Tsinghua University Institute for AI Industry Research (AIR) logo

Tsinghua University Institute for AI Industry Research (AIR)

Research labChina

Tsinghua University research institute that released X-VLA, a 0.9B soft-prompted cross-embodiment VLA, with Shanghai AI Lab co-authors.

Overview

The Institute for AI Industry Research (AIR) is a research institute of Tsinghua University, with Ya-Qin Zhang as dean. Its researchers, with co-authors from Shanghai AI Lab and Peking University, published X-VLA in October 2025, a 0.9B-parameter VLA that uses embodiment-specific soft prompts to train across heterogeneous robots; pretrained and fine-tuned checkpoints are released under Apache-2.0.

Sources: air.tsinghua.edu.cn (19 Oct 2026) · arxiv.org (11 Oct 2025)

Type
Research lab

Key people

Funding history

Research lab · Research institute of Tsinghua University; no separate funding disclosed

Ranking

#13 of 104 model companies · score 76.5 / 100 · updated 19 Oct 2026

  • Published benchmarks 35%97%
  • Open weights 20%100%
  • Adoption 20%60%
  • Released models 15%20%
  • Disclosed funding 10%n/a

Each bar shows an input from 0 to 100% before weighting. 1 of 1 listed models have open weights. Most-starred official repository: 2toinf/X-VLA (744 stars, 19 Oct 2026).

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.

Submit or correct data →

Open-weights models (1)

Tsinghua University Institute for AI Industry Research (AIR) logo

X-VLA

Open weightsVLA

Cross-embodiment transformer VLA that conditions on learnable per-embodiment soft prompts.

Released
11 Oct 2025
Parameters
0.9B
License
Apache-2.0
Embodiments
single-arm, bimanual, car
GitHub stars
744 as of 19 Oct 2026
HF downloads (all time)
129.5k as of 19 Oct 2026
Published benchmark results for X-VLA
BenchmarkResultSource
LIBEROAverage success rate across LIBERO-Spatial/Object/Goal/Long (%)98.1%arxiv.orgTable 2. As of 11 Oct 2025
SimplerEnv Google VMSimplerEnv Google Robot visual matching average (%)80.4%arxiv.orgTable 2. As of 11 Oct 2025
SimplerEnv Google VASimplerEnv Google Robot variant aggregation average (%)75.7%arxiv.orgTable 2. As of 11 Oct 2025
SimplerEnv WidowXSimplerEnv WidowX (Bridge) average (%)95.8%arxiv.orgTable 2. As of 11 Oct 2025
CALVIN ABC→DAverage successful length, CALVIN ABC->D (0-5)4.43arxiv.orgTable 2. As of 11 Oct 2025