小马智行 (PONY) 2026财年第二季度业绩电话会：Robotaxi收入暴增691%

小马智行（Pony AI Inc.，PONY）公布2026年第二季度Robotaxi商业化进程迅速，总营收同比增长69%，Robotaxi业务营收创下1210万美元的历史新高。管理层还强调车队部署提速、获得海外合作伙伴承诺以及经营杠杆改善，同时亏损与现金消耗依然显著。

核心要点

• 总营收同比增长69%至3620万美元，主要得益于Robotaxi营收大增691%以及Robotruck营收增长40%。
• Robotaxi营收达到创纪录的1210万美元。在车队拓展至更高价值城区及联合部署模式支撑下，收费服务营收增长849%。
• 小马智行（Pony.ai）的Robotaxi车队规模达到2,000辆。管理层表示，公司仍按计划推进，预计到2026年底车队将拓展至3,500辆并在20座城市开展运营。
• 公司已获得超过4,000辆海外车辆的合作承诺，其中包括与Uber合作在五个欧洲城市部署的2,000多辆Robotaxi。
• 净亏损同比收窄14.9%至4540万美元。净亏损率从负248.3%改善至负125.2%。
• 截至2026年6月30日，现金及相关金融资产总计13.9亿美元，低于3月31日的14.4亿美元。单季度经营性现金流出为4400万美元，资本支出达3220万美元。

关键财务数据

业务与运营表现

Robotaxi业务扩张

小马智行的Robotaxi车队已扩大至2,000辆，三款第七代车型投入日常运营。在中国的注册用户突破150万。

在广州，自2026年初以来，公司服务覆盖面积新增超300平方公里，并将运营延伸至市中心。在深圳，其网络连接了主要交通枢纽，并已覆盖早晚高峰、节假日及暴雨天气等场景。

管理层表示，广州和深圳的单车盈利模式已实现转正。据公司介绍，更密集的车队分布缩短了乘客等待时间，提升了用户留存率，并增加了单车日均收入。

轻资产国际化部署

小马智行的联合部署模式分工明确：由小马智行、出行平台及当地车队运营商共同承担责任。小马智行提供第七代Robotaxi及其虚拟司机技术，合作伙伴则提供客流需求、车队资金、维保服务及本地运营能力。

该模式可产生前期车辆交付收入、分成收入以及技术授权费。管理层预计，随着部署车队的规模扩大，经常性收入部分的利润率将更高。

公司已获得超过4,000辆海外车辆的合作承诺。其中包括通过与Uber扩大的合作协议在五个欧洲城市部署的2,000多辆Robotaxi。管理层将这些承诺视为多年期的增长催化剂，而非单一季度的部署目标。

小马智行还提及了在卢森堡和新加坡持续推行的业务活动，以及在克罗地亚萨格勒布启动的商业化Robotaxi部署。

Robotruck与L4级轻卡

在物流运输收入的支撑下，Robotruck营收增长40%至1330万美元。第四代Robotruck进入量产和商业化运营阶段，包括在深圳妈湾港与有人驾驶卡车共同开展的全无人化部署。

针对L4级轻卡，小马智行表示已与顺丰速运和中邮科技建立合作伙伴关系。公司瞄准城市物流应用场景，并计划与主机厂、车队运营商及物流平台展开更多合作。

技术与运营效率

PonyWorld 2.0利用人工智能识别本地驾驶难题、生成针对性解决方案并验证更新后的模型。管理层表示，这减少了进入新城市所需的工程师数量，并支持在交通习惯不同的市场进行同步扩张。

公司还通过自动泊车、充电导航和标准化车队管理工具来减少人工干预。管理层指出，日常运营中每100辆Robotaxi仅需约3名地面人员提供支持，从而降低了单车运营成本。

管理层业绩指引

• 管理层预计2026全年Robotaxi营收将超过上年水平的3.5倍，展现出比最初预期更高的信心。
• 公司表示，依然按计划在2026年底前将Robotaxi车队规模从2,000辆扩大至3,500辆。
• 在PonyWorld 2.0和联合部署模式的支撑下，管理层计划在年底前在20座城市开展运营。
• 预计Robotruck在2026年下半年的增长势头将得以延续并可能进一步增强。
• 小马智行计划继续在主要中国市场投资核心自动驾驶技术及自有车队，同时利用合作伙伴的资本开展更广泛的国内和国际扩张。

