Pony AI

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小马智行2026Q2业绩直播

Key Takeaways (AI-Generated)

Financial Performance

- Total revenue surged 69% year-over-year to $36.2 million in Q2 2026

- Robotaxi revenue jumped 691% year-over-year to $12.1 million, accelerating from Q1's 395% growth

- Operating loss margin improved dramatically from -285.6% to -181.5%, narrowing over 100 percentage points

- Net loss narrowed 14.9% year-over-year to $45.4 million despite significant revenue growth

Business Highlights

- Expanded robotaxi fleet to 2,000 vehicles with year-end target of 3,500 vehicles

- Surpassed 1.5 million registered users and secured over 4,000 vehicle commitments with overseas partners

- Launched Europe's first capital city center robotaxi service in Zagreb, Croatia

- Upgraded to PonyWorld 2.0 AI framework enabling rapid city expansion with minimal engineering resources

Financial Guidance

- On track to exceed original robotaxi revenue outlook of 3.5 times last year's level

- Target expansion to 26 cities by year-end from current operations

- Expect robotruck growth momentum to persist and strengthen in second half 2026

- Joint deployment model expected to drive top-line growth with improved capital efficiency

Opportunities

- International expansion through joint deployment model with over 4,000 committed vehicles from partners

- L4 light truck business development leveraging robotaxi technology for urban delivery market

- Strategic partnerships with Uber, SF Express, and China Post Technology for market expansion

- Operational efficiency gains through 3:100 staff-to-vehicle ratio versus traditional 1:1 model

Full Transcript (AI-Generated)

Operator

Ladies and gentlemen, thank you for standing by and welcome to Pony AI Inc Second Quarter 2026 Earnings Conference Call. At this time, all participants are in 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 IR dot Pony dot AI.

I will now turn the call over to your host, George Xiao, Head of Capital Markets and Investor Relations at Pony dot AI. Please go ahead, George.

George Xiao

Thank you, operator and hello everyone. We appreciate you joining us today for Pony AI second quarter 2026 earnings call. Earlier today, we issued a press release with our financial and operating metrics, which is available on our IR website. An earnings presentation, which we will refer to during the conference call can also be accessed and downloaded on our Investor Relations website.

Joining me on today's call are Doctor James Peng, Chairman of the Board and Chief Executive Officer, Doctor Tiancheng Luo, Chief Technology Officer and Doctor Liu Wang, Chief Financial Officer of the company. They will provide prepared remarks followed by a Q and A session before we begin.

Please refer to the Safe Harbor statement in our earnings release which applies to this call as we will be making forward-looking statements. Please also note 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 IR website and filings with the SEC and the Hong Kong Stock Exchange.

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

Doctor James Peng

Thank you, George. Hello everyone. Thank you for joining our earnings call today. We delivered another fantastic quarter highlighted by multi fold expansion across the board. First, strong top line growth. Total revenue surged by 69% year over year, driven by a close to 8 times jump in robotaxi revenue and over 9 times surge in fare charging revenue.

Second, rapid fleet scaling. Our robotaxi fleet expanded to 2000 vehicles, putting us on track to deliver 3500 vehicles by year end. Third expanded deployment. Domestically, we reinforced our leadership in tier one cities as we surpassed 1.5 million registered users. We also improved our network density with more deployed vehicles and operational coverage.

Internationally, we unlocked demands by scaling our joint deployment model. Currently, we have secured over 4000 vehicle commitments with Uber and other overseas partners. The expanded deployment in both China and overseas markets clearly shows that our dual engine strategy is turning into robust top line growth.

Looking at our domestic operations first, the L4 industry in China is entering a new phase where higher standards are required to keep the industry on a sustainable healthy trajectory. For any robotaxi company to enter into large scale deployment, it now needs proven driverless capabilities, positive user satisfaction and verified safety records. We are perfectly positioned to capitalize on this shift because we have already been operating well ahead of this curve.

This rising standards will only widen our competitive moat and solidify our leadership in China. Our confidence actually is grounded in solid results from commercial robotaxi operations. We have 3 Gen. 7 robotaxi vehicle models in our daily services including the GAC Aion RT, the BAIC Arkfox Alpha T5, and the Toyota BZ 4X, we are continuously improving user experience, which is the key driver for our organic user growth.

