing so today. We would increase the population coverage and expand to more drivable mileages, etc., etc. With all these being done, I think we can boost the average order value per trip. Okay, now I'll get back to the operator. Thank you, sir.

With all this demand side and operational side improvement, I believe we could see sustained strong growth momentum through the continuous fleet expansion with more and more Gen7 vehicles into our service. First of all, we expect that our fleet has been growing exponentially from 270 last year to be more than 1,000 this year, and a target of more than 3,000 next year. This scaling up would also create a better network fence, which means shorter wait time, higher vehicle utilization, and higher user adoption.

With all this, you know, demand-side and operational-side improvement.

Uh, I believe we could see sustained strong growth momentum through the continuous.

Fleet expansion with more and more Gen7 vehicles into our service.

First of all,

We expect that our fleet has been growing exponentially from 270 last year to more than 10,000 this year.

And a target of more than 3,000 next year.

This scaling up would also create better network effects.

We would also progressively expand our service area in cities such as Shanghai, Shenzhen. We've already been doing so today. We would increase the population coverage and expand to more drivable mileages, etc., etc. With all these being done, I think we can boost the average order value per trip. Okay, now I'll get back to the operator.

which means shorter wait time, higher vehicle utilization, and higher user adoption.

We would also be progressively expanding our service area in cities such as Shanghai and Shenzhen; we've already been doing so today.

We would increase the population coverage and expand to more drivable mileage, etc., etc.

With all these being done, I think we can boost the average order value per trip.

Operator: Thank you, sir. The next question comes from Qiao Wu with City Research. Please go ahead.

Okay, now I get back to the operator.

Leo Wang: The next question comes from Qiao Wu with City Research. Please go ahead. Thanks for taking my questions. This is Qiao from City Research, and congratulations on achieving the milestone of city-wide UE break-even. Could you elaborate more about the assumption behind the UE break-even, including daily order pricing, daily operating hours, and the ratio of remote assistance? Thank you. Yes, I'll take this question. Like you said, we all believe the city-wide unit economic break-even is a pivotal milestone for the company and also for the industry. First of all, we achieved this pivotal milestone in Guangzhou since our Gen7 vehicle has been put into commercial service. We always believe China is the largest market of global ride-hailing market. For the Tier 1 cities, the total TAM accounts for a huge percent of ride-hailing market in China.

Kyle Wu: Thanks for taking my questions. This is Qiao from City Research, and congratulations on achieving the milestone of city-wide UE break-even. Could you elaborate more about the assumption behind the UE break-even, including daily order pricing, daily operating hours, and the ratio of remote assistance? Thank you.

Thank you, sir. The next question comes from Kyle Wu with Citi Research. Please go ahead.

Leo Wang: Yes, I'll take this question. Like you said, we all believe the city-wide unit economic break-even is a pivotal milestone for the company and also for the industry. First of all, we achieved this pivotal milestone in Guangzhou since our Gen7 vehicle has been put into commercial service. We always believe China is the largest market of global ride-hailing market. For the Tier 1 cities, the total TAM accounts for a huge percent of ride-hailing market in China.

Thanks for taking my questions. Um, this is Kyle from City Research, and congratulations on achieving the milestone of citywide Uber even. Could you elaborate more about the assumptions behind the delivery event, including daily order pricing, daily operating hours, and the ratio of our remote assistance? Thank you.

Yes, I'll I'll take this, uh, question. Uh, like you said, we we all believe the Citywide unique economic Break Even is a pivotal milestone for the company and also for the industry

First of all, we, uh, you know, achieved this, uh, pivotal milestone, uh, in Guano City, uh, since our Gen 7 vehicle has been put into commercial service.

and,

We always believe China is the largest market globally, right? The heating market, and for the Tier 1 cities.

Leo Wang: Achieving this milestone in this market is far more meaningful from a commercial perspective. If we talk about the unit economics, there is the revenue side and there is always the cost side. On the revenue side, first of all, on the daily net revenue per vehicle, as I mentioned, our daily net revenue per vehicle has hit RMB 299. It is based on a two-week daily average figure as of 23 November 2023, following the launch of our Gen7 vehicle in Guangzhou. This net revenue also refers to the total RMB value generated from ride-hailing service after deducting discounts and refunds. In terms of daily orders from this RMB 299 number, it was an average of 23 orders per day. It is fueled by robust, widespread user demand. Now let's look into the cost side. The cost side of the unit economics basically has two major components.

Achieving this milestone in this market is far more meaningful from a commercial perspective. If we talk about the unit economics, there is the revenue side and there is always the cost side. On the revenue side, first of all, on the daily net revenue per vehicle, as I mentioned, our daily net revenue per vehicle has hit RMB 299. It is based on a two-week daily average figure as of 23 November 2023, following the launch of our Gen7 vehicle in Guangzhou.

The total time accounts for a huge percent of the Wright heating market in China. So, achieving this milestone in this market is far more meaningful from a commercial perspective.

Then, if we talk about the unique economic aspects, there's the revenue side, and there's always the cost side.

On the revenue side, first of all on The Daily, net revenue per vehicle,

As I mentioned, our daily net revenue per vehicle has hit $299.

It's based on a two-week, daily average figures as of November 23rd.

