Model reference · open weights
GELab-Zero is an open-weight language model from stepfun-ai. GELab-Zero-4B-preview (BF16) weighs 8.9 GB; the smallest configuration that runs it is RTX 4060 Ti 16 GB.
Summary of the stepfun-ai/GELab-Zero-4B-preview model card, 2026-10-01
What it is
| Released by | stepfun-ai |
|---|---|
| Released | 2025-11-28 |
| Parameters | 4.4B |
| VRAM | 8.9 GB for the weights |
What it runs on
| Card | Requests at once | Context max | Memory | |
|---|---|---|---|---|
| 8K each | 32K each | |||
| RTX 3060 12 GB | — | — | 4K | 11.6 GB |
| RTX 4060 Ti 16 GB | 3 | — | 30K | 15.4 GB |
| RTX 3090 24 GB | 10 | 2 | 82K | 23.4 GB |
| RTX 4090 24 GB | 10 | 2 | 82K | 23.4 GB |
| RTX 5090 32 GB | 16 | 4 | 133K | 31.0 GB |
| L40S 48 GB | 27 | 6 | 219K | 44.0 GB |
| A100 80 GB | 55 | 13 | all 256K | 78.2 GB |
| H100 80 GB | 52 | 13 | all 256K | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | 65 | 16 | all 256K | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | 76 | 19 | all 256K | 107 GB |
| H200 141 GB | 101 | 25 | all 256K | 138 GB |
| B200 180 GB | 132 | 33 | all 256K | 176 GB |
| 2× RTX 3060 12 GB tensor parallel | 8 | 2 | 68K | 11.6 GB a card |
| 2× RTX 4060 Ti 16 GB tensor parallel | 14 | 3 | 118K | 15.4 GB a card |
| Requests at once | 8K tokens each | 32K tokens each |
|---|---|---|
| 1 | 12.1 GB | 15.7 GB |
| 5 | 16.9 GB | 35.0 GB |
| 8 | 20.5 GB | 49.5 GB |
| 16 | 30.2 GB | 88.2 GB |
| 32 | 49.5 GB | 165 GB |
| 64 | 88.2 GB | 320 GB |
One card, with vLLM's small-card settings.
From the model card
This model is part of the GELab-Zero project, which presents the Step-GUI Technical Report [Paper] [Project Page] [Code].
This model is part of the GELab-Zero project, which aims to accelerate the innovation and application deployment of GUI Agents by providing:
The easiest way to run inference is using Ollama.
1.Install Ollama: Download from ollama.com.
2.Download the Model:
# Install huggingface-cli
pip install huggingface_hub
# Download model
huggingface-cli download --resume-download stepfun-ai/GELab-Zero-4B-preview --local-dir gelab-zero-4b-preview
3.Create and Run in Ollama:
cd gelab-zero-4b-preview
ollama create gelab-zero-4b-preview -f Modelfile
# Test the model
curl -X POST http://localhost:11434/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "gelab-zero-4b-preview",
"messages": [{"role": "user", "content": "Hello, GELab-Zero!"}]
}'
To use this model for actual Android device control (ADB connection, task execution), please use the GELab-Zero.
If you find GELab-Zero-4B-preview useful for your research, please consider citing our work :)
@misc{yan2025stepguitechnicalreport,
title={Step-GUI Technical Report},
author={Haolong Yan and Jia Wang and Xin Huang and Yeqing Shen and Ziyang Meng and Zhimin Fan and Kaijun Tan and Jin Gao and Lieyu Shi and Mi Yang and Shiliang Yang and Zhirui Wang and Brian Li and Kang An and Chenyang Li and Lei Lei and Mengmeng Duan and Danxun Liang and Guodong Liu and Hang Cheng and Hao Wu and Jie Dong and Junhao Huang and Mei Chen and Renjie Yu and Shunshan Li and Xu Zhou and Yiting Dai and Yineng Deng and Yingdan Liang and Zelin Chen and Wen Sun and Chengxu Yan and Chunqin Xu and Dong Li and Fengqiong Xiao and Guanghao Fan and Guopeng Li and Guozhen Peng and Hongbing Li and Hang Li and Hongming Chen and Jingjing Xie and Jianyong Li and Jingyang Zhang and Jiaju Ren and Jiayu Yuan and Jianpeng Yin and Kai Cao and Liang Zhao and Liguo Tan and Liying Shi and Mengqiang Ren and Min Xu and Manjiao Liu and Mao Luo and Mingxin Wan and Na Wang and Nan Wu and Ning Wang and Peiyao Ma and Qingzhou Zhang and Qiao Wang and Qinlin Zeng and Qiong Gao and Qiongyao Li and Shangwu Zhong and Shuli Gao and Shaofan Liu and Shisi Gao and Shuang Luo and Xingbin Liu and Xiaojia Liu and Xiaojie Hou and Xin Liu and Xuanti Feng and Xuedan Cai and Xuan Wen and Xianwei Zhu and Xin Liang and Xin Liu and Xin Zhou and Yingxiu Zhao and Yukang Shi and Yunfang Xu and Yuqing Zeng and Yixun Zhang and Zejia Weng and Zhonghao Yan and Zhiguo Huang and Zhuoyu Wang and Zheng Ge and Jing Li and Yibo Zhu and Binxing Jiao and Xiangyu Zhang and Daxin Jiang},
year={2025},
eprint={2512.15431},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2512.15431},
}
@software{gelab_zero_2025,
title={GELab-Zero: An Advanced Mobile Agent Inference System},
author={GELab Team},