As our total registered users had surpassed 1.5 million in Guangzhou, we extended our robotaxi services into the city center, now adding over 300 square kilometers since the beginning of this year. The operational area spans across Haizhu, Panyu, Huangpu and Baiyun districts, covering a population of over 7 million. As a result, our driverless fleet is positioned to capture highly concentrated urban mobility demands.

Shenzhen, known as China's Silicon Valley, serves also as a great showcase of our capability to navigate highly complex traffic scenarios. Our operational resilience was rigorously validated by corner cases such as the high demand holidays such as the Dragon Boat Festival, the peak rush hours and heavy rainstorms. Despite this demanding conditions, we effectively met high frequency commuting demands.

In addition, by seamlessly integrating 3 major transit hubs, including Baoan International Airport, Shenzhen Bay Port and The Shekou Cruise Port, we further expanded our network to provide users with greater convenience and more mobility options.

Now turning into our global expansion to meet the ever increasing demand of L4 mobility in overseas markets, we have entered more international markets with huge consumer demand and the commercial potential. We are using our joint deployment model to form global alliance, fulfilling autonomous mobility demands in this international markets and creating values for our partners.

To that end, we collaborate with multiple partners to accelerate our international pipeline. Currently, we have secured over 4000 vehicle commitments led by over 2000 robotaxis across 5 European cities with Uber alongside commitments from some other partners. Meanwhile, we continue to deepen our operations in existing markets.

In Luxembourg, our deployment with Bolt and Celantis keeps moving forward. And in Singapore, our service is now officially live for the general public on ComfortDelGro ride hailing app called Zig. This international demands are a direct endorsement of our Gen. 7 robotaxi operations in China's tier one cities where we have proven our superior driving capability, reliable 24/7 operations, high user satisfaction and positive UE.

I'm confident that this proven model will continue to win partners with more vehicle deployment commitments and drive user adoption globally. Now let me elaborate a bit more on our joint deployment model. As we expand our fleet across China and overseas, we leverage existing local ecosystems and our partners on the ground expertise to drive capital efficient expansion.

I am very pleased to share that the model is already delivering strong tangible commercial results. First look at the strong, the monetization was validated in Q2 by broadening our partnerships. We delivered significant quarter over quarter growth in revenue contribution. That's a direct proof point of this JDM models financial viability.

Second, the joint deployment model is the asset light one, where our partners fund the fleet this fundamentally enables fastest scaling lower unit costs and the superior capital efficiency for our fleet expansion. Third with best scaling JDM essentially unlocks massive commercial value for years to come. For example, we recently expanded our partnership with Uber to pocket at premium markets.

This creates a highly repeatable growth engine, allowing us to attract more partners and deliver even higher growth trajectory. Now let's move to our Robotruck business. Our Robotruck business delivered outstanding results in Q2 with revenue jumping more than 40% year over year. We actually expect this growth momentum to persist and even strengthen in the second-half of this year.

We continue to expand our long haul operations with Sinotrans through our joint venture. At the same time, our Gen. 4 robo trucks have entered mass production and already begun commercial operations. Working with China Merchants Port, we launched our commercial deployment of robo trucks at Shekou Mawan Port, where our fully driverless robo trucks operate together with other human driven trucks.

This success highlights our unique cross segment synergies. We have leveraged our rich operational experience from urban robotaxis and long haul robo trucks to enable our trucks to seamlessly navigate traffic interactions at the ports. As we pass the midpoint of the year, our acceleration across both domestic and international markets puts us well on track to surpass our 26 city goal by year end.

In China's tier one cities, we will continue to deploy more vehicles to our fleet to widen our competitive moat and advance our scaling edge. And at the same time, we are on track to enter multiple domestic new markets. Internationally, the joint deployment model will contribute top line growth with great capital efficiency.