This net revenue also refers to the total RMB value generated from ride-hailing service after deducting discounts and refunds. In terms of daily orders from this RMB 299 number, it was an average of 23 orders per day. It is fueled by robust, widespread user demand. Now let's look into the cost side. The cost side of the unit economics basically has two major components.

Following the launch of our j7 vehicle in Guango.

And this net revenue also refers to the total R&B value generated from Wright Heating Service.

After deducting discounts and the refunds.

And in terms of daily orders from this 299, R&B number.

It was.

Average 23 orders per day.

It's fueled by robust widespread user demand.

Leo Wang: First of all, it's the hardware depreciation. For Gen7 vehicles, the annual vehicle depreciation is based on a six-year useful life. The other major component on the cost side is the operational cost, which includes the charging, remote assistant, the ground supporting staff, vehicle service and maintenance, insurance, parking, internet network costs. Regarding the remote assistant, we are on track to achieve our 1 over 30 vehicles. From this milestone that we achieved, we are very confident to capture the China huge TAM. Meanwhile, it also established a strategic foundation for further scaling up domestically and internationally. This not only gives us strong confidence to further scale our fleet, but we also see more and more third-party companies are enabled to fund their fleet, helping us to transition into an asset-light model.

First of all, it's the hardware depreciation. For Gen7 vehicles, the annual vehicle depreciation is based on a six-year useful life. The other major component on the cost side is the operational cost, which includes the charging, remote assistant, the ground supporting staff, vehicle service and maintenance, insurance, parking, internet network costs. Regarding the remote assistant, we are on track to achieve our 1 over 30 vehicles.

Now, let's look into the cost side. The cost side of the unique economic model basically has two major components. First of all, it's the hardware depreciation.

It's based on a 6-year useful life.

The other major component on the cost side is the operational cost.

Which include.

The charging.

Remote assistant and the ground supporting staff.

Vehicle service and maintenance.

Insurance.

Parking.

Internet Network cost.

So, regarding the remote assistance.

From this milestone that we achieved, we are very confident to capture the China huge TAM. Meanwhile, it also established a strategic foundation for further scaling up domestically and internationally. This not only gives us strong confidence to further scale our fleet, but we also see more and more third-party companies are enabled to fund their fleet, helping us to transition into an asset-light model.

We are on track to achieve our 1 over 30 vehicles.

and from this,

Milestone that we achieved.

We are very confident in our ability to capture.

The China, huge 10.

Meanwhile, it also established a strategic foundation for further scaling up.

The magically and internationally.

This not only gives us strong confidence.

To further scale our Fleet.

But we also see more and more third parties.

Companies are enabled to fund their fleet and help us transition into an ASA light model.

Leo Wang: All these together, we believe will drive our top-line growth and also the cost optimization. Okay, I'll get back to the operator. Thank you. The next question comes from Perdy Ho with Huotai Securities. Please go ahead. Hello, James, Dr. Lu, and Leo. Thank you for taking my question, and congratulations on the results. We've observed a surge in diverse players attempting to attempt into the robotaxi operation, particularly the EV makers. What's your take on these new entrants in the Level 4 autonomous driving space? Also, specifically, could you elaborate on the main technical and operational challenges, such as tackling corner cases and fleet management, for these newcomers? Thank you. Basically, James, I'll take this one.

All these together, we believe will drive our top-line growth and also the cost optimization. Okay, I'll get back to the operator.

So, all these together, we believe will drive our topline growth and also the cost of optimization.

Operator: Thank you. The next question comes from Perdy Ho with Huotai Securities. Please go ahead.

Okay, I'll go get back to the operator.

Thank you.

Purdy Ho: Hello, James, Dr. Lu, and Leo. Thank you for taking my question, and congratulations on the results. We've observed a surge in diverse players attempting to attempt into the robotaxi operation, particularly the EV makers. What's your take on these new entrants in the Level 4 autonomous driving space? Also, specifically, could you elaborate on the main technical and operational challenges, such as tackling corner cases and fleet management, for these newcomers? Thank you.

The next question comes from Perdy Ho with Hai Securities. Please go ahead.

James, Dr. L, in real. Thank you for choosing my question, and congratulations on the results.

James Peng: Basically, James, I'll take this one. First and foremost, I think it's definitely, as we see more and more companies announcing that they're going to enter into the robotaxi industry, I think itself is actually a great thing because it indicates increasing recognition and confidence in robotaxi imminent potential for the large-scale commercialization. As the awareness increases, more resources, more companies come in, more resources will pour into this robotaxi industry to actually accelerate its development.

This observed a search in diverging diverse choices accounting to attend to the robot taxi operations, particularly the easy makers, right? So what's your take on these new entrants in the Level 4 autonomous driving space? And also, could you elaborate on the main technical and operational challenges, such as tackling corner cases and state management for legal compliance? Thank you.

Um,

Leo Wang: First and foremost, I think it's definitely, as we see more and more companies announcing that they're going to enter into the robotaxi industry, I think itself is actually a great thing because it indicates increasing recognition and confidence in robotaxi imminent potential for the large-scale commercialization. As the awareness increases, more resources, more companies come in, more resources will pour into this robotaxi industry to actually accelerate its development. Overall, I view this as a good thing. On the flip side, the robotaxi industry is actually not one that any new player can easily enter because, as you can see, the fact is that currently none of the new entrants, being an OEM maker or being ride-hailing platforms, none of them have fully driverless vehicles deployed on the open road. It's clear evidence this is not an easy industry to be entered.