风险与关注要点

• 由于应付账款结算以及下半年车队扩张前的库存投资，经营性现金流出增加至4400万美元。
• 资本支出随Robotaxi车队、自动驾驶设备和数据中心的投入增加而上升。因此，扩张节奏在一定程度上仍取决于合作伙伴的共同投资。
• 智能解决方案营收增速放缓，主要是受域控制器交付波动影响。
• 管理层强调，随着里程和车队规模增加，维持自动驾驶安全性的难度加大。获得监管批准需要渐进式部署、经过验证的安全表现以及持续的公众信任。
• 不同城市的驾驶习惯和交通参与者概率存在差异，尽管管理层认为小马智行的泛化能力强大，但仍需要对本地模型进行微调。

分析师问答环节要点

与Uber的合作：管理层表示，Uber选择小马智行是看中其大规模技术可靠性以及具有竞争力的硬件和运营成本。小马智行声明，目前的协议使其成为Uber在欧洲最大的自动驾驶合作伙伴；若性能和经济效益持续得到验证，未来车队规模有望进一步扩大。

联合部署的经济模式：轻资产模式通常涉及小马智行、出行平台以及本地车队运营商。小马智行预计将从车辆交付、技术授权和经常性营收分成中获取收入，而合作伙伴则资助车队并提供本地运营基础设施。

国内市场扩张：管理层将继续提高中国一线城市的车队密度，同时进入部分二线城市及粤港澳大湾区市场。公司预计规模效应将提升车辆利用率，并在更广范围的车队中摊薄运营成本。

开源世界模型：管理层指出，通用生成式世界模型无法取代L4级自动驾驶所需的真实世界概率数据、强化学习过程和验证框架。因此，预计开源模型不会实质性削弱PonyWorld 2.0的竞争地位。

规模化与演示对比：管理层强调，有限的自动驾驶技术演示与运营大型商业车队存在本质区别。管理层将实现数个数量级的安全性提升以及建立监管信任视为规模化扩展的关键门槛。

业绩电话会议完整文字记录

---

完整财报电话会议逐字稿

管理层陈述

Operator

Ladies and gentlemen, thank you for standing by, and welcome to Pony AI Inc.'s Second Quarter 2026 Earnings Conference Call. [Operator Instructions] 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.pony.ai. I will now turn the call over to your host, George Shao, Head of Capital Markets and Investor Relations at Pony.ai. Please go ahead, George.

George Shao

Thank you, operator, and hello, everyone. We appreciate you joining us today for Pony AI's 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 Dr. James Peng, Chairman of the Board; and Chief Executive Officer; Dr. Tiancheng Lou, 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 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 over to our Chairman and CEO, Dr. James Peng. Please go ahead.

Jun Peng

Thank you, George. Hello, everyone. Thank you for joining our earnings call today. We delivered another fantastic quarter, highlighted by multifold expansion across the board.

First, strong top line growth. Total revenue surged by 69% year-over-year, driven by a close to 8x [ growth ] in Robotaxi revenue and over 9x surge in fair [ charting ] revenue. Second, rapid fleet scaling. Our Robotaxi fleet expanded to 2,000 vehicles, putting us on track to deliver 3,500 vehicles by year-end. Third, expanded deployment. Domestically, we reinforced our leadership in Tier 1 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 4,000 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 three Gen 7 Robotaxi vehicle models in our daily services, including the GAC INV, the BAIC [ AFX ] alpha T5 and the Toyota [ BizFlex ].

We are continuously improving user experience, which is the key driver for our organic user growth as our total registered users has 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 spend across [ Haijou ], [ Pianko ], [ Wanfu ] and [ Panu ] districts, covering a population of over $7 million. As a result, our driver fleet is positioned to capture highly concentrated urban mobility demand.

Shenzhen known as China 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 rain storms.