This dual momentum gives us greater confidence in beating our original Robotaxi revenue outlook, which is exceeding 3.5 times last year's level. Looking ahead, our focus remains clear, delivering long term value creation and driving the commercialization of autonomous driving with capital efficiency. Now I'll hand it over to our CTO, Tiancheng to go over the technology progress. Tiancheng, please go ahead.

Doctor Tiancheng Luo

Thank you, James. Hello everyone, this is Tiancheng. To start. Our strong Q2 momentum is driven by our unique tech stack. This foundation allows us to scale rapidly and adopt seamless checkouts both domestic and international markets. Starting with our domestic market, This is where we validate our technology in most challenging scenarios and translate this mastery into commercial value.

Tier one cities such as Guangzhou and Shenzhen are clear examples. In older urban cores and the major transit hubs, roads are narrow, residential neighborhood are dense and roadside parking are common. Our world model and virtual drivers prove to be more agile and precisely in navigating this extreme conditions automated delivering high commercial returns than regular scenarios.

We also rapidly replicate this success to more high premium urban market globally. Traffic rules and driving habits vary significantly across China, Europe, the Middle East and Asia. Despite its fundamental region differences, our robust generalization enables rapid deployment. Our proven technical track record, especially in tier one cities of China and the Zagreb of Croatia, is exactly why top tier partners are choosing to scale with us through our joint deployment model.

Beyond the driving capability, another key engine behind our extension is efficiency. Let me now elaborate on how our unique technical and operational capabilities deliver these efficient benefits. As I shared in previous quarters, the key to enabling robotaxi to seamlessly navigate diverse urban environment lies in our world model precision.

This is what bridges gap of so-called sim to real in physical AI in auto driving. Closing the gap comes down to modeling probability distribution of different behaviors among traffic participants. For example, the probability of the pedestrian standing on the roadside suddenly jaywalking varies from city to city. A high precision world model actually accurately captures this dynamics, enabling the virtual driver to handle such scenarios with confidence over current.

Upgraded PonyWorld 2.0 brings this precision alignment into closed loop engineering. The system automatically isolates deeply hidden issues, generate targeted solutions, and validates them for real world deployment, reducing the need for human engineers to analysis cases one by one. This also dramatically accelerates our development timeline.

The old way of entering a new city takes dozens of engineers doing manual works to review local driving issues, analysis root cause of these issues, upgrade the world model and retrain the onboard models, and then deploy and validate the new model on the road. However, with PonyWorld 2.0, our system leverages AI to resolve this local changes automatically.

This turns city's extension from effort that used to take a dozen of engineers into the human loop automatic process that just a few people can run. So for example, when we went to the Zagreb, we noticed local drivers almost never slowed down when they hold the right away, even near blind spot. PonyWorld 2.0 caught this difference automatically and we quickly trained a new version of virtual driver that fits local habit perfectly with very few engineers involved.

As a result, we can now launch in multiple cities with completely distinct driving environment all at once. This scalability ensure we efficiently achieve our target of 20 cities by the end of this year. This gives us the unique efficiency advantage to scale our footprint far more rapidly.

On the operational side, we are also using technology to redefine efficiency. For example, we don't need a closed dedicated parking lot to charge our cars over. Our robotaxis can share normal parking lot with human drivers, the drivers themselves to find an open charging spot without human intervention. This means a tiny ground team can easily manage charging and service for a large fleet.

This optimizes personnel allocation and lower over UE cost. The vehicle to staff ratio for our ground support and remote assistant team has improved significantly. More importantly, it also boosts the willingness of industry partners to adopt our joint deployment model. So as James mentioned, multiple partners such as Uber are clear examples.

In short, our tech driven efficiency give us a unique operation leverage as we scale across new markets. This not only reinforce our competitive moat but also positions our technical innovation as a core engine driving the entire industry forward. This concludes my prepared remarks. I will now pass the call over to our CFO, Doctor Leo Wang for a closer look at our financial result. Leo, please go ahead.

Doctor Leo Wang

Thank you, Tiancheng. Hello everyone. This is Leo. I will focus on year over year comparisons for the second quarter and the first half of 2026 unless otherwise noted. For detailed financials, please refer to our earnings release. This quarter total revenues reached 36.2 million U.S. dollars, representing a remarkable 69% increase from 21.5 million U.S. dollars in the same quarter last year.

