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---
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license: apache-2.0
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language:
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- en
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pipeline_tag: image-text-to-text
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tags:
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- multimodal
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library_name: transformers
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base_model:
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- Qwen/Qwen2-VL-2B
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---
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# G2VLM-2B-MoT
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## Geometry Grounded Vision Language Model with Unified 3D Reconstruction and Spatial Reasoning
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<p align="left">
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<img src="https://huggingface.co/InternRobotics/G2VLM-2B-MoT/resolve/main/assets/icon.png" alt="G2VLM" width="200"/>
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</p>
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<p align="left">
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<a href="https://gordonhu608.github.io/g2vlm.github.io/">
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<img
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src="https://img.shields.io/badge/G2VLM-Website-0A66C2?logo=safari&logoColor=white" style="display: inline-block; vertical-align: middle;"
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alt="G2VLM Website"
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/>
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</a>
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<a href="https://arxiv.org/abs/2511.21688">
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<img
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src="https://img.shields.io/badge/G2VLM-Paper-red?logo=arxiv&logoColor=red" style="display: inline-block; vertical-align: middle;"
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alt="G2VLM Paper on arXiv"
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/>
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</a>
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<a href="https://github.com/InternRobotics/G2VLM" target="_blank" style="margin: 2px;">
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<img
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alt="Github" src="https://img.shields.io/badge/G2VLM-Codebase-536af5?color=536af5&logo=github" style="display: inline-block; vertical-align: middle;"
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alt="G2VLM Codebase"
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/>
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</a>
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</p>
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> We present <b>G<sup>2</sup>VLM</b>, a geometry grounded vision-language model proficient in both spatial 3D reconstruction and spatial understanding tasks. For spatial reasoning questions, G<sup>2</sup>VLM can natively predict 3D geometry and employ interleaved reasoning for an answer.
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This repository hosts the model weights for <b>G<sup>2</sup>VLM</b>. For installation, usage instructions, and further documentation, please visit our [GitHub repository](https://github.com/InternRobotics/G2VLM).
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<p align="left"><img src="https://huggingface.co/InternRobotics/G2VLM-2B-MoT/resolve/main/assets/teaser.png" width="100%"></p>
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## 🧠 Method
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<i>G<sup>2</sup>VLM is a unified model that integrates both a geometric perception expert for 3D reconstruction and a semantic perception expert for multimodal understanding and spatial reasoning tasks. All tokens can do shared multi-modal self attention in each transformer block.
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<p align="left"><img src="https://huggingface.co/InternRobotics/G2VLM-2B-MoT/resolve/main/assets/method.png" width="100%"></p>
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## License
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G2VLM is licensed under the Apache 2.0 license.
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## ✍️ Citation
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```bibtex
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@article{hu2025g2vlmgeometrygroundedvision,
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title={G$^2$VLM: Geometry Grounded Vision Language Model with Unified 3D Reconstruction and Spatial Reasoning},
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author={Wenbo Hu and Jingli Lin and Yilin Long and Yunlong Ran and Lihan Jiang and Yifan Wang and Chenming Zhu and Runsen Xu and Tai Wang and Jiangmiao Pang},
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year={2025},
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eprint={2511.21688},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2511.21688},
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}
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``` |
