StartupBerkeley, CA, United StatesFounded 2017
Developed RFM-1, a robotics foundation model trained on data from its warehouse pick-and-place deployments.
Covariant is a Bay Area AI robotics company founded in 2017 by Pieter Abbeel, Peter Chen, Rocky Duan and others, which builds AI models for warehouse picking and fulfillment robots. In August 2024 Amazon hired its three co-founders and about a quarter of its staff and took a non-exclusive license to its robotic foundation models. Covariant continues to operate independently under CEO Ted Stinson.
Sources: prnewswire.com (6 May 2020) · aboutamazon.com (30 Aug 2024) · techcrunch.com (31 Aug 2024)
Private company · In August 2024 Amazon hired Covariant's co-founders and about a quarter of its staff and licensed its models on a non-exclusive basis; Covariant was not acquired. · $195M disclosed in USD across 3 of 3 listed rounds
| Date | Round | Amount | Lead | Source |
|---|---|---|---|---|
| 6 May 2020 | Series B | $40M | Index Ventures | techcrunch.com, 6 May 2020 |
| 27 Jul 2021 | Series C | $80M | Index Ventures | techcrunch.com, 27 Jul 2021 |
| 4 Apr 2023 | Series C extension | $75M | Radical Ventures, Index Ventures | techcrunch.com, 4 Apr 2023 |
#83 of 104 model companies · score 8.4 / 100 · updated 19 Oct 2026
Each bar shows an input from 0 to 100% before weighting. 0 of 1 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
Multimodal robotics foundation model trained on data from Covariant's warehouse pick-and-place fleet; accepts text and image inputs and predicts actions and video.
No benchmark results on a shared public benchmark have been published for this model.