Despite these demanding conditions, we effectively met high-frequency commuting demands. In addition, by seamlessly integrating three major transit hubs, including [indiscernible] International Airport, Shenzhen Bayport and Circle 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 alpha 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 these 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 4,000 vehicle commitments led by over 2,000 Robotaxis across five 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 [ Voge ] and [ Stellantis ] keeps moving forward. And in Singapore, our service is now officially live for the general public [indiscernible] their growth, ride-hailing app called [ Zig ].

With international demands are a direct endorsement of our Gen 7 global taxi operations in China's Tier 1 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 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 [ DDM ] model's financial viability.

Second, the joint deployment model is an asset-light one. where our partners found the fleet. This fundamentally enables faster scaling, lower unit costs and superior capital efficiency for our fleet expansion.

Third, with fast scaling, [ DDM ] essentially unlocks massive commercial value for years to come. For example, we recently expanded our partnership with Uber to target 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 Robotruck have entered mass production and already begun commercial operations. Working with China Merchants Port, we launched our commercial deployment of Robotruck at Shenzhen [ Mawan ] port, where our fully driverless Robotruck operate together with other human-driven trucks. This success highlights our unique cross-segment synergies. We have leveraged our rich operational experience from urban mobile taxes and long-haul Robotruck, to enable our trucks to seamlessly navigate traffic interactions at the port.

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 1 cities, we will continue to deploy more vehicles to our fleet to widen our competitive moat and advance our killing edge.

And at the same time, we are on track to enter multiple domestic new markets. Internationally, the point deployment model will contribute to top line growth with great capital efficiency. These two momentum gives us greater confidence in beating our original Robotaxi revenue outlook, which is exceeding 3.5x 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 will hand it over to our CTO, Tiancheng, to go over the technology progress. Tiancheng, please go ahead.

Tiancheng Lou

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 [indiscernible] across 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 1 cities such as Guangzhou and Shenzhen are clear examples and other urban cores and the major transit hubs, [indiscernible] residential neighborhood [ advance ] and roadside parking are common. Overall model and virtual drivers prove to be more agile and precisely in navigating this extreme conditions, ultimately 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 very significant on China, Europe, the Middle East and Asia. Despite this fundamental region differences, our robust generalization enables rapid deployment.

Over proven technical track record, especially in Tier 1 cities of China and the [indiscernible] is exactly why top-tier partners choosing to scale with us through our drone demand model.

Beyond the driving capability, another key engine behind our expansion and efficiency. Let me now elaborate on how our unique technical and operational capability to deliver these efficient benefits. As I shared in previous quarters, the key to enabling over Robotaxi to seamless navigate diverse urban environment, lighting over world model precision. This is what bridges gap of so [ core ] seem to real in physical area.

In our top driving, closes the gap comes down to modern the probability distribution of different behaviors among traffic participants. For example, the probability of the pedestrian standing on the low side, suddenly jaywalking varies from city to city. High-precision driver model accurately captures these dynamics, enabling the virtual driver to handle such scenarios with confidence.

Our current upgraded PonyWorld 2.0 brings this precision alignment into Uber engineering. The system automatically isolates deeply hidden issues generate targeted solutions and validate 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. And as the cause of these issues upgrade the word model and retain the onboard models and then deploy and validate the new model on the road. However, with PonyWorld 2.0, over system leverages AI to resolve this local changes automatically, this turns cities intention from efforts that using take a dozen of engineers into acumen of automatic process than just a few people can run.

So for example, when we went to [indiscernible] we noticed local drivers almost never slow down when they hold it right away, even near [indiscernible]. PonyWorld [indiscernible] let [indiscernible] is different automatically, and we quickly trained a new version of virtual driver that fits local hybrid perfectly with very few engineers involved.

As a result, we cannot launch in mutable cities with completely distinct driving environment all at what this scalability ensure we efficiently achieve our target of 20 cities by the end of this year. This gives us the unique efficiency advantage can offer [ print ] 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 park our cars. Our Robotaxi can share a normal parking lot with human drivers driving 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 our unit cost. The vehicle to staff ratio for our ground supporters and remote assistant team has improved significantly.

