Insider Brief
- X Square Robot completed a Series A++ funding round of about $140 million, backed by investors including ByteDance and HongShan, adding to earlier support from Alibaba Group and Meituan.
- The company is developing a general-purpose embodied AI foundation model called WALL-A, which integrates vision-language-action models with world models and large-scale real-world reinforcement learning to improve zero-shot generalization and autonomous task execution in unstructured environments.
- X Square Robot has demonstrated commercial progress with autonomous food delivery and logistics deployments using its Quanta robot platforms, while advancing a closed-loop strategy that tightly links hardware design, real-world data capture, and model iteration to support scaling across manufacturing, logistics, and healthcare.
PRESS RELEASE — X Square Robot, a pioneer in general purpose embodied AI, announced on January 12 the completion of its Series A++ funding round, raising about US$140 million (RMB 1 billion). The funding attracted world-class investors, including ByteDance and HongShan, along with several other strategic Chinese partners.
With leading tech companies such as Alibaba Group and Meituan already backing it from previous rounds, X Square Robot has demonstrated compelling model capabilities and product potential that continue to attract investor confidence.
“We’re honored to have the strong endorsement of our world-class strategic investors,” said WANG Qian, founder and CEO of X Square Robot. “At X Square, we believe the key to enabling robots to truly master real-world tasks lies in the ‘robot brain’—a foundation model for the physical world that parallels virtual LLMs to shatter generalization bottlenecks. This investment underscores shared confidence in our role as a catalyst for technological progress and will accelerate our expansion into high-value applications.”
WALL-A: Integrating VLA with World Models for Continuous Real-World Evolution
Founded in December 2023, X Square Robot is a trailblazer in developing general-purpose end-to-end embodied AI foundation models in China. The company’s in-house developed VLA model, WALL-A, pioneered a system paradigm that deeply integrates VLA with World Models, ranking among the world’s most advanced systems. By using World Models to predict actions and causal inference to understand feedback, the model significantly enhances the zero-shot generalization capabilities of robots performing mobile manipulation tasks in unstructured environments.
Simultaneously, large-scale real-robot reinforcement learning (RL) allows the foundation model to learn through physical interaction. This data-driven approach enables the robot to autonomously refine its skills and perform complex tasks in real-world environments.
Alongside the development of WALL‑A, X Square Robot introduced WALL‑OSS in September 2025, an open‑source version of its model family designed to democratize embodied intelligence and accelerate community‑driven innovation.
“The next phase of competition in embodied intelligence is essentially a battle of foundation models built on data closed-loops and their capacity for model evolution,” noted Mr. Wang.
To win this race, X Square Robot is also adhering to a closed-loop iteration of hardware, data, and models. As the first company in China to scale up real-world data resources, it has developed advanced data capture tools—including teleoperation, exoskeletons, and Universal Manipulation Interface (UMI). The company has also established a model-driven data pipeline that generates high-quality data at scale. By using the foundation model to provide feedback on hardware design and data processing, X Square Robot is improving acquisition efficiency and model performance, creating a self-reinforcing “flywheel”.
A First in Robotics: Fully Autonomous Food Delivery Using Foundation Models
This end-to-end adaptability is proof that embodied AI has moved into practical, real-world deployment. A landmark breakthrough was recently demonstrated in autonomous food delivery, powered by Wall-A, where the Quanta X1, X Square Robot’s wheeled bimanual robot, successfully navigated indoor and outdoor tasks to complete a delivery in an open environment.
During the mission, Quanta X1 handled challenges such as strong winds, deformed packaging, and visual occlusions. Much like a human, the robot used the model’s causal inference to “fill in the blanks” when objects were partially hidden. When encountering operational stalls or friction, the robot autonomously self-corrects and completes the task loop without any human intervention.
This capacity is also demonstrated in complex logistics; facing piles of parcels, the robot utilizes zero-shot generalization to identify irregular items. Notably, the model’s evolution has unlocked the potential of high DoF (degree of freedom) dexterous hands, mastering human-like skills from tool use to precise card dealing—successfully conquering the “last centimeter” of precision manipulation.
From Full-Stack R&D to Multi-Scenario Deployment
Driven by model and data requirements, X Square Robot has deeply defined its hardware architecture, releasing two high-performance robots: Quanta X1 and the Quanta X2, a wheeled humanoid robot. Meanwhile, X Square Robot also uses in-house developed core components—including robotic arms, joint modules, and controllers—establishing a solid foundation for mass production and commercial scale.
“X Square Robot continues to iterate across our three core pillars: models, data pipelines, and hardware,” said Wang. “By leveraging our technical depth and full-stack R&D, we consistently push the boundaries of robot performance.”
Today, X Square Robot’s solutions are driving “a new era where embodied intelligence powers every layer of productivity.” Its technologies are increasingly deployed across key industry verticals—from advanced manufacturing and autonomous logistics to senior healthcare services.
Image credit: X Square Robot