This is James. Um, I'll take this one. So, our first and foremost, I think the definitely...

As we see more and more companies announcing that they are going to enter into the robo-taxi industry, I think it itself is actually a great thing because it indicates.

Uh, increasing, uh, recognition and confidence in robo-taxi, uh, imminent.

Potential for the large-scale commercialization.

Uh,

As the awareness increases, more resources.

Overall, I view this as a good thing. On the flip side, the robotaxi industry is actually not one that any new player can easily enter because, as you can see, the fact is that currently none of the new entrants, being an OEM maker or being ride-hailing platforms, none of them have fully driverless vehicles deployed on the open road. It's clear evidence this is not an easy industry to be entered.

More companies come in, and more resources will pour into this Robo taxi industry to actually accelerate its development. So overall, I view this as a good thing. But on the flip side,

Uh, the robo-taxi industry is actually not one that any new player can easily enter.

Because, as you can see, the fact is that currently, none of the new entrants, uh, being, uh, uh, OEM makers or being ride-hailing platforms, none of them have fully driverless vehicles deployed.

Leo Wang: I think there are certainly three huge hurdles for any new players. Those hurdles are business side, regulatory side, and also technical challenges. Let's probably look at the business challenges first because robotaxi, as you see, it's not just about L4 driving itself. It also has many more aspects, such as user acquisition, vehicle production, fleet dispatching, fleet maintenance, such as the cleaning, charging, and everything else. As a leader and the first mover in this industry, we certainly enjoyed the early mover advantages as we have a much bigger L4 fleet on the road. We generated better brand awareness. We have optimized the cost on every aspect of the business, as Leo already mentioned in his answer to the last question. Because of early mover, we also have secured more partners. I think all those are important and create a big hurdle for any new entrants.

I think there are certainly three huge hurdles for any new players. Those hurdles are business side, regulatory side, and also technical challenges. Let's probably look at the business challenges first because robotaxi, as you see, it's not just about L4 driving itself. It also has many more aspects, such as user acquisition, vehicle production, fleet dispatching, fleet maintenance, such as the cleaning, charging, and everything else.

Uh, on the row road. So, it's, uh, clear evidence this is not, uh, an easy industry to be entered.

Uh, I think there are certainly three.

Huge hurdles for any new players include busy size, regulatory sites, and also technical challenges.

Uh, let's probably look at the business challenges first.

because we will Taxi.

As you see, it's not just about Air Force driving itself.

Uh, it also has many more aspects, such as user acquisition.

As a leader and the first mover in this industry, we certainly enjoyed the early mover advantages as we have a much bigger L4 fleet on the road. We generated better brand awareness. We have optimized the cost on every aspect of the business, as Leo already mentioned in his answer to the last question. Because of early mover, we also have secured more partners. I think all those are important and create a big hurdle for any new entrants.

Vehicle production, fleet dispatching, fleet maintenance, as well as cleaning, charging, and everything else.

so, as a leader at the,

Uh, first mover in this industry. We certainly enjoyed the early mover advantages, uh, as...

We have a much bigger.

Alpha Fleet on the road, we generated better brand awareness. We have optimized the cost on every aspect of the business, as Leo already mentioned in his answer to the last question.

Partners. I think all those are important, and it creates a big hurdle for any new entrant.

Leo Wang: The second hurdle that I want to mention is on the regulatory front because L4, a robotaxi, needs very high safety requirements. All the policymakers worldwide fundamentally will require much, much higher safety requirements for the robotaxis compared with the traditional taxi. That means in any city, a new player needs to prove its safety step by step before they can expand even into a fully driverless fleet. Typically, a new player will start with testing with just a few dozen or maybe even fewer vehicles. Once those vehicles prove to be safe, they add more vehicles, and then expand operational areas after they can accumulate the safety records. Along the way, they also need to acquire all the required licenses and permits. This in itself is actually a lengthy process. Overall, the whole process takes time.

The second hurdle that I want to mention is on the regulatory front because L4, a robotaxi, needs very high safety requirements. All the policymakers worldwide fundamentally will require much, much higher safety requirements for the robotaxis compared with the traditional taxi. That means in any city, a new player needs to prove its safety step by step before they can expand even into a fully driverless fleet.

Uh, the second hurdle that I want to mention is, uh, on the regulatory front.

uh, because

L, for a robot taxi, needs very high safety requirements.

Uh, all the policy makers worldwide will fundamentally require much higher safety requirements for the robot taxis compared with traditional taxis.

That means in any City.

Typically, a new player will start with testing with just a few dozen or maybe even fewer vehicles. Once those vehicles prove to be safe, they add more vehicles, and then expand operational areas after they can accumulate the safety records. Along the way, they also need to acquire all the required licenses and permits. This in itself is actually a lengthy process. Overall, the whole process takes time.

A new player needs to prove its safety step by step before they can expand even into a fully driverless fleet.

