Unitree Robotics logo

Unitree Robotics

Robot makerHangzhou, ChinaFounded 2016

Builds quadruped and humanoid robots and releases the UnifoLM family of world-model-action and VLA models.

Overview

Unitree Robotics is a Hangzhou-based maker of quadruped and humanoid robots founded in 2016 by Wang Xingxing. Its products include the Go2, B2 and A2 quadrupeds and the H1, G1, H2 and R1 humanoids, and it also publishes robot models and datasets such as UnifoLM. It listed on the Shanghai STAR Market on August 19, 2026 at 150.8 yuan per share, raising about RMB 6.1 billion.

Sources: unitree.com (17 Oct 2026) · caixinglobal.com (3 Jul 2026) · finance.yahoo.com (19 Aug 2026)

Type
Robot maker
Headquarters
Hangzhou, Chinafinance.yahoo.com, 19 Aug 2026
Founded
2016caixinglobal.com, 3 Jul 2026

Key people

Funding history

Public company · Listed on the Shanghai STAR Market since Aug 2026

Funding rounds for Unitree Robotics
DateRoundAmountLeadSource
Feb 2024Series B2Nearly RMB 1Bn/aeu.36kr.com, 20 Jun 2025
Sep 2024Series C (partial)Valuation: RMB 8B (reported)Hundreds of millions of RMBn/aeu.36kr.com, 20 Jun 2025
Jun 2025Series CValuation: Over RMB 12B post-moneyNearly RMB 700MFunds under China Mobile, Tencent, Jinqiu, Alibaba, Ant Group and Geely Capitaleu.36kr.com, 20 Jun 2025
19 Aug 2026IPO (STAR Market)About RMB 6.1B (about $905M)n/afinance.yahoo.com, 19 Aug 2026

Robots and products

Ranking

#11 of 104 model companies · score 77.8 / 100 · updated 19 Oct 2026

  • Published benchmarks 35%100%
  • Open weights 20%67%
  • Adoption 20%64%
  • Released models 15%60%
  • Disclosed funding 10%n/a

Each bar shows an input from 0 to 100% before weighting. 2 of 3 listed models have open weights. Most-starred official repository: unitreerobotics/unifolm-world-model-action (1.2k stars, 19 Oct 2026).

How we rank model companies

The score (0–100) measures public, checkable evidence about a company's robot models. It does not measure private capability. A company that publishes no benchmark results and no weights can still have strong models. Every input is computed from the data on each company page, and every number there links to its source.

InputWeightHow it is measured
Published benchmarks35%For each scored benchmark, the company's best result divided by the best result any company has published, averaged over the benchmarks it reports. No published results scores 0. Results come only from the model's own paper, model card or the official benchmark leaderboard. Scored: LIBERO (4-suite average success, %); SimplerEnv Google Robot, visual matching (%); SimplerEnv Google Robot, variant aggregation (%); SimplerEnv WidowX / Bridge (%); CALVIN ABC→D (average length, 0–5); RoboArena (pairwise rating).
Open weights20%Share of the company's listed models whose weights the public can download.
Adoption20%GitHub stars on the company's most-starred official model repository, on a log scale relative to the most-starred repository in the list. Hugging Face downloads are shown on company pages but not scored, because gated repositories report zero.
Released models15%Number of publicly announced, named models, capped at 5.
Disclosed funding10%The sum of the funding rounds listed on the company's profile that were disclosed in USD, on a log scale from $10M to the largest sum in the list. Rounds reported only in other currencies are listed but not converted or counted. This input applies only to private startups and robot makers. For big-tech divisions, research labs and listed companies it is n/a, and its weight is shared across the other inputs in proportion.

Sources. arXiv papers and official model cards for benchmarks and parameters; official leaderboards (RoboArena); the GitHub and Hugging Face APIs for stars and downloads; company announcements and established press for funding. Missing values are shown as n/a, never estimated.

Updated 19 Oct 2026. Benchmark protocols differ between papers, for example in fine-tuning and number of trials, so small gaps between close scores are not meaningful.

Submit or correct data →

Open-weights models (2)

Unitree Robotics logo

UnifoLM-VLA-0

Open weightsVLA

Vision-language-action model built on Qwen2.5-VL-7B for humanoid manipulation, released with VLM-Base, VLA-Base and LIBERO-tuned checkpoints.

Released
29 Jan 2026
Parameters
n/a
License
CC BY-NC-SA 4.0
Embodiments
humanoid
GitHub stars
642 as of 19 Oct 2026
HF downloads (all time)
1k as of 19 Oct 2026
Published benchmark results for UnifoLM-VLA-0
BenchmarkResultSource
LIBEROAverage success rate across LIBERO-Spatial/Object/Goal/Long (%)98.7%unigen-x.github.ioOfficial project page LIBERO table: Spatial 99.0, Object 100, Goal 99.4, Long 96.2, avg 98.7. As of 29 Jan 2026
Unitree Robotics logo

UnifoLM-WMA-0

Open weightsWorld model

World-model-action framework pairing a video-generation world model with an action head, released as Base and Dual checkpoints with training and inference code.

Released
15 Sep 2025
Parameters
n/a
License
CC BY-NC-SA 4.0
Embodiments
single-arm, bimanual, humanoid
GitHub stars
1.2k as of 19 Oct 2026
HF downloads (all time)
n/a

No benchmark results on a shared public benchmark have been published for this model.

Closed or unreleased-weights models (1)

Unitree Robotics logo

UnifoLM-X2-1.0

Closed weightsWorld model

Real-time world model demonstrated controlling a Unitree G1 humanoid in autonomous sparring; no paper, weights or benchmarks found.

Released
Sep 2026
Parameters
n/a
License
n/a
Embodiments
humanoid
GitHub stars
n/a
HF downloads (all time)
n/a

No benchmark results on a shared public benchmark have been published for this model.