Breaking down this strong top line growth by business segment, most notably our Robotaxi revenue are growing 691%. And the robo truck revenues growing 40%. Our phenomenal triple digit robotaxi growth is a strong demonstration that our commercialization strategy is translating into good financial numbers.

Look deeper into robotaxi, we delivered a very strong growth this quarter. Robotaxi revenues reached a record high of 12.1 million U.S. dollars, growing 691%, a further acceleration from the 395% growth compared to the first quarter. Our fare charging revenue delivered a exceptional growth rate of 849 percent.

These rapid growth rates show that robotaxi continues to serve as our core growth engine, this acceleration was driven by several factors. First, our fare charging fleet continued to expand across more regions and specifically into core downtown areas with high economic values. Second, our joint deployment model gained a significant momentum and our commercial robotaxi launched in Zagreb, Croatia has served as a powerful showcase as the first of its kind in the city center of a European capital.

Zagreb has proved our high quality service in the demanding international market and enabled us to secure additional overseas contracts under the joint deployment model. We are currently recognizing upfront vehicle delivery revenues which establish a solid foundation for us to having high margin recurring revenue sharing income going forward as our fleet operations scale.

What is particularly encouraging is that this acceleration is broader based, not concentrated in a single market. In China. In this quarter, we continue to strengthen our leading position in tier one cities with fast growing scale and a strong user base. Overseas, we are building a alliance that accelerates our global footprint.

For example, we have secured over 4000 initial vehicle deployment commitments with Uber and other overseas partners. Our continuous expansion in China and overseas while translating into a rapidly increasing base of recurring robotaxi revenues turning into robotruck. The revenue grew 40% year over year to 13.3 million U.S. dollars this quarter.

This growth was driven by increased logistic transportation revenues. Robo truck growth is more than just above volume. It reflects the cross segment synergies within our ecosystem from robo taxi to robo truck. As James highlighted, the Mawan port demonstrates our ability to apply the technology and operational capabilities polished in robo taxi urban environments and robo truck long haul routes to a new vertical.

Our Intelligence Solution segment delivered the revenue of 10.8 million U.S. dollars this quarter, a 4% year over year increase with the growth rate moderating due to the delivery fluctuation from domain controllers. For the first half of 2026, the Intelligence Solutions revenue reached approximately 26.3 million U.S. dollars.

The same quarter last year total GAAP operating expenses were 72.1 million U.S. dollars this quarter and the non GAAP operating expenses were 63 million U.S. dollars representing a modest 9.6% increase. The expense increased is significantly lower than our revenue growth rate of 68.8%.

As Tiancheng mentioned, our leading Pony World Model 2.0 and AI powered closed loop R&D framework allows the same engineering team to handle far more work across different cities and the complex corner case analysis. The R&D efficiency is directly visible in our financial numbers. We are scaling globally without proportionally scaling our cost base.

We continue to see our operating loss margin narrowing and the operating leverage beginning to materialize as revenue scale. The loss from operation was 65.7 million U.S. dollars, a modest 7.3% increase. The operating margin narrowed dramatically from -285.6% in Q2 2025 to -181.5% this quarter and improvement of over 100 percentage points.

On a non GAAP basis, loss from operation was 56.7 million U.S. dollars increased by less than 5% year over year. Net loss narrowed significantly to 45.4 million U.S. dollars at 14.9% year over year decrease compared to Q2 2025. The net loss margin narrowed from -248.3% to -125.2%, an improvement of more than 100 percentage points.

From a broader perspective, our revenue growth rate significantly outpaced our non GAAP operating expense growth rate, clearly demonstrating economics of scale and operating leverage. Turning to our balance sheet, cash and cash equivalents, short term investments, restricted cash and long term wealth management instruments stored at 1.39 billion U.S. dollars as of June 30, 2026 compared to 1.44 billion U.S. dollars as of March 31st, 2026.