Uh, typically a new player.

uh, will start with

A testing phase with just a few dozen or maybe even fewer vehicles, and then once those vehicles prove to be safe, they will add more vehicles and expand operational areas.

Uh, after they can accumulate the safety records.

And along the way, they also need to acquire all the required licenses and permits. And this, in itself, is actually a lengthy process.

Leo Wang: This code-starting process cannot be easily accelerated. That is the second challenge. The third challenge, certainly in my view, is on the technical side. Probably for this one, I'll tend to elaborate. Yeah, sure. I'm Tiancheng. Let me continue from a technology perspective. As I said in my preparatory remarks, we are now seeing the broader industry starting to use world models, such as robotaxi players and automakers. Essentially, they are all about using reinforcement learning based on simulation training environments. First and foremost, I will say we started developing reinforcement learning for autonomous driving five years ago. This gives us an early mover advantage. We have one of the most experienced companies in the world model. We believe that we will continue to stay ahead as more players follow the same path.

This code-starting process cannot be easily accelerated. That is the second challenge. The third challenge, certainly in my view, is on the technical side. Probably for this one, I'll tend to elaborate.

So overall, the whole process takes time, and this code starting process cannot be easily accelerated.

Tiancheng Lou: Yeah, sure. I'm Tiancheng. Let me continue from a technology perspective. As I said in my preparatory remarks, we are now seeing the broader industry starting to use world models, such as robotaxi players and automakers. Essentially, they are all about using reinforcement learning based on simulation training environments.

So, that's the second challenge. The third challenge, certainly in my view, is on the technical side. As for the problem for this one, I'll tend to elaborate.

Yeah, sure. So, um, Tina. So let me continue from a technology perspective.

First and foremost, I will say we started developing reinforcement learning for autonomous driving five years ago. This gives us an early mover advantage. We have one of the most experienced companies in the world model. We believe that we will continue to stay ahead as more players follow the same path.

So, as a side in my prepare, my remarks, and we are not saying in the broader industry, starting to use the word 'model', such as robotics players and automakers, essentially, they are all about using reinforcement learning based on simulation training environments.

First and foremost, we started developing reinforced learning for account driving 5 years ago. This gave us an early move advantage. This has one of the most experienced company models in the world.

He believes that he will continue to stay ahead as more peers follow the same path.

Leo Wang: Once the world model matured, I would say human feedback and real-world data are no longer used for further iterations. At the stage of training closed-loop, the world model and the virtual driver co-evolve into a dual spiral cycle. This means the world model is training the virtual driver, and at the same time, the world model improves itself through feedback of the virtual driver. This sharply reduces reliance on the real-world data. The question was touched on the technical challenge for the meeting of corner cases. Maybe an example here that when the virtual driver meets some corner cases, this can give feedback to the world model, and the world model will improve its distribution of the corner cases.

Once the world model matured, I would say human feedback and real-world data are no longer used for further iterations. At the stage of training closed-loop, the world model and the virtual driver co-evolve into a dual spiral cycle. This means the world model is training the virtual driver, and at the same time, the world model improves itself through feedback of the virtual driver.

So, once the world mode matured, I was human feedback and the real-world data was no longer used for further iterations.

This sharply reduces reliance on the real-world data. The question was touched on the technical challenge for the meeting of corner cases. Maybe an example here that when the virtual driver meets some corner cases, this can give feedback to the world model, and the world model will improve its distribution of the corner cases.

So, at the stage of training closed, the world model and the world driver co-evolve into a new spiral cycle. This means world models train the virtual driver, and at the same time, the world model includes self through feedback from the virtual driver.

This sub to reduce Reliance on the world data.

Leo Wang: The next generation of next version of world model will be able to create or generate and testing and also improving the capability of the virtual driver to handle the corner cases. Okay, looking ahead, our real advantage lies in the ability to validate new technology safely and deploy them at scale. Based on our proving track record of scaling robotaxi operations, we believe we can quickly capture the next wave of innovation. Also, last but not least, our current Hong Kong IPO will further accelerate R&D and iteration cycles, reinforcing our technical leadership and widening our competitive moat. Yeah, with that, I'll back to the operator. Thank you. The next question comes from Jia Yi Li with Jefferies. Please go ahead. Thanks for taking my question. I have one as well.

The next generation of next version of world model will be able to create or generate and testing and also improving the capability of the virtual driver to handle the corner cases. Okay, looking ahead, our real advantage lies in the ability to validate new technology safely and deploy them at scale. Based on our proving track record of scaling robotaxi operations, we believe we can quickly capture the next wave of innovation.

The cultural touch on the technical challenge for the meeting, the corner cases, maybe an example here that when the Virtual Drive meets some corner cases, this can give you feedback to the world model, and the world model will improve its distribution of the corner cases. Then, the next generation of the next virtual world model will be able to create, generate, and test, and also improve the capability of the world to handle the communicators.

Okay, so looking ahead, our real advantage lies in our ability to validate new technology safely and deploy it at scale.

Also, last but not least, our current Hong Kong IPO will further accelerate R&D and iteration cycles, reinforcing our technical leadership and widening our competitive moat. Yeah, with that, I'll back to the operator.

So, based on our proven track record of scaling robotics operations, we believe we can quickly capture the next wave of innovation.

