China’s X Square Robot raises USD140.3 million led by Alibaba Cloud and launches Wall-OSS, an open source foundation model designed to fast-track embodied intelligence adoption.
X Square Robot, a Chinese startup focused on general-purpose embodied intelligence, has launched Wall-OSS, one of the country’s first open source embodied foundation models, alongside raising USD140.3 million (nearly CNY1 billion) in a Series A+ financing round.
The funding was led by Alibaba Cloud, marking its first investment in humanoid robotics. Other participants included Guoke Investment, China Development Bank Financial, Meituan, and Lenovo. Earlier this year, Meituan had led X Square’s Series A round. The latest deal was also the first time Alibaba and Meituan jointly backed a humanoid robot maker.
Wall-OSS offers developers a complete toolkit, including model parameters, training and inference code, optimisation solutions, and toolchains. According to Wang Qian, Founder and CEO of X Square, “We hope that the open sourced model will become an out-of-the-box ‘brain’ for more developers, enabling them to put it into use. Only when the open-sourced model becomes a widely applicable tool can the industry truly embrace the era of general-purpose embodied intelligence.”
Wang noted that the company shortens iteration cycles to every two to three months and has built a large-scale data collection factory to ensure high-quality proprietary data for training. While the firm’s products remain in the proof-of-concept phase, rapid iterations are paving the way for industrial adoption.
X Square has also unveiled hardware, including the Quanta X2 humanoid robot and a dexterous hand with 20 degrees of freedom, with plans for small-scale shipments by end-2025.
A source close to Alibaba Cloud said the company invested because it is optimistic about X Square’s technical path and iteration pace, adding, “There are also precedents overseas where robot makers ally with cloud service providers such as Amazon Web Services and Microsoft Azure.”














































