More importantly, it also puts the willingness of industry partners to adopt our joint demand model. As James mentioned, multiple partners such as Uber are clear examples. In short, our [ tax-driven ] efficiency gives us a unique operational leverage as we scale across new markets. This not only reinforce our competitive moat, but also positions over 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, [ Dr. Leo Wang ] for a closer look at our financial results. Leo, please go ahead.

Haojun 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 USD 36.2 million, representing a remarkable 69% increase from USD 21.5 million in the same quarter last year. Bridging down the strong top line growth by business segment. Most notably, our Robotaxi revenue are growing 691% and the Robotruck 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 USD 12.1 million, growing 691% a further acceleration from the 395% growth compared to the first quarter. Our fair charging revenue delivered an exceptional growth rate of 849%, 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 value. Second, our joint deployment model gained 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 improved our high-quality service in a 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 established a solid foundation for us to having high margin recurring revenue sharing income going forward as our fleet operation scale.

What is particularly encouraging is that this acceleration is broad-based, not concentrated in a single market. In China in this quarter, we continue to strengthen our leading position in Tier 1 cities with fast-growing scale and a strong user base.

Overseas, we are building an alliance that accelerates our global footprint. For example, we have secured over 4,000 initial vehicle deployment commitments with Uber and other overseas partners. Our continuous expansion in China and overseas were translating into a rapidly increasing base of recurring Robotaxi revenues.

Turning into Robotruck, the revenue grew 40% year-over-year to USD 13.3 million this quarter. This growth was driven by increased logistics transportation revenues. Robotruck growth is more than just above volume. It reflects the cross-segment synergies within our ecosystem from Robotaxi to Robotruck. As James highlighted, the [ Mawan ] port demonstrates our ability to apply the technology and operational capabilities polished in Robotaxi urban environments and Robotruck long-haul routes to a new vertical.

Our Intelligent Solutions segment delivered revenue of USD 10.8 million 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 USD 26.3 million. [Audio Gap] same quarter last year.

Total GAAP operating expenses were USD 782.1 million this quarter, and the non-GAAP operating expenses were USD 63 million, representing a modest 9.6% increase. The expense increase is significantly lower than our revenue growth rate of 68.8%. As Tiancheng mentioned, our leading PonyWorld 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 [ Kona ] case analysis. The R&D efficiency is directly visible in our financial numbers. We are scaling globally without proportionately scaling our cost base.

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

On a non-GAAP basis, loss from operations was USD 56. 7 million Increased by less than 5% year-over-year. Net loss narrowed significantly to USD 45.4 million a 14.9% year-over-year decrease compared to Q2 2025. The net loss margin narrowed from negative 248.3% to negative 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 stood at USD 1.39 billion, as of June 30, 2026 compared to USD 1.44 billion as of March 31, 2026. We continue to maintain a prudent cadence in cash management and maintain a robust financial position.

Net cash used in operating activities was USD 44 million this quarter compared to USD 25.4 million in the second quarter of 2025. The increase was due to normal working capital fluctuation, especially the settlement of accounts payable during the current quarter, coupled with strategic investment in inventory and prepared to support our fleet expansion in the second half of this year.

Capital expenditures were USD 32.2 million this quarter, bringing first half CapEx to USD 44.3 million. This was mainly driven by the fleet and autonomous driving CapEx as we see Robotaxi acceleration in both domestic and overseas markets. 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 partner's co-investment under the joint deployment model framework. Our capital allocation strategy is designed to balance disciplined investment with scalable growth. Specifically, we invested in our core technology and the 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 international markets without a proportional increase in capital intensity.

Together with approximately 2,000 vehicles produced operating footprint across the world, more than 1.5 million registered domestic users and USD 1.39 billion cash reserve. We have the operating momentum, global opportunities and financial resources to execute our full year target and support sustainable growth beyond 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 long-term shareholder value creation. I will now turn the call over to the operator to begin our Q&A session. Thank you.

Operator

[Operator Instructions] The first question today comes from Ming-Hsun Lee with Bank of America.

分析师问答

Ming-Hsun Lee

I only have one question. So given that Uber partners with several autonomous driving companies worldwide, what are the main reasons that made choose Pony in its European rollout.