Also, last but not least, our kind of Hong Kong IPO will further accelerate, Andy, and iteration cycles, reinforcing our technical leadership and widening our competitive moat.

Purdy Ho: Thank you.

Yeah, with that, back to the operator.

Operator: The next question comes from Jia Yi Li with Jefferies. Please go ahead. Thanks for taking my question.

Thank you.

The next question comes from J.

You lie with Jeffrey's. Please, go ahead.

Xiaoyi Lei: I have one as well. My question is about what do you see as the main factors behind the faster expansion of your operational areas? Beyond technology, what else do you think really matters? From the technical perspective, are you using large language models? If so, how are they helping push L4 autonomy forward? Thank you.

Leo Wang: My question is about what do you see as the main factors behind the faster expansion of your operational areas? Beyond technology, what else do you think really matters? From the technical perspective, are you using large language models? If so, how are they helping push L4 autonomy forward? Thank you. Thank you. This is Tiancheng. I will continue to answer this question. I think your question consists of two parts. Let me answer your question on generalization first. I will address the other one on large language model later. For generalization, I would say technically, our tech stack is by nature built for generalization. A good example is that our operational area expansion into new areas in Shanghai, Pudong, and Shenzhen, Nanshan District in the South Quarter.

Tiancheng Lou: Thank you. This is Tiancheng. I will continue to answer this question. I think your question consists of two parts. Let me answer your question on generalization first. I will address the other one on large language model later. For generalization, I would say technically, our tech stack is by nature built for generalization. A good example is that our operational area expansion into new areas in Shanghai, Pudong, and Shenzhen, Nanshan District in the South Quarter.

Thanks for taking my question. Uh I have 1 as well. Um, my question is about what do you see as the main factors behind the faster expansion of your operational areas and Beyond technology or else? Uh, do you think uh really matters uh and from the technical perspective? Uh are you using large language models? Uh, and if so how are they helping push? Uh, for autonomy for forward, thank you.

Uh, thank you. This is Tina. I have continued to answer this question, but I think your question consists of two parts. But let me answer your question on organization first. Then I will address the other one, large language model, later.

Fraternization. I was a Tech, technically, uh, over Tech stack. It's by nature. Beautiful journaling.

Leo Wang: In both cases, it only took us a few weeks from verifying the city to truly realizing fully driverless operations to the public. There was no need for additional model training. The key reason is that L4 native architecture is built for handling corner cases and edge cases, while these cases are actually very consistent across different regions. They are really nothing more than things like small obstacles, boxes on the road, pedestrians that are crossing, and suddenly lane changes from other cars without looking at the vehicle behind, etc. It's just about the likelihood and the probabilities of each one happening. I hope that can help understand why the L4 tech stack is by nature built for generalization. At this moment, I will say the key to our new area expansion is the number of robotaxi vehicles.

In both cases, it only took us a few weeks from verifying the city to truly realizing fully driverless operations to the public. There was no need for additional model training. The key reason is that L4 native architecture is built for handling corner cases and edge cases, while these cases are actually very consistent across different regions. They are really nothing more than things like small obstacles, boxes on the road, pedestrians that are crossing, and suddenly lane changes from other cars without looking at the vehicle behind, etc.

Know that our operational area extended into new areas in Shanghai, Pudong, and Shenzhen, Nan District in the third quarter. In both cases, it only took us a few weeks from verifying the city to truly realizing fully reserved operation to the public.

There was no need for additional model training.

The quick key reason that our native architecture is beautiful is Henry Corner cases and Jim cases, while these cases are actually very consistent across different regions.

It's just about the likelihood and the probabilities of each one happening. I hope that can help understand why the L4 tech stack is by nature built for generalization. At this moment, I will say the key to our new area expansion is the number of robotaxi vehicles.

They are really nothing more than small obstacles, like boxes on the road for pedestrians. Starting a crossing and suddenly changing lanes from other cars without looking at the vehicle behind, etc.

So, it is just about the likelihood and the probabilities of each one happening.

The hope that can help understand why the awful tech stack is, by nature, built for generalization.

Leo Wang: If we expand to too many areas without adding more cars, it will instead dilute the density. That is the reason why the speed of operational area expansion cannot be significantly faster than that of the size. Let me share my thought on the second part, that's a large language model. First, I will say first and foremost, there are two non-negotiable requirements for L4 onboard driving model: uncompromising safety, and also low latency. The large language model and chatbot do not meet these, and they are not designed to meet them as well. For safety, large language models generally have issues like mode health in nature, which is unacceptable for L4 in terms of safety. For latency, large language models are optimized for throughput like tokens per second.

If we expand to too many areas without adding more cars, it will instead dilute the density. That is the reason why the speed of operational area expansion cannot be significantly faster than that of the size. Let me share my thought on the second part, that's a large language model.

So at this moment, I would say the key to our new area extension is this number. We have a number of robotics vehicles.

If we extend to too many areas without adding more cars, it will instead dilute the density.

So, that is the reason why the speed of operation area extension cannot be significantly faster than that of precise.

So then then, uh,

First, I will say first and foremost, there are two non-negotiable requirements for L4 onboard driving model: uncompromising safety, and also low latency. The large language model and chatbot do not meet these, and they are not designed to meet them as well. For safety, large language models generally have issues like mode health in nature, which is unacceptable for L4 in terms of safety. For latency, large language models are optimized for throughput like tokens per second.

