Unitree targets $610M IPO as humanoid robots drive 335% revenue growth
What's the deal? Unitree Robotics, a Hangzhou-based robot maker, has filed for an initial public offering in Shanghai, aiming to raise about $610 million. The company reported 2025 revenue of 1.71 billion yuan ($248 million), up 335% year on year, while adjusted net profit reached around 600 million yuan ($87 million), highlighting strong growth driven by humanoid robots.
Humanoid systems have become its core business, accounting for more than half of revenue in the first nine months of 2025. The company shipped over 5,500 units last year and claims a leading position globally in humanoid robot shipments.
Why now? The listing comes as China increases support for robotics and embodied AI, positioning the sector as a future economic driver. Investor interest has also surged, fuelled by rapid advances in AI and rising demand for automation across industries.
Unitree’s momentum reflects this shift. Its revenue and profit growth coincide with broader excitement around humanoid robots, which are increasingly seen as the next frontier after software-based AI.
What could go wrong? Despite strong growth, real-world adoption remains limited. Much of Unitree’s current revenue comes from controlled environments such as exhibitions, enterprise reception, and guided tours, rather than large-scale industrial deployment.
Margins could also face pressure as the company lowers prices to scale adoption. Competition is intensifying globally, and the sector still needs to prove long-term commercial viability beyond demonstrations.
The signal: Unitree’s IPO marks a turning point where robotics begins to resemble a true commercial market, not just a research field. The combination of fast growth, profitability, and public market ambition suggests humanoid robots are moving closer to mainstream adoption.
At the same time, the playbook looks familiar — early hype, rapid capital inflow, and a race to scale before real use cases fully mature. If demand holds, robotics could follow a path similar to earlier AI waves, where infrastructure, applications, and platforms evolve in parallel.
A.M.