Jun Peng

This is James, and I'll take this one. As you can see that I'm actually quite pleased that we have signed a commercial agreement with Uber to deepen our collaboration. I think the reasons Uber decided to work closely with us 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 bouts whether our autonomous driving capabilities can handle the European cities, especially the big ones where the infrastructure and 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 evidence. We have already launched large-scale Robotaxi commercial operations in all tier 1 cities in China. The unit economics turned positive in Guangzhou and Shenzhen.

In addition, we also rolled out Europe's first commercial Robotaxi service in [ Zagreb ], Croatia, with Uber and [ Vern ]. So all this evidence shows that our Robotaxis can cover the most complex highest demanding scenarios.

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 one another's professionalism and dedication. 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 what we announced about the 2000 [indiscernible] because it's 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.

Operator

The next question comes from Tim Hsiao with Morgan Stanley.

Tim Hsiao

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?

Jun Peng

This is James again. Probably let me begin with high level, and I'll probably -- regarding the details, I'll hand over to [ Leo ]. So the joint deployment 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 1 cities, it's really a showcase. It proves that our superior safety record and operational efficiency and then ultimately 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 ecosystem, whether it's a mobility platform or a fleet operator they can share the most economic value per deployed vehicle. So on the highlight, we can think of the joint deployment model, 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.

Haojun Wang

Yes. Thanks, James, and this is Leo. Yes, Tim, you mentioned is correct. This is an 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 the AI driver, a mobility platform that can introduce user demand and an 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 this 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 [ Voge ] mobility platforms to attract demand. And we are also partnered with [ Vern ] in Croatia and [indiscernible] [ Dago ] in Singapore as local fleet operator.

So from a financial perspective, this model could generate sharing-based revenue or technology licensing fee for Pony. And this has 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 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 4,000 vehicle commitment from Uber and other partners will serve as a multiyear growth catalyst. For 2026 and beyond.

Operator

The next question comes from Paul Gong with UBS.

Paul Gong

I have one question regarding on the PonyWorld 2.0. I think Tiancheng has mentioned about its self-evolution and [indiscernible]. Can you please provide more color on what makes [indiscernible] evolution difference in autonomizing? And how does it improve your R&D efficiency? And if we think in the future, if someone open source or world model would your mods be affected? Thank you.

Tiancheng Lou

This is Tiancheng. I will take this one. To start, I will say auto-driving is a physical AI to training the onboard model or improving the word model are both filed on real-world feedback. Our general purpose to open source [ word ] model is basically as a 3D video generator, it can generate data, but that's nowhere near enough to train our autonomous driving system.

Then we use [ word ] 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 it. Take up pedestrian sudden jaywalking as an example. The chance isn't 99%. That'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 [ word ] model.

So the probability distribution of traffic pedestrians varies from city to city. Although our model generalized capability strong enough to handle items scenarios worldwide, we still need to fine tune it for local driving styles.

So for example, in both China and Croatia, they are drivers who change lanes without checking behind it. That happens with different probability in different places. So that's where PonyWorld 2.0 coming. It is a self evolving system that continuously improving the world model position. In the past, our workflow with human lead. So when we enter a new city as data from that region that engineers were determined which is a scenario of the [indiscernible] model like expedition.

Now AI drives the whole process, who may still involve mostly for verification and validation. So as a result, we significantly reduced engineering resources to enter a new city. In other words, 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 in a very large mode -- so -- and I do not think it will be affected by any open source generative work model.

Operator

The next question comes from Jeff Chung with Citi.

Ming Chung

This is Jeff. 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.

Jun Peng

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 [ lot ]. China itself represents a massive mobility market with over 10 million taxes and ride-hailing vehicles. So it's a highly -- but the reality is that also the mobility demand is highly concentrated in Tier 1 cities and the Tier 2 cities.

So as a result, our strategy remains the same. We'll start our focus from the highest value of the market and then expanding into other cities and regions. The Tier 1 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 [indiscernible] driving.

Today, our scale and commercial model in these Tier 1 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 these markets shortens users win time and boost yielder 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 our 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 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 more and more fleets in the Tier 1 cities to widen our competitive moats.