Let me share my thoughts on the second part that large language model.

First, I will say, first and foremost, there are 2 non-negotiable requirements for Level 4 onboard driving model.

Uh, on compromising safety and also low latency.

There are large languages that don't need to be designed to meet as well.

So, for Safety Last, we went large, large landing models. Generally have issues like more healthy nations.

Which, which is unacceptable for L4 in terms of safety.

Leo Wang: In contrast, L4 is optimized for low latency and the ability to run fully driverless robotaxi on chips that are both low power consumption and cost-efficient. Moreover, large language models overly run human data, which fundamentally limits them to the boundary of the existing human knowledge, as it inevitably makes them pick up human errors and bad habits from human drivers. We also extensively use large language models in the R&D effort, such as AI-enhanced human-machine interaction, engineering productivity tools for coding and documentation, and analysis for the rider's feedback for experience improvement. However, due to the multiple reasons mentioned above, large language models are by nature not built for driving models onboard. With that, back to the operators. Thank you. Thank you. That's very helpful. The next question comes from Jin Yu Feng with UBS. Please go ahead. Hi.

In contrast, L4 is optimized for low latency and the ability to run fully driverless robotaxi on chips that are both low power consumption and cost-efficient. Moreover, large language models overly run human data, which fundamentally limits them to the boundary of the existing human knowledge, as it inevitably makes them pick up human errors and bad habits from human drivers.

And for latency large l. L models are optimized for throughput like tokens per second. In contrast our for the optimized for low latency and the ability to run fully drive this over tax on chips. That are both low power consumption and the cost efficient

Moreover, our model performs better over the long run compared to human data.

Uh, which fundamentally limits them to the boundary of the existing human knowledge?

We also extensively use large language models in the R&D effort, such as AI-enhanced human-machine interaction, engineering productivity tools for coding and documentation, and analysis for the rider's feedback for experience improvement. However, due to the multiple reasons mentioned above, large language models are by nature not built for driving models onboard. With that, back to the operators. Thank you.

Add anything, you have inevitably makes them pick up human errors and bad habits from humans, right?

So we also extensively use a large language model in the IMD effort, such as AI-enhanced human-machine interaction, engineering productivity tools for coding and documentation, and analysis for the writer feedback for exchange improvement. However, due to the multiple reasons mentioned about large language models, they are, by nature, not well-suited for driving models on board.

Xiaoyi Lei: Thank you. That's very helpful.

So, with that, back to the operator. Thank you.

Thank you.

Operator: The next question comes from Jin Yu Feng with UBS. Please go ahead.

For helpful.

Xinyu Fang: Hi. Thank you, Mancheng, for taking my questions. I have one question here. It is currently that Pony cooperates with multiple OEMs for robotaxi manufacturing, including BAIC, GAC, and Toyota. Does Mancheng see potential for improving operating leverage through working with only one OEM team staff? Thank you.

The next question comes from Jin Yu Fong with UBS. Please go ahead.

Leo Wang: Thank you, Mancheng, for taking my questions. I have one question here. It is currently that Pony cooperates with multiple OEMs for robotaxi manufacturing, including BAIC, GAC, and Toyota. Does Mancheng see potential for improving operating leverage through working with only one OEM team staff? Thank you. This is James. I'll take this one. The matter of the reality is that in the whole global taxi industry, local governments and the local residents actually have strong preferences for the local branded taxi vehicles. That's the reality. Typically, when a robotaxi fleet is relatively small, the brand doesn't really matter much. If we need to deploy a significant fleet size, the requirements certainly are no longer true, and the local branded OEMs are much more preferred. It is necessary for us to cooperate with multiple local OEMs in different regions.

James Peng: This is James. I'll take this one. The matter of the reality is that in the whole global taxi industry, local governments and the local residents actually have strong preferences for the local branded taxi vehicles. That's the reality. Typically, when a robotaxi fleet is relatively small, the brand doesn't really matter much. If we need to deploy a significant fleet size, the requirements certainly are no longer true, and the local branded OEMs are much more preferred. It is necessary for us to cooperate with multiple local OEMs in different regions.

Hi. Thank you management for taking my questions. Um, I have 1 question here. Uh, it is currently the home in cooperate with multiple oems for uh robot taxing manufacturing, including Bic, uh, Jac and Toyota. Uh, this makes me see potential for improving operating leverage through. Working with only 1 OEM team staff. Thank you.

Uh this is Jeff's. I'll take this 1. So uh the uh matter of the reality is that in the whole Global Taxi industry.

Uh, local governments and the local residents actually have a strong preference for the, uh, local branded taxi vehicles.

So so that's a reality. Uh, typically

While, uh, the robot taxi fleet is relatively small, uh, the brand— but that doesn't really matter much. But if...

We need to deploy a significant fleet size. The requirements, uh, certainly are no longer true, and the local branded OEMs are much more preferred.