We continue to maintain a prudent cadence in cash management and maintain a robust financial position. Net cash used in operating activities was 44 million U.S. dollars this quarter compared to 25.4 million U.S. dollar in the same second quarter of 2025. The increase was due to normal working capital fluctuation, especially the settlement of account payable during the current quarter, coupled with strategic investment in inventory and prepaid to support our fleet expansion in the second-half this year.

Capital expenditures were 32.2 million U.S. dollars this quarter, bringing first half CapEx to 44.3 million U.S. dollars. This was mainly driven by the fleet and autonomous driving kit CapEx as we see robotaxi acceleration in both domestic and overseas market as well as increasing spending in data centers to support our greater scale deployment and continuous R&D.

As we scale up our fleet, we expect to maintain capital discipline supported by our partners Co investment under the joint deployment model framework. Our capital allocation strategy is designed to balance disciplined investment with scalable growth. Specifically, we invest in our core technology and owned fleet in key domestic markets, while partners contribute fleet capital and the local operating capability through the joint deployment model.

This allows us to expand our revenue generating footprint across China and the international markets without a proportional increase in capital intensity. Together with approximately 2000 vehicles produced operating footprint across the world, more than 1.5 million registered domestic users and 1.39 billion U.S. dollar cash reserve, we have the operating momentum, global opportunities and financial resources to execute our full year's target and support sustainable growth beyond the 2026.

Meanwhile, with our recent inclusion in Hong Kong listing stock Connect, we are excited to welcome onshore investors and maintain committed to transparent market engagement and the long term shareholder value creation. I will now turn the call over to the operator to begin our Q&A session. Thank you.

Operator

Thank you. We will now begin the question and answer session. To ask a question, you may press * then one on your telephone keypad. If you're using a speakerphone, please pick up your handset before pressing the keys. If at any time your question has been addressed and you would like to withdraw your question, please press * then two. If you ask questions in Chinese, please repeat them in English.

At this time. We will repeat. At this time, we will pause momentarily to assemble our roster. The first question today comes from Ming Shangli with Bank of America. Please go ahead.

Ming Shangli

Hi, James and Tiancheng and Leo, Congrats for the good results. So I only have one question. So given that Uber partners with several autonomous driving companies worldwide, what are the main reasons that met Uber choose a pony in its European rollout? Thank you.

Doctor James Peng

Thanks, Ming Shen. This is James and I'll take this one. As you can see that I'm actually quite pleased that we have signed commercial agreement with Uber to deepen our collaboration. I think the reasons Uber decided to work closely with us are actually quite straightforward. Uber always looks for autonomous driving partners whose technology is reliable at scale and also whose cost structure brings the attractive economics.

That's exactly the two reasons that we can offer on the table. We actually worked with Uber back in early 2025. At that time, our Gen. 7 robotaxis just started the deployment in China. And at that time, there were some doubts whether our autonomous driving capabilities can handle the European cities, especially the big ones where the infrastructure and the road condition are typically mixed with old and new.

But after a year now look at, I think the question has been answered with resounding real world evidences. We have already launched large scale robotaxi commercial operations in all tier one cities in China, The unit Economics turn positive in Guangzhou and Shenzhen. In addition, we also rolled out Europe's first commercial robotaxi service in Zagreb Croatia with Uber and Verne.

So all this evidence shows that our robotaxis can cover the most complex, highest demanding scenarios and and also what we have found out is the more places a vehicle can operate, the higher utilization becomes. So on the cost side, we also can offer is even more compelling right combining with the hardware and also the operational costs, our total cost per mile is the most competitive in the industry.

I think another important reason is that the culture alignment has also been a hallmark of our collaboration between Pony and Uber. Both sides are impressed by why another's professionalism and the dedication, the the mutual appreciation and the mutual commitment really lead to right now what we have seen the expanded collaboration for both of our companies.

The strategy is to begin with the most socially and economically meaningful markets and then we'll even extend our mobility services to additional geographies. So the what we announced about the 2000 vehicles is under the current contract with these contracts, we become Uber's largest autonomous driving partner in Europe.

Going forward, as the performance and also the economics continue to validate at scale, we'll see substantial room to expand the fleet size even further. So back to the operator.

Operator

The next question comes from Tim Hsiao with Morgan Stanley. Please go ahead.

