Robot makerShenzhen, ChinaFounded 2022
Builds the Oli humanoid and TRON legged robots and the COSA agentic OS with the LimX WBT whole-body motion model.
LimX Dynamics (逐际动力) was founded in Shenzhen in January 2022. It builds the TRON 1 and TRON 2 legged robots and the Oli humanoid, and in January 2026 announced COSA, an agentic operating system for humanoids whose motion layer runs the LimX WBT whole-body model. It also open-sourced the FluxVLA Engine for VLA training and deployment in April 2026.
Sources: limxdynamics.com (19 Oct 2026) · limxdynamics.com (12 Jan 2026) · limxdynamics.com (30 Apr 2026)
Private company · $400M disclosed in USD across 2 of 6 listed rounds
| Date | Round | Amount | Lead | Source |
|---|---|---|---|---|
| Jul 2022 | Angel | undisclosed | n/a | limxdynamics.com, 19 Oct 2026 |
| Oct 2023 | Angel and Pre-A (combined) | RMB 200M | n/a | limxdynamics.com, 19 Oct 2026 |
| Jul 2024 | Series A | undisclosed | Alibaba | limxdynamics.com, 19 Oct 2026 |
| Jul 2025 | Strategic | undisclosed | JD.com | limxdynamics.com, 19 Oct 2026 |
| Feb 2026 | Series B | $200M | n/a | limxdynamics.com, 19 Oct 2026 |
| Jul 2026 | Pre-IPO | $200M | n/a | qbitai.com, 16 Jul 2026 |
#72 of 104 model companies · score 12.7 / 100 · updated 19 Oct 2026
Each bar shows an input from 0 to 100% before weighting. 0 of 2 listed models have open weights.
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.
| Input | Weight | How it is measured |
|---|---|---|
| Published benchmarks | 35% | 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 weights | 20% | Share of the company's listed models whose weights the public can download. |
| Adoption | 20% | 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 models | 15% | Number of publicly announced, named models, capped at 5. |
| Disclosed funding | 10% | 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.
Closed weightsPolicy
Whole-body motion foundation model running at 1000 Hz as the motion-control layer (S0) of LimX COSA 0.5 on the Oli humanoid.
No benchmark results on a shared public benchmark have been published for this model.
Closed weightsEmbodied reasoning
Agentic operating system for humanoids that layers cognition and memory, reusable skills and a whole-body control foundation model; version 0.5 shown in July 2026.
No benchmark results on a shared public benchmark have been published for this model.
