Pony AI（PONY）2026年第2四半期決算説明会：ロボタクシー売上高が691%急増

Pony AI Inc. (PONY) は2026年第2四半期にRobotaxiの商用化が急速に進展したと発表しました。総売上高は前年同期比69%増となり、Robotaxiの売上高は過去最高の1,210万米ドルに達しました。経営陣はまた、フリート導入の加速、海外パートナーとの提携コミットメント、営業レバレッジの改善を強調したものの、赤字とキャッシュ消費は引き続き大幅な水準にとどまりました。

要点

• 総売上高は、Robotaxi売上高の691%増およびRobotruck売上高の40%増が牽引し、前年同期比69%増の3,620万米ドルとなりました。
• Robotaxiの売上高は過去最高の1,210万米ドルに達しました。有料乗車による売上高は、高価値の都市部へのフリート拡大と共同導入モデルに支えられ、849%増加しました。
• Pony.aiのRobotaxiフリートは2,000台に達しました。経営陣によると、2026年末までに3,500台への拡大および20都市での運用開始に向けて順調に進展しているとのことです。
• 同社は海外で4,000台以上の車両供給に関するコミットメントを獲得しており、これにはUberとの提携により欧州5都市で展開する2,000台以上のRobotaxiが含まれます。
• 純損失は前年同期比14.9%縮小の4,540万米ドルとなりました。純損失率は前年同期のマイナス248.3%からマイナス125.2%に改善しました。
• 2026年6月30日時点の現金および関連金融資産の合計は13億9,000万米ドルとなり、3月31日時点の14億4,000万米ドルから減少しました。四半期の営業キャッシュアウトフローは4,400万米ドル、設備投資額は3,220万米ドルに達しました。

主要財務データ

事業およびオペレーションの実績

Robotaxiの拡張

Pony.aiのRobotaxiフリートは2,000台に拡大し、第7世代（Gen 7）の3モデルが日常運行を行っています。中国における登録ユーザー数は150万人を超えました。

広州では、2026年初頭以降にサービスエリアを300平方キロメートル以上拡大し、市内中心部まで運行範囲を広げました。深圳では、同社のネットワークが主要な交通ハブを接続しており、通勤ラッシュ時、祝休日、大雨の状況下でも運行しています。

経営陣によると、広州と深圳ではユニットエコノミクスが黒字化しました。フリート密度の高まりにより乗客の待ち時間が短縮され、リテンション（定着率）の向上や車両1台あたりの日次売上高の増加につながっているとのことです。

アセットライトな国際展開

Pony.aiの共同導入モデルは、同社、モビリティプラットフォーム、地元のフリート事業者間で役割を分担する構造となっています。Pony.aiが第7世代のRobotaxiおよびバーチャルドライバー技術を提供し、パートナー側が乗客需要、フリート資金、保守整備、現地のオペレーション能力を提供します。

このモデルにより、初期の車両導入売上、レベニューシェア収入、技術ライセンス料を上げることができます。経営陣は、導入フリートが拡大するにつれて、継続的な収益の利益率が高まると見込んでいます。

同社は海外で4,000台以上の車両供給に関するコミットメントを獲得しています。これには、Uberとの提携拡大に基づき欧州5都市で展開する2,000台以上のRobotaxiが含まれます。経営陣は、これらのコミットメントを単一期間の導入目標ではなく、複数年にわたる成長カタリストと位置付けています。

また、Pony.aiはルクセンブルクやシンガポールでの継続的な活動のほか、クロアチアのザグレブにおけるRobotaxiの商用導入にも言及しました。

RobotruckおよびL4小型トラック

Robotruckの売上高は、物流輸送売上高に支えられ40%増の1,330万米ドルとなりました。第4世代（Gen 4）のRobotruckは量産および商用運行段階に入っており、深圳の媽湾港（Mawan Port）では有人トラックと並行して完全無人化での運用が行われています。

レベル4（L4）小型トラックに関して、Pony.aiは順豊速運（SF Express）および中国郵政科技（China Post Technology）との提携を獲得したと発表しました。同社は都市型物流への応用を目指しており、自動車メーカー、フリート事業者、物流プラットフォームとの更なる連携を追求する計画です。

