With the launch of the L9 Livis, Li Auto enters the era of embodied intelligence
Over the past few years, Li Auto has excelled at packaging complex technologies into concrete family-oriented scenarios. Range-extending technology was designed to alleviate range anxiety for family users, while features like refrigerators, flat-screen TVs, and large sofas were intended to redefine the boundaries of a family SUV’s functionality. Li Auto’s past success has largely stemmed from this ability. However, the launch of the all-new Li Auto L9 Livis signals a new direction. This time, Li Auto is aiming to go beyond simply “upgrading its flagship family SUV.” As Li Xiang recently articulated in his discussion of embodied intelligence, the all-new Li Auto L9 Livis serves more as a transitional prototype. Li Auto is attempting to extend the product capabilities it has built around family scenarios into the underlying technological and organizational frameworks. If the previous phase of Li Auto addressed the question of “how to build a car that better understands family users,” this time the question has shifted to: Once a car possesses stronger perception, judgment, and action capabilities, how far will the boundaries of an automaker be pushed? Li Xiang refers to this direction as embodied intelligence. He posits that “autonomous driving is the first half of embodied intelligence, while general-purpose humanoid robots are the second half.” This statement may sound like a grand technological assertion, but viewed within the context of Li Auto’s own development trajectory, it actually points to a more practical issue. Li Auto is no longer content with simply creating a single blockbuster model; instead, it aims to build a set of foundational capabilities for the next decade centered around chips, models, operating systems, perception systems, and actuators. For the embodied intelligence industry, humanoid robots are still in their early stages. Before they can enter households and open environments on a large scale, they must overcome multiple hurdles related to cost, reliability, generalization capabilities, and safety. The automotive industry, however, is already a mature, trillion-dollar sector. Therefore, breakthroughs in autonomous driving are likely to serve as a testing ground for the scaled deployment of embodied intelligence. The all-new Li L9 is the first concrete manifestation of this strategic shift. It also marks the first time Li Auto has integrated its self-developed chips, perception models, the VLA driver model, by-wire chassis, active suspension, and operating system into a single product framework. It remains a family SUV and must still face direct sales competition in the high-end new energy vehicle market. But behind the product, Li Auto is undergoing a deeper transformation—shifting from an automaker skilled at defining family vehicle needs to a technology company striving to master the foundational capabilities of “intelligentizing the physical world.” Why Is Li Auto Talking About “Embodied Intelligence”? To understand Li Auto’s embodied intelligence strategy, it may be helpful to start with the industry logic. Over the past decade, AI has primarily transformed the digital world. Text, images, code, search, and knowledge management have all been reshaped by large language models. However, changes in the physical world have been relatively slow. Interactions with the environment in people’s daily lives still rely on humans to carry out. The automobile is one of the key gateways for AI to enter the physical world. Compared to humanoid robots, cars possess a more mature industrial chain, clearer use cases, and a larger-scale data ecosystem. They are inherently “embodied”: equipped with sensors to perceive the environment, a computing platform to process information, a control system to execute actions, and an operating system to coordinate all modules. In this sense, a car with advanced autonomous driving capabilities is, in itself, a product of embodied intelligence. Li Xiang has already broken down the development of embodied intelligence into a relatively clear industrial roadmap: the first half is autonomous vehicles, and the second half is general-purpose humanoid robots. In the first half—autonomous vehicles—Li Xiang divides the journey into three stages: 2018 to 2023 is the L2 driver-assistance stage; 2023 to 2028 is the L3 autonomous driving stage; 2028 to 2033 is the L4 autonomous driving stage. In the second half, general-purpose humanoid robots will enter three new stages: from 2030 to 2035, they will possess generalization capabilities equivalent to a 6-year-old child; from 2035 to 2040, they will reach the level of a 12-year-old; and from 2040 until the realization of AGI, they will possess generalization capabilities approaching those of an 18-year-old adult. According to Ideal’s own technological classification, the L3 stage from 2023 to 2028 corresponds to 2D ViT perception, pre-trained models, end-to-end control, and computing power of approximately 2,000 TOPS; whereas the L4 stage from 2028 to 2033 will further evolve toward 3D ViT perception, stable pre-trained models, a fully autonomous control system, and computing power approaching 10,000 TOPS. From this perspective, the perception, models, chips, operating systems, and control capabilities accumulated in the first half of this journey are likely to become the foundational capabilities for robots in the second half. Li Auto views both autonomous vehicles and general-purpose humanoid robots as core forms of embodied intelligence products, and anticipates a high degree of overlap between future L4 autonomous driving users and general-purpose humanoid robot users. Therefore, what truly merits attention about Li Auto this time is not merely that it has “developed its own chips” or “created a by-wire chassis,” but rather that these technical capabilities have already partially surpassed the basic requirements of the current stage, representing Li Auto’s redesign of its future growth trajectory. Organizational Capabilities Adjustments Behind the Strategy If viewed solely through the lens of products and technology, Li Auto’s strategic moves could easily be interpreted as “stepping up AI R&D.” However, judging from a recent conversation between Li Xiang and Luo Yonghao, Li Auto’s deeper transformation lies in using AI to restructure its organization and production processes. During the conversation, Li Xiang repeatedly mentioned that the most important task over the past 200-plus days has been learning about AI. He not only uses AI tools himself but also encourages employees to adopt tools like Claude Code and OpenClaw,
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