Robot makerSan Jose, CA, United StatesFounded 2022
Builds the Figure humanoid robots and trains the Helix family of vision-language-action models that control them.
Figure is a US robotics company founded in 2022 by Brett Adcock that develops general-purpose humanoid robots and the AI models that control them. Its first-generation robot, Figure 01, was announced in 2023. In September 2025 it reported more than $1B in committed Series C capital at a $39B post-money valuation. The company is headquartered in San Jose, California.
Sources: therobotreport.com (29 Feb 2024) · figure.ai (16 Sep 2025) · figure.ai (17 Oct 2026)
Private company · $1.75B disclosed in USD across 3 of 3 listed rounds
| Date | Round | Amount | Lead | Source |
|---|---|---|---|---|
| 24 May 2023 | Series A | $70M | Parkway Venture Capital | parkway.vc, 24 May 2023 |
| 29 Feb 2024 | Series BValuation: $2.6B | $675M | n/a | therobotreport.com, 29 Feb 2024 |
| 16 Sep 2025 | Series CValuation: $39B post-money | >$1B | Parkway Venture Capital | figure.ai, 16 Sep 2025 |
We list this brand but do not currently carry its robots.
#62 of 104 model companies · score 18.3 / 100 · updated 19 Oct 2026
Each bar shows an input from 0 to 100% before weighting. 0 of 3 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 weightsVLA
Helix model pretrained on Figure's Index human-behavior dataset and adapted to whole-body household tasks; Figure reports zero-shot operation in 30 unseen homes.
No benchmark results on a shared public benchmark have been published for this model.
Closed weightsVLA
Extends Helix to full-body control on Figure 03 with a third layer (System 0, a 10M-parameter whole-body balance controller at 1 kHz) under System 1 (200 Hz) and System 2.
No benchmark results on a shared public benchmark have been published for this model.
Closed weightsVLA
Dual-system VLA: a 7B vision-language model at 7-9 Hz conditions an 80M visuomotor policy at 200 Hz controlling a 35-DoF humanoid upper body, running onboard.
No benchmark results on a shared public benchmark have been published for this model.