Leo Wang: It actually can help us to expand into different markets much quickly. That's why we are now collaborating with three OEMs to produce our Gen7 Robotaxis. It is true that fitting our autonomous driving kit into different vehicles actually poses a huge technical challenge. If you look at it from the other side, the mere fact that we were able to standardize our technology and being able to fit our setup into different vehicles, that shows our technical generalization. Down the road, it actually can create a huge competitive edge. As a result, we can add new models much faster to accelerate our expansion into new regions. For example, in Europe, we currently added the partnership with Stellantis. With that, I'll back to the operator. The next question comes from Tang Zhu Jia with Guoshen. Please go ahead. Thanks for taking my question.

It actually can help us to expand into different markets much quickly. That's why we are now collaborating with three OEMs to produce our Gen7 Robotaxis. It is true that fitting our autonomous driving kit into different vehicles actually poses a huge technical challenge. If you look at it from the other side, the mere fact that we were able to standardize our technology and being able to fit our setup into different vehicles, that shows our technical generalization.

So, it is necessary for us to cooperate with multiple local OEMs in different regions. This collaboration can help us expand into different markets much more quickly, and that's why we are now collaborating with three OEMs to produce our Gen 7 Robo taxis.

uh but on the if you look at from the other side, the mere fact that we were able to standardize our technology and being able to see our setup into different vehicles that shows

uh,

Down the road, it actually can create a huge competitive edge. As a result, we can add new models much faster to accelerate our expansion into new regions. For example, in Europe, we currently added the partnership with Stellantis. With that, I'll back to the operator.

Our technical generalization, and down the road, it actually can create a huge competitive edge.

so, as a result,

We can add new models.

Much faster to accelerate our expansion into new regions. For example, in Europe, we have currently added the partnership with Stantis.

Operator: The next question comes from Tang Zhu Jia with Guoshen. Please go ahead.

So with that, I'll back to the operator.

Tang Xuxia: Thanks for taking my question.I have one question. Why can Pony use remote assistant on robotaxi when the car meets difficulty instead of remote control or human takeover? What is the technology difference behind that?

The next question comes from Tongue. Zuzia with Grossen, please go ahead.

Leo Wang: I have one question. Why can Pony use remote assistant on robotaxi when the car meets difficulty instead of remote control or human takeover? What is the technology difference behind that? This is Tiancheng. I will take this one. I think one of the previous questions also touched on the remote assistant for robotaxi. Let me elaborate on that in a little more detail. First, I'll promote that the remote assist never controls the vehicle through the steering wheel or pedal. Instead, they provide remote support and suggestions by responding to service requests. For all the time, the vehicle can independently drive and independently make decisions without remote assistance. Assistance only initiates when a vehicle requests it rather than through remote driving. When a vehicle receives the assistance response, the onboard driving system will still make timely decisions based on the actual situation.

Thanks for taking my question. I have one question. Why can Pony use a remote assistant on remote taxis when the car meets difficulty instead of remote control or a human takeover? What is the technology difference behind that?

Tiancheng Lou: This is Tiancheng. I will take this one. I think one of the previous questions also touched on the remote assistant for robotaxi. Let me elaborate on that in a little more detail. First, I'll promote that the remote assist never controls the vehicle through the steering wheel or pedal. Instead, they provide remote support and suggestions by responding to service requests.

Uh, they intend to take this 1.

Oh, I think one of the previous questions also touched on the remote system for robot taxis. So let me elaborate on that a little more.

First and foremost, I say, over remote assist, never control the vehicle through the same wheel or pedal.

For all the time, the vehicle can independently drive and independently make decisions without remote assistance. Assistance only initiates when a vehicle requests it rather than through remote driving. When a vehicle receives the assistance response, the onboard driving system will still make timely decisions based on the actual situation.

instead they provide remote support and suggestions by responding to service requests

For all this time, the vehicle can independently drive through this environment and make decisions without remote assistance.

Assistance, only initiates 1 a vehicle requested.

Rather than through the remote driving.

Leo Wang: Because the vehicle never waits for remote command to act, it remains safe operating without any dependence on network latency. One typical example of remote assistance is the situation of a temporary traffic control. In such cases, the system may request remote assist, which can provide high-level suggestions to confirm the car's decision, navigating through the scenario. Also, as I mentioned, we have continuously improved AI algorithms and leveraged general AI capability to recognize more and more complex contexts. This allows us to improve remote assist to vehicle ratio in the third quarter to reach 1 to 30 by year-end. I hope that can answer your question. Back to the operator. Thank you. The next question comes from Serena Li with China Securities. Please go ahead. Thank you for taking my question. This is Serena Li from China Securities.

Because the vehicle never waits for remote command to act, it remains safe operating without any dependence on network latency. One typical example of remote assistance is the situation of a temporary traffic control. In such cases, the system may request remote assist, which can provide high-level suggestions to confirm the car's decision, navigating through the scenario.

So 1 vehicle received the assistant response, the on board driving system will still make timely decision based on the actual situation.

Because the vehicle never wait for remote command to re to act.

Also, as I mentioned, we have continuously improved AI algorithms and leveraged general AI capability to recognize more and more complex contexts. This allows us to improve remote assist to vehicle ratio in the third quarter to reach 1 to 30 by year-end. I hope that can answer your question. Back to the operator.

One example of remote assistance is the situation of a temporary traffic control in such cases. The system may request remote assist, which can provide high-level suggestions to confirm the cost decision while navigating through the scenario.