Tim Hsiao

Thank you, management and congratulations on the strong quarterly results. Could you please elaborate on your strategy going forward for the joint deployment model? And also can you share more color on how the commercialization model works and operate under asset light model?

Doctor James Peng

Thanks for the question. This is James again. Probably let me begin with a high level and I'll probably regarding the details I'll hand over to Leo. So, so the joint deploying model will actually accelerate our fleet expansion with high capital efficiency both domestically and internationally. You can think of this as in this model we are building a win win model across the value chain.

The success of our Gen. 7 robotaxi operations across the tier one cities, it's really a showcase. It proves that our superior safety record and operational efficiency And then ultimately turn positive UE margins by delivering this top tier driving capabilities and user experience and at the same time at very low hardware and operational costs, we can achieve high margins than our peers.

Therefore partners in our ecosystems, whether it's a mobility platform or a fleet operator, they can share the most economic value per deployed vehicle. So on the HALA we can think of the the joint deploy model they they gave partners are naturally incentivized to commit a large portion of their fleet shares to Pony because in this model they can maximize their total value generated together with us. Regarding the details of this business model, I'll now hand over to Leo.

Doctor Leo Wang

Yeah, Thanks James. And this is Leo. Yes, Tim, you you mentioned is correct. This is a asset light model for Pony to expand our fleet and in most cases there are three parties and each plays a different role. For Pony, we supply our Gen. 7 robotaxi with our virtual driver capability, that is AI Driver, a mobility platform that can introduce user demands and a operating company who can deal with fleet management and maintenance.

We of course acknowledge in different markets the consumer can have the choice on mobility platforms and there are existing operating companies. So we don't want to disrupt these ecosystem in these markets, but instead our joint deployment business model is trying to bring values and form a win win alliance.

For example, we leverage Uber and Bolt as mobility platforms to attract demands and we are also partner with Verne in Croatia and ComfortDelGro in Singapore as local fleet operator. So from a financial perspective, this model could generate revenue sharing based revenue or technology licensing fee for Pony.

And this is not only broaden our revenue base but also introduce higher margin recurring income across the entire robotaxi operating life cycle. And as we expand our footprint into a higher premium international markets, for example in Europe, in Middle East and in other parts of Asia, we definitely think that this could lift our long term financial outlook.

And just to be clear, these 4000 vehicle commitment from Uber and other partners will serve as a multi year growth catalyst for 2026. And. Yeah. I will now turn the call back to the operator.

Operator

The next question comes from Paul Gong with UBS. Please go ahead.

Paul Gong

Hi, thanks for taking my question. I have one question regarding on the Pony World 2.0. I think Tiancheng has mentioned about its self evolution and closed loop engineering. Can you please provide more color on what makes self evolution different in automatizing and how does it improve your R&D efficiency? And if we think in the future if someone open source the world model, would your moats be affected? Thank you.

Doctor Tiancheng Luo

Thank you. This is Tiancheng. I will take this one to start. I will say auto driving is a physical AI. So training the onboard model or improving the world model are both built on real world feedback. A general purpose to open source world model is basically just a 3D video generator. It can generate the data, but that's nowhere near enough to train our autonomous driving system.

Then we use world model to train the onboard model through reinforcement learning. To do this right, it is not just simulating what people do, it's about how often they do this. Take up pedestrians suddenly jaywalking as example. The chance isn't 99%, it's not 1% either. So precision means matching the exact real world probability.

That level of statistical accuracy is what we mean by precision of the world model. So the probability distribution of traffic participants varies from city to city. Although our model generalized capabilities strong enough to handle extreme scenarios worldwide, we still need to fine tune it for local driving styles.

So for example, in both China and Croatia, there are drivers who change lanes without checking one tracking behind them. It happens with different probability in different places. So that's where pony world 2.0 comes in. It is the self evolving system that continues in improving the world model precision.

In the past our workflow was human lead. So when we enter new city we calculate from that region that engineers will determine which scenario the current world model lacks precision. Now AI drives the whole process. Human are still involved, but mostly for verification validation.

