StartupChinaFounded 2024
Develops the Spirit series of vision-language-action foundation models for robot manipulation.
Spirit AI is a Chinese embodied AI company founded in January 2024 by Han Fengtao, a serial robotics entrepreneur, with co-founder Gao Yang, an assistant professor at Tsinghua University's Institute for Interdisciplinary Information Sciences. It develops embodied foundation models, including Spirit v1.6, and robot platforms. It completed four funding rounds totalling nearly RMB 5 billion between February and June 2026.
Sources: stcn.com (24 Feb 2026) · stcn.com (3 Jun 2026)
Private company
| Date | Round | Amount | Lead | Source |
|---|---|---|---|---|
| Nov 2024 | Angel+ | Undisclosed | Borui Capital | stcn.com, 24 Feb 2026 |
| Feb 2026 | Two consecutive roundsValuation: Over RMB 10B | Nearly RMB 2B (combined) | Yunfeng Fund, Sequoia China, Hundun Investment | stcn.com, 24 Feb 2026 |
| 7 Apr 2026 | Undisclosed | RMB 1B | Shunwei Capital, Yunfeng Fund | m.thepaper.cn, 7 Apr 2026 |
| 3 Jun 2026 | Series A+ | RMB 1.5B | n/a | stcn.com, 3 Jun 2026 |
#59 of 104 model companies · score 27.8 / 100 · updated 19 Oct 2026
Each bar shows an input from 0 to 100% before weighting. 1 of 2 listed models have open weights. Most-starred official repository: Spirit-AI-Team/spirit-v1.5 (666 stars, 19 Oct 2026).
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.
Open weightsVLA
VLA with a Qwen3-VL-4B backbone and a DiT flow-matching action head; company reported first place on the RoboChallenge Table30 real-robot benchmark as of 2026-01-11.
No benchmark results on a shared public benchmark have been published for this model.
Closed weightsVLA
Successor to Spirit v1.5 that briefly topped the RoboArena leaderboard in June 2026; SCMP later reported it was removed from the leaderboard after a methodology overhaul citing benchmark hacking.
No benchmark results on a shared public benchmark have been published for this model.
