---
license: apache-2.0
language:
- en
- zh
base_model: Qwen/Qwen3-VL-32B-Thinking
tags:
- gui-agent
- mobile
- multimodal
- distillation
- teacher-model
library_name: transformers
pipeline_tag: image-text-to-text
---

# Qwen3-VL-32B-Thinking-Mobile-Teacher

This is the **Mobile Teacher** model from the [UI-MOPD](https://elisspectre.github.io/UI-MOPD/) project — a platform-specific expert trained for mobile GUI interaction tasks.

## Model Description

Qwen3-VL-32B-Thinking-Mobile-Teacher is fine-tuned from [Qwen3-VL-32B-Thinking](https://huggingface.co/Qwen/Qwen3-VL-32B-Thinking) on mobile interaction trajectories from the **Uni-GUI** dataset. It serves as the mobile-platform teacher in the UI-MOPD multi-teacher on-policy distillation framework.

### Key Highlights

- **Base Model**: Qwen3-VL-32B-Thinking
- **Training Data**: Mobile subset of Uni-GUI (~160K interaction steps across ~11.5K trajectories)
- **Role**: Platform-specific teacher for mobile environments in the UI-MOPD distillation pipeline
- **MobileWorld Performance**: **16.2%** task success rate (vs. 9.4% base model)

## Training Details

This model is obtained in **Stage 1** of the UI-MOPD training pipeline:

1. **Stage 1 (This Model)**: Supervised fine-tuning of Qwen3-VL-32B-Thinking on mobile GUI interaction trajectories from Uni-GUI to produce a platform-specific mobile expert.
2. **Stage 2**: The mobile teacher (this model) and a desktop teacher jointly guide a shared 8B student policy via multi-teacher on-policy distillation with platform-conditioned routing.

## Performance

| Method | MobileWorld |
|--------|:-:|
| Qwen3-VL-32B-Thinking (base) | 9.4% |
| **Mobile Teacher (this model)** | **16.2%** |

## Intended Use

This model is designed to:
- Serve as a **teacher model** in the UI-MOPD distillation framework for training cross-platform GUI agents
- Be used as a standalone **mobile GUI agent** for executing mobile tasks (e.g., app navigation, settings control, messaging)

## How to Use

```python
from transformers import Qwen3VLForConditionalGeneration, AutoProcessor

model = Qwen3VLForConditionalGeneration.from_pretrained(
    "UI-MOPD/Qwen3-VL-32B-Thinking-Mobile-Teacher",
    torch_dtype="auto",
    device_map="auto",
)
processor = AutoProcessor.from_pretrained("UI-MOPD/Qwen3-VL-32B-Thinking-Mobile-Teacher")
```

## Citation

```bibtex
@misc{lian2026uimopdmultiplatformonpolicydistillation,
      title={UI-MOPD: Multi-Platform On-Policy Distillation for Continual GUI Agent Learning}, 
      author={Niu Lian and Alan Chen and Zhehao Yu and Chengzhen Duan and Fazhan Liu and Hui Liu and Pei Fu and Jian Luan and Yaowei Wang and Shu-Tao Xia and Jinpeng Wang},
      year={2026},
      eprint={2607.04425},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2607.04425}, 
}
```

## Related Resources

- **Project Page**: [https://elisspectre.github.io/UI-MOPD/](https://elisspectre.github.io/UI-MOPD/)
- **Code**: [https://github.com/EliSpectre/UI-MOPD](https://github.com/EliSpectre/UI-MOPD)
- **Paper**: [UI-MOPD (arXiv)](https://arxiv.org/abs/2607.04425)
- **Desktop Teacher**: [UI-MOPD/Qwen3-VL-32B-Thinking-Desktop-Teacher](https://huggingface.co/UI-MOPD/Qwen3-VL-32B-Thinking-Desktop-Teacher)
- **Student Model**: [UI-MOPD/Qwen3-VL-8B-Thinking-UI-MOPD-Student](https://huggingface.co/UI-MOPD/Qwen3-VL-8B-Thinking-UI-MOPD-Student)