Is Momenta worth visiting?

A few years ago, the automotive industry—the 'mother industry' of intelligent driving—reached this inflection point. After two years of explosive growth, capital markets began scrutinizing fundamentals: based on current trends, could these companies achieve profitability? Some automakers demonstrated solid profitability, while others showed weak earnings power. Now, several years later, intelligent driving has reached that same moment. Though the industry remains a blue ocean with rapid growth, early signs of commercial viability are already emerging. After all, you don’t need to wait until an industry matures to assess whether a business is sound. A healthy business loses relatively little when unprofitable—and profits exceptionally quickly once it turns its focus toward profitability. Momenta is now entering its second phase—and it’s already exhibiting traits of a fundamentally strong business: its breakeven inflection point is arriving faster than most anticipated. Its semi-annual report shows that, excluding non-operating items such as share-based compensation and changes in fair value of financial liabilities, Momenta’s adjusted net loss for the first half of the year stood at just RMB 14.097 million—a 97% year-on-year reduction. Intelligent driving is a high-R&D-intensity sector, where massive expenditures fund future capabilities. In the first half of the year, Momenta’s R&D spending reached RMB 1.163 billion—over 72% of its revenue. Yet, as Huang Zheng (founder of Pinduoduo) observed, many expenses labeled as ‘costs’ aren’t truly ‘burned’—they instead form business assets capable of generating future revenue. One word captures Momenta’s profit metrics: early. Momenta’s revenue growth remains at 75%. Just two months ago, it completed its IPO—placing it at a developmental stage comparable to Pinduoduo in 2015 or NVIDIA in 1999. Logically, it should still be in the ‘spend-to-gain-market-share’ phase. Yet it already displays the hallmarks of a robust business model. Its gross margin was already high—and rose another 1.4 percentage points year-on-year to 73.2% in H1. Growth in its three major expense categories (sales, general & administrative, and R&D) all lagged behind revenue growth—what’s commonly called ‘organic growth’: customers adopt its products because they’re genuinely superior—not because of heavy marketing spend. For a business growing at 75%, profitability, loss reduction, and gross margin aren’t the top-line metrics. CEO Cao Xudong explicitly stated during the earnings call: “Short-term profitability is not our primary objective at this stage.” Yet strong businesses operate this way—they approach breakeven even before prioritizing profit. Momenta’s data also reflects an industry-wide trend: intelligent driving is entering an era where profitability will be rigorously examined—where stakeholders begin ‘running the numbers.’ For many years, the market evaluated intelligent driving using only one metric: growth rate and total addressable market. But with Momenta’s dramatic loss reduction, investors are now reaching for calculators: What’s the gross margin? Where lies the moat? Can it generate stable cash flow? This is the ‘coming-of-age ceremony’ every nascent industry must undergo—and behind these numbers lie fundamentally different business models across companies. 02 Compared to automobiles, intelligent driving resembles an AI platform more closely Although embedded in the automotive supply chain, Momenta’s business logic differs markedly from that of OEMs. The automotive business’s most critical moats are extreme cost-control capability and brand power. The former is the lifeline of budget vehicles; the latter, the secret behind luxury brands’ enduring appeal.

From burning cash to generating its own cash flow, Momenta is rewriting the commercial logic of autonomous driving.

Once mass-produced vehicles accumulate sufficient scale in data, computing power, models, and engineering capability, the value of this capability extends far beyond the automotive domain. Cao Xudong offered an analogy: achieving autonomous driving is like landing on the moon. Some choose to climb Mount Everest—the Earth’s highest peak closest to the moon—while Momenta chooses to build rockets. Mass-production business is the rocket-building process; the R7 World Model is the rocket’s engine. The R7 World Model operates within a closed-loop framework built on ‘Four Scalings’: First layer: Data Scaling—more data enables the model to better understand the world. As of June 2026, over one million mass-produced vehicles have been equipped with Momenta’s solution, accumulating over 13 billion kilometers of real-world driving mileage and more than 100 million segments of ‘golden data’—enabling the model to grasp the physical world’s operating rules with greater precision. Second layer: Compute Scaling—greater computing power boosts training efficiency. Momenta runs over 10 million kilometers of simulation daily, and its computing capacity continues to scale annually—allowing the model to repeatedly iterate, experiment, and optimize within virtual environments. Third layer: Model Scaling—stronger models deliver better product experiences. As data and compute resources grow, the R7 World Model’s parameter count expands rapidly—translating into enhanced scene-understanding capability, more human-like driving behavior, and safer decision-making—all directly perceptible to end users. Fourth layer: Business Scaling—the more vehicles deployed, the more data generated. Data flows into training compute infrastructure; compute fuels model development; stronger models improve user experience; improved experience attracts more vehicle model partnerships; and commercial revenue follows. These newly partnered vehicles then hit the road—becoming the next round’s data source. The R7 isn’t an ordinary model—it’s a self-accelerating machine powered by scale. If Momenta focused solely on mass-production business, R&D investment would be pure expense: each yuan spent would further erode margins. But within this framework, R&D investment serves as fuel for the flywheel—generating sustained, self-reinforcing momentum. Passenger vehicles, Robotaxis, Robovans, Robotrucks—and even future robots—can all share the same foundational world model. In the past, autonomous driving R&D resembled discrete project costs. Today, the world model functions more like reusable infrastructure—capable of cross-vehicle and cross-scenario deployment—and shouldn’t be confined by the label ‘ADAS.’ The path to breakeven hinges on repeated utilization of this technological foundation; vehicle deployment volume is merely the natural outcome along that path. Momenta Robovan targets express delivery and overnight logistics scenarios. Momenta allocates 70% of its revenue to R&D—not just chasing near-term profits, but unlocking far broader value beyond mass production, expanding from ‘ADAS’ into the wider physical world. The Robovan is already undergoing trial operations in Suzhou, targeting urban last-mile logistics. Momenta’s roadmap is equally clear: ・Q4 2026: Launch of the first mass-produced Robotaxi model, powered by the R7 World Model; ・By end-2026: Deployment of hundreds of Robotaxis domestically and internationally, with operating licenses secured in over 10 cities; ・2027: Entry into the Robotruck domain; ・Momenta has also laid groundwork for another initiative: launching robotics business in 2027.

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