Recently, the embodied intelligence company, X Square Robot Technology (Shenzhen) Co., Ltd. (hereinafter referred to as “X Square Robot”) completed a round of A financing of hundreds of millions of yuan, led by Meituan Strategic Investment Department and followed by Meituan DragonBall. This round of financing will be used to continuously accelerate the synchronous iteration of the fully self-developed end-to-end universal embodied intelligence large model and the robot body, as well as the cooperation and implementation of intelligent solutions for multiple application scenarios in the future.
| Release date | Round | Financing amount | Investors |
| May 12, 2025 | A round | Hundreds of millions of yuan | Meituan and Meituan DragonBall |
| March 12, 2025 | Pre-A round | Hundreds of millions of yuan | Meridian Capital, Yunqi Partners and GF Xinde Investment |
| March 27, 2024 | Angle round | Tens of millions of yuan | Unity Ventures |
X Square Robot was established in Shenzhen in December 2023 and set up a Beijing branch on March 1, 2024. Its business mainly focuses on the research and development of “universal embodied large models” to provide robots with a universal large model base. The company’s goal is to build a universal brain-cerebellum system for robots, providing end-to-end capabilities from perception to action.
According to the information at Qcc.com, X Square Robot has completed five rounds of financing since its establishment, with a cumulative financing of more than 1 billion yuan. Investors include Delian Capital, Cornerstone Capital, QF Capital, Nanshan SEI Investment, Lightspeed China Partners, Legend Capital, Meridian Capital, Yunqi Partners, GF Xinde Investment and many other institutions.
Information shows that X Square’s self-developed robot universal model platform is a combination of multi-modal large model, Large Manipulation Model, and robot body. The basic model currently developed by the team can train robots to complete complex and delicate physical operations.
It is understood that the company has independently developed dozens of data processing models and multiple generations of data acquisition equipment to achieve automatic control of data quality and comprehensive improvement of data acquisition efficiency.
At the hardware level, the company independently developed and continuously optimized the robot body adapted to multi-modal large model control to better meet the needs of fine operation and stable operation in an open environment. At present, the robot body of X Square has been put into use in multi-step complex task scenarios.
According to official disclosures, since the end of last year, the X Square Robot has made breakthroughs in multi-modal output and embodied thinking chain, earlier than the time when Gemini Robotics announced the research results of thinking chain in March this year.
Public information shows that Wang Qian, the Founder and CEO, graduated from Tsinghua University and is one of the earliest scholars in the world to introduce attention mechanisms in neural networks. During his doctoral studies, Wang Qian participated in a number of Robotics Learning studies in top robotics laboratories in the United States, covering many cutting-edge fields of robotics.
Wang Hao, the Co-founder and CTO, is a PhD in computational physics from Peking University. During his time at the Guangdong-Hong Kong-Macao Greater Bay Area International Digital Economy Academy (IDEA), he served as the algorithm leader of the Fengshenbang big model team and released the country’s first multimodal open source big model “Taiyi”, the first batch of 10 billion-level big language models “Randeng” and 100 billion-level big language model “Jiang Ziya”.
Wang Qian said that the development of embodied intelligence depended on the advantages of model algorithms in the short term, data advantages in the medium term, and product advantages in the long term. X Square has always deepened its accumulation around these three major directions, and has taken the lead in implementing open service scenarios in China to explore service closed loops in different scenarios.
