Li Auto logo

Li Auto

Robot makerDrivingBeijing, China

Electric-vehicle maker that develops the MindVLA family of vision-language-action driving models.

Overview

Li Auto is an electric-vehicle maker based in Beijing and listed on Nasdaq. In March 2026, at NVIDIA GTC 2026, it unveiled MindVLA, its next-generation autonomous-driving foundation model, together with a 3D ViT encoder. Li Auto researchers also co-authored the DriveVLM driving vision-language model paper with Tsinghua University.

Sources: sec.gov (1 Apr 2026) · arxiv.org (19 Feb 2024)

Type
Robot maker
Headquarters
Beijing, Chinasec.gov, 19 Oct 2026

Funding history

Public company · Listed on Nasdaq (LI).

Ranking

#86 of 104 model companies · score 6.7 / 100 · updated 19 Oct 2026

  • Published benchmarks 35%0%
  • Open weights 20%0%
  • Adoption 20%0%
  • Released models 15%40%
  • Disclosed funding 10%n/a

Each bar shows an input from 0 to 100% before weighting. 0 of 2 listed models have open weights.

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.

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Closed or unreleased-weights models (2)

Li Auto logo

MindVLA

Closed weightsVLA

Autonomous-driving foundation model that Li Auto says forms, with its 3D ViT encoder, an architecture that perceives the 3D physical world with unified geometric and semantic understanding.

Released
Mar 2026
Parameters
n/a
License
Proprietary
Embodiments
car
GitHub stars
n/a
HF downloads (all time)
n/a

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

Li Auto logo

DriveVLM

Closed weightsVLA

Vision-language model for driving scene understanding and planning, paired with a conventional pipeline in the DriveVLM-Dual system; co-authored by Tsinghua University and Li Auto researchers.

Released
19 Feb 2024
Parameters
n/a
License
n/a
Embodiments
car
GitHub stars
n/a
HF downloads (all time)
n/a

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