robbyant/lingbot-vla-4b-depth

A Pragmatic VLA Foundation Model

LingBot-VLA has focused on Pragmatic:

• Large-scale Pre-training Data: 20,000 hours of real-world data from 9 popular dual-arm robot configurations.
• Strong Performance: Achieve clear superiority over competitors on simulation and real-world benchmarks.
• Training Efficiency: Represent a 1.5 ∼ 2.8× (depending on the relied VLM base model) speedup over existing VLA-oriented codebases.

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Model Sources

• Repository: https://github.com/robbyant/lingbot-vla
• Paper: A Pragmatic VLA Foundation Model
• Project Page: https://technology.robbyant.com/lingbot-vla

Related Models

Model Name	Huggingface	ModelScope	Description
LingBot-VLA-4B	🤗 lingbot-vla-4b	🤖 lingbot-vla-4b	LingBot-VLA w/o Depth
LingBot-VLA-4B-Depth	🤗 lingbot-vla-4b-depth	🤖 lingbot-vla-4b-depth	LingBot-VLA w/ Depth

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Citation

@article{wu2026pragmatic,
  title={A Pragmatic VLA Foundation Model},
  author={Wei Wu and Fan Lu and Yunnan Wang and Shuai Yang and Shi Liu and Fangjing Wang and Shuailei Ma and He Sun and Yong Wang and Zhenqi Qiu and Houlong Xiong and Ziyu Wang and Shuai Zhou and Yiyu Ren and Kejia Zhang and Hui Yu and Jingmei Zhao and Qian Zhu and Ran Cheng and Yong-Lu Li and Yongtao Huang and Xing Zhu and Yujun Shen and Kecheng Zheng},
  journal={arXiv preprint arXiv:2601.00000},
  year={2026}
}

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License Agreement

This project is licensed under the Apache-2.0 License.

Acknowledgement

This codebase is builded on the VeOmni project. Thanks for their excellent work!