Meanwhile, of course, second tier and even third tier markets on strategically vital. This year, we plan to enter key cities such as [ Hansa ], [ Hangdou ] and many of the additional 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.

Operator

The next question comes from Xiaoyi Lei with Jefferies.

Xiaoyi Lei

This is Xiaoyi from Jefferies. A 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 new ones?

Tiancheng Lou

This is Tiancheng. So regarding the operational efficiency, I will start saying based on our experience across the Tier 1 cities. So we now have developed a deep understanding of the complexity for operating the full driverless fleet. This is a completely different game for managing traditional taxes.

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

For example, all over Robotaxi [indiscernible] a depot, they require to human assistant autonomous navigating, locating available chargers and using self-parking even in other type space. So because of that, so we need three people for every 100 robots to keep daily operations running smoothly. That's true whether we run them by ourselves, our working partners. So this directly translated into significantly lower operating cost per vehicle and advanced [ uniqueconomics ]. Therefore, without inflating management overhead and cost we can still expand into new cities that are deployed more vehicle [indiscernible].

We have developed this know-how into standardized operating procedures and automation tools. That's why more and more partners join us to adopt overdrawn depot model, making Pony Robotaxi the most efficient and profitable for [indiscernible] available.

Operator

The next question comes from Kai Xiao with CICC.

Kai Xiao

Could you give us an update on your new business initiatives, specifically the progress with your L4 light truck business.

Jun Peng

Kai. This is James, and I'll take this one. The new business initiatives, especially the L4 light truck, I think it 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 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 essentially, the development and operation can slash our costs.

The light truck extends the logistics portfolio from long haul into urban delivery. It essentially unlocks a new TAM. In China alone, the active light truck fleet on the road exceeds 8 million vehicles.

Also look at the current already on the ground, the low-speed ruble [indiscernible], compared with that, our light truck offers three to four the cargo capacity and also the speed is 2x faster. As a result, it can open up 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 4 months. And in that 4 months, we have already built a strong commercial ecosystem. The vehicle sales are jointly developed with CATL. The vehicle is the word 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, two leading logistics 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 will also integrate with urban logistics network platforms to capture even further demand. So I'm actually very excited about this new initiative.

Operator

The next question comes from Anne Nee with Everbright Securities.

Unknown Analyst

We know that Waymo's management recently said that [indiscernible] only 1% of the word. Can Pony management share your views on this comment, please. Thank you.

Tiancheng Lou

This is Tiancheng. I will take this one. First, this is an interesting framing, and I think it captures something real. To building an impressive demo are scaling are two entirely different games. [indiscernible] is really a probability problem. If you get into one asset, every 1,000 kilometers, sure, I can do a demo because demo only covers a few kilometers.

But at scale, this accident rate is a deal breaker. Our typical ridesharing vehicle drives about 300 kilometers a day. So if you have a fleet of 100 cars in 1 city. So that is 10,000 kilometers every day. The fleet will see 10 accidents every single day, then no regulators will [indiscernible] it and will the public definitely won't. So because auto driving is a probability problem. Risk evolves differently at scale.

Moving through city takes time and mileage and you cannot just shortcut by dunking solo cards on the straight overnight. [indiscernible] and the time are not in intangible. This is also why regulators everywhere takes exactly same approach. They go step by step, a small fleet first proof of safety and that [indiscernible] then to the next level. So [indiscernible] technically going from a demo to full scaling takes multiple 10x jump in performance. And we jumped it harder than the last. It's not just about fixing the remaining 10% of problems, but also systematic resolving 90% of the issues without creating new ones.

For example, hard braking to avoid a collision makes of a problem, but it may create more rear-ended collisions. And if the underlying technical approach is wrong, safety has a hard [indiscernible]. Therefore, proving safety to regulators just the only want bar from a technical standpoint, new players have to prove we can it very fast because the leaders are already miles ahead by several order magnitude of safety. So long tory 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 build the trust with regulators before you can scale.

So for Pony, we have already checked both of these boxes. That's why we're focused for today is on expanding into more cities and deploying larger fleets.

Operator

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

George Shao

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.

Operator

This concludes today's conference call. You may now disconnect your lines. Thank you.