So as a result, we significantly reduced engineering resources to enter a new city. In other word, without adding R&D resources, we can either enter many new markets at the same time, quickly achieving safe and smooth L4 autonomous driving. This ability to scale is a very large moat so and I do not think it will be affected by any open source generative world model. With this back to the operator,

Operator

The next question comes from Jeff Chung with Citi. Please go ahead.

Jeff Chung

Hi, this is Jeff. Thank you for the opportunity. And my question is about the domestic market and how should we think about Pony's new outlook for the domestic market having into the second-half of the year? Thank you.

Doctor James Peng

Thanks, Jeff. Hey, this is James. I'll take this call. As you can see that China is our home base. I believe that domestic fleet expansion remains a significant part of our vehicle roll out. China itself represents a massive mobility market with over 10 million taxis and the ride hailing vehicles.

So it's a highly but, but the the reality is that also the mobility demand demands highly concentrated in tier one cities and the Tier 2 cities. So as a result, our strategy remains the same. We'll start our focus from the highest valued markets and then expanding into other cities and regions.

The tier one cities alone account for a significant share of the national ride hailing demand. These cities are also the ones that offer the most mature regulatory framework to support our driverless driving today, our scale and the commercial model in this tier one cities remains industry leading.

In our larger operational hubs such as the Guangzhou and Shenzhen, we are already seeing strong growth momentum. Expanding the fleet size in this market shortens users wait time and boosts user retention and then as a result directly translates into higher daily revenue per vehicle even as we scale up our fleet size.

So this virtuous cycle not only drives paid order growth and margins, but also reinforce our regulatory trust and also the brand recognition. At the same time, scaling allows us to amortize the operational costs driving down our daily per vehicle costs. So what we have seen is really a continuous improvement of our UE margins.

Therefore, we will proceed with deploying, deploying more and more fleets in the tier one cities to widen our competitive moats. Meanwhile, of course, second tier and even third tier markets are strategically vital. This year, we plan to enter key cities such as Changsha, Hangzhou and many of the additional Bay Greater Bay Area cities and potentially some other cities and regions.

This will establish the foundation for these markets, essentially become a new growth engine for us to go forward with this. Back to the operator.

Operator

The next question comes from Charlie Lee with Jefferies. Please go ahead.

Charlie Lee

Thanks for taking my question. This is Charlie from Jefferies. My question is on robotaxi operations. You've mentioned that operational efficiency is crucial for running the fleet at scale. Could you maybe give us more color on how is that actually being achieved? For example, on the remote assistance side, vehicle utilization or charging and maintenance perspective? And then how those efficiency gains are helping you accelerate deployment both in terms of like expanding existing cities and entering the new ones? Thank you.

Doctor Tiancheng Luo

This is Tiancheng. Yes, thanks for the question. So regarding the operational efficiency, I will start saying based on our experience across the tier one cities, So we now have developed a deeper understanding of the complexity of operating the fully driverless fleet. This is a completely different game for managing traditional taxis.

So at the end of the day efficiency comes down to one thing, the fleet to staff ratio. So with traditional taxis it's always one to one 100 cars need 100 drivers to handle everything from cleaning, charging to daily maintenance. So for us, so it's not just by about managing people better, but even critically on whether technology can minimize need to human involvement.

For example, when our robotaxi return to a depot, they require 0 human assistance, autonomous navigating, locating available chargers and executing self parking even in very tight space. So because of that, so we need three people for every 100 robotaxis to keep daily operation running smoothly.

That's true whether we run them by ourself or work with partners. So this is directly translated into significantly lower operating costs per vehicle and advanced unique economics. Therefore, without insulating management overhead and the cost, we can still expand into new cities and don't deploy more vehicles rapidly.

We have developed this know how into standardized operating procedures and automation tools. That's why more and more partners that join us to adopt our joint deployment model making Pony robotaxi the most efficient and profitable choice available. With this back to the operator.

Operator

The next question comes from Kai Xiao with CICC. Please go ahead.

Kai Xiao

Thank you management and Congrats. Congratulations for the quarter. Could you give us updates? On your new business initiatives, specifically the progress with your L4 light truck business. Thank you.

Doctor James Peng

Thanks, Kai. This is James and I'll take this one. The new business initiatives, especially the L4 light truck, I think fits very well with our vision and ambition, which is autonomous mobility everywhere. The L4 light truck has a great synergy among our current product offerings. Think about it can leverage the robotaxis driving capabilities and the cost efficient hardware.

And at the same time, the light truck also shares the same customer base with our robotruck. The light truck almost shares 100% of our robotaxis technology and operational infrastructure. So, so essentially the development and operation can slash our costs. The light truck extends the logistic portfolio from long haul into urban delivery. It's essentially unlocks a new time.

In China alone, the active light truck fleet on the road exceeds 8 million vehicles. Also look at the current already on on the ground, the low speed Robovan. Compared with that, our light truck offers three to four times the cargo capacity and also the speed is 2/2 times faster.

As a result, it can open up a heavier loaded commercial applications across the full urban supply chain. If you think about typical usage, those from distribution hubs to the shopping malls to the supermarkets and also the convenience stores. As you recall that we actually unveiled the L4 light truck in the Beijing Auto Show.

Since then it has been four months and in that four months, we have already built a strong commercial ecosystem. The vehicle itself are jointly developed with CATL. The vehicle is the world's first automotive grade fully redundant light truck purposely built for L4 autonomous driving.

Currently, we also have secured partnerships with SF Express and the China Post Technology 2 leading logistic operators in China. With the orders and the deployment schedules already in place, this partnership can create a strong pipeline for the autonomous urban delivery.

Looking at the remaining of this year, I believe that the collaboration pipelines with even more OEMs and the fleet operators will still in the pipeline to drive scaling up. We'll also integrate with urban logistics network platforms to capture even further demand. So I'm actually very excited about this new initiative. With this back to the operator,

Operator

The next question comes from Annie with Ever Bright Securities. Please go ahead.

Annie

Hi dear management, thank you so much for taking my question. We know that Waymo's management recently said that the demo is only 1% of the work. Could Pony's management share your views on this comment please? Thank you.

Doctor Tiancheng Luo

Thank you, this is Tiancheng. I will take this one. Firstly I would say this is an interesting framing and I think it captures something real. So building an impressive demo and scaling are two entirely different games. Autonomous driving is really a probability problem if you get into one accident every 1000 kilometers.

Sure, I can do a demo because the demo only covers a few kilometers, but at a scale this accident rate is a deal breaker. A typical ride sharing vehicle drives about 300 kilometers a day. So if you have a fleet of 100 cars in one city, so that is 10s of 1000 kilometers every day, the fleet, the fleet would see 10 accidents every single day, then no regulators will tolerate this and will the public definitely won't.

But because auto driving is a probability problem, risk evolves differently at scale. Moving safety takes time and mileage and you cannot just shortcut by dumping some cars on the street overnight pretty side and the time are not interchangeable. This is also why regulators everywhere take exactly same approach. They go step by step. A small fleet first proved of safety at that scale, then to the next level.

So technically going from a demo to full scaling takes multiple 10X jumps in performance, and every jump is harder than the last. It's not just about fixing the remaining 10% of problems, but also systematically resolving 90% of the issues without creating new ones. For example, hard braking to avoid a collision may solve a problem, but it may create more rear-ended collisions.

And if the underlying technical approach is wrong, City has a hard ceiling. Therefore, proving safety to regulate is just the only one of the bar from the technical standpoint. New players have to prove they can iterate very fast because the leaders are ready miles ahead by several over the magnitude of safety.

So Long story short, if all you have today is a demo, you still need to prove that you can achieve multiple 10X performance jumps. And on top of that, you need time to do the trust with regulators before you can scale. So for Pony, we've already checked both of these boxes. That's why our focus for today is on expanding into more cities and deploying larger fleets. So with that, with that, back to the operator.

Operator

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

George Xiao

Thank you once again for joining us today. If you have any further questions, please feel free to contact our IR team. We look forward to speaking with you in the next quarter. This concludes today's conference call. You may now disconnect your line. Thank you.

Details at Pony AI IR

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