But also, as I mentioned, we have continuously improved our AI algorithm and also leveraged a general AI capability to recognize more and more complex contact contexts.

This allows us to improve remote access to vehicle ratio in. So, third quarter to reach 1 to 30 by year end.

Tang Xuxia: Thank you.

The computer can answer a question. So back to the operator.

Operator: The next question comes from Serena Li with China Securities. Please go ahead.

Thank you. The next question.

Serena Li: Thank you for taking my question. This is Serena Li from China Securities. As far as we know, some countries in the Middle East have issued fully driverless robotaxi licenses recently. What's our view on that? What's Pony's overseas strategy?

The next question comes from Serena Lee with China Security. Please go ahead.

Leo Wang: As far as we know, some countries in the Middle East have issued fully driverless robotaxi licenses recently. What's our view on that? What's Pony's overseas strategy? Sure. This is James again. Let me take this one. Our company's mission has always been autonomous mobility everywhere. So we certainly have the global ambition, since our funding, to actually utilize our technology to benefit the local societies worldwide. Currently, our global efforts are focused on the markets with hyper-growth potential. So those are the markets with typically strong mobility demand, well-developed infrastructure, and a supportive regulatory environment. When we evaluate a potential market to enter, on a high level, three factors we will consider. One is the adjustable market size, which is 10. Second is the openness and the execution of the local government to support and issue permits for the fully driverless commercial operation.

James Peng: Sure. This is James again. Let me take this one. Our company's mission has always been autonomous mobility everywhere. So we certainly have the global ambition, since our funding, to actually utilize our technology to benefit the local societies worldwide. Currently, our global efforts are focused on the markets with hyper-growth potential. So those are the markets with typically strong mobility demand, well-developed infrastructure, and a supportive regulatory environment.

Okay. Thank you for taking my question. This is Serena from China Security. As far as we know, some countries in the Middle East have issued fully driverless global taxi licenses recently. What's our view on that? What forms overseas to strategy?

Uh, sure, this is James again. Uh, let me take this one. Uh, our company's mission has always been autonomous mobility everywhere. So we certainly have the global ambition, since our funding, to actually utilize our technology to benefit the local societies worldwide.

When we evaluate a potential market to enter, on a high level, three factors we will consider. One is the adjustable market size, which is 10. Second is the openness and the execution of the local government to support and issue permits for the fully driverless commercial operation.

Uh current our Global efforts are focused on the markets with Hyper growth potential. So those are the markets with uh typically strong Mobility demand. Well developed infrastructure uh as a supportive regulatory environment.

Uh, when the evaluate a potential Market to enter, uh, on a high level 3 factors. We will consider, 1 is the, uh, adjustable Market size, which is 10. Uh, second is the openness and, uh, uh, the execution of the local government to support and issue permits for the fully driverless commercial operation

Leo Wang: Third is how strong is the local partner for their on-the-ground resources and operational capacities. So as you can see, our current global expansion status is that we have already entered eight countries for our robotaxi. And we also, for example, in Q3, we added Qatar as a new market by collaborating with Movasalet. In Q3, we have also saw rapid revenue growth, especially for the robotaxi from our overseas markets. And we certainly expect this momentum to continue. So going forward, we will enter other global markets if we see there's good growth opportunities. So this is our overseas strategy. With this, back to the operator. As there are no further questions, I'd like to turn the call back over to the company for closing remarks. Thank you, operator. This is George again. If anyone has any more questions, feel free to contact our team.

Third is how strong is the local partner for their on-the-ground resources and operational capacities. So as you can see, our current global expansion status is that we have already entered eight countries for our robotaxi. And we also, for example, in Q3, we added Qatar as a new market by collaborating with Movasalet. In Q3, we have also saw rapid revenue growth, especially for the robotaxi from our overseas markets.

Third, how strong is the local partner for their underground resources and operational capacities?

Entered 8 countries for our Robo Taxi.

For example, in Q3 we added, uh, Qatar as a new market by collaborating with mobile.

And we certainly expect this momentum to continue. So going forward, we will enter other global markets if we see there's good growth opportunities. So this is our overseas strategy. With this, back to the operator.

Uh, in Q3 we have also saw a rapid Revenue growth. Uh, especially for the robo taxi for our over from our overseas markets.

And we certainly expect this momentum to continue.

So, going forward.

We will enter other global markets if we see, uh, there's a good growth opportunity.

so, this is our

Operator: As there are no further questions, I'd like to turn the call back over to the company for closing remarks.

Overseas strategy with this back to the operator.

George Shao: Thank you, operator. This is George again. If anyone has any more questions, feel free to contact our team. We will conclude our call today. Thank you, everyone.

As there are no further questions, I'd like to turn the call back over to the company for closing remarks.

Leo Wang: We will conclude our call today. Thank you, everyone. This concludes today's conference call. We thank you all for attending today's presentation. You may now disconnect your line.

Operator: This concludes today's conference call. We thank you all for attending today's presentation. You may now disconnect your line.

Thank you, operator. Um, this is George. Again, if anyone has any more questions, feel free to contact our team. We will conclude our call today. Thank you, everyone.

This concludes today's conference call. We thank you all for attending today's presentation. You may now disconnect your line.

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