技術およびオペレーション効率

PonyWorld 2.0はAIを活用して地域の走行課題を特定し、ターゲットを絞ったソリューションを生成して、更新されたモデルを検証します。経営陣によると、これにより新しい都市に進出する際に必要なエンジニアの数を削減でき、交通行動が異なる複数の市場への並行展開をサポートできるとのことです。

同社はまた、自動駐車、充電ナビゲーション、標準化されたフリート管理ツールを活用して人的介入を減らしています。経営陣によると、日常運行においてRobotaxi 100台あたり約3名の地上スタッフで対応可能であり、車両1台あたりの運行コストを削減しているとのことです。

業績見通し（ガイダンス）

• 経営陣は、2026年通期のRobotaxi売上高が前年の3.5倍を超えると予想しており、当初の見通しよりも自信を深めていることを示しています。
• 同社は、2026年末までにRobotaxiフリートを2,000台から3,500台に拡大する計画が順調に進んでいると表明しました。
• 経営陣は、PonyWorld 2.0と共同導入モデルに支えられ、年内に20都市での運用開始を目指しています。
• Robotruckの成長は2026年後半も継続し、一段と強まる可能性があると見込まれています。
• Pony.aiは、中国の主要市場においてコアとなる自動運転技術および自社所有フリートへの投資を継続する一方で、パートナーの資本を活用して国内外での広範な展開を進める方針です。

リスクおよび注目点

• 営業キャッシュアウトフローは、買掛金の決済および下半期のフリート拡大に向けた在庫投資により、4,400万米ドルに増加しました。
• 設備投資額は、Robotaxiフリート、自動運転機器、データセンターへの支出に伴い増加しました。そのため、拡大のペースは引き続きパートナーからの共同投資にも一部依存しています。
• インテリジェント・ソリューションの成長は、ドメインコントローラーの出荷変動により減速しました。
• 経営陣は、走行距離やフリート規模が拡大するにつれて自動運転の安全性を維持することが困難になると強調しました。規制当局からの承認を得るには、段階的な導入、検証された安全性実績、そして持続的な社会からの信頼が必要となります。
• Pony.aiの汎化能力は強力であると経営陣は考えているものの、運転行動や交通参加者の行動確率は都市ごとに異なるため、地域ごとのモデルのファインチューニングが必要です。

アナリスト質疑応答のハイライト

Uberとの提携：経営陣によると、Uberは大規模展開における技術の信頼性と、競争力のあるハードウェアおよび運行コストを理由にPony.aiを選定したとのことです。Pony.aiは、現在の合意により同社が欧州におけるUber最大の自動運転パートナーになると述べ、性能と経済性が引き続き検証されれば、フリートのさらなる拡大の可能性があるとしています。

共同導入モデルの経済性：アセットライトなモデルでは、一般的にPony.ai、モビリティプラットフォーム、地元のフリート事業者が連携します。パートナーがフリート資金を拠出し現地の運行インフラを提供する一方で、Pony.aiは車両納入、技術ライセンス、および継続的なレベニューシェアからの売上を見込んでいます。

国内展開：経営陣は、中国の第1層都市でフリート密度を高め続けながら、厳選した第2層都市および粤港澳大湾区（グレーターベイエリア）市場に進出する計画です。同社は、規模の拡大により車両稼働率が向上し、拡大されたフリート全体に運用コストを分散できると期待しています。

オープンソースのワールドモデル：経営陣は、汎用的な生成型ワールドモデルでは、レベル4自動運転に必要な現実世界の確率データ、強化学習プロセス、検証フレームワークを代替することはできないと主張しました。したがって、オープンソースモデルがPonyWorld 2.0の競争上の優位性を実質的に弱めることはないと見ています。

スケール拡大と実証実験の比較：経営陣は、限定的な自動運転のデモ走行と大規模な商用フリートの運用は根本的に異なるものだと強調しました。同社は、数桁に及ぶ安全性の向上と規制当局からの信頼獲得が、スケール拡大に向けた主要な障壁であると指摘しています。

決算説明会全文文字起こし

決算説明会の完全なトランスクリプト

経営陣による説明

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.

質疑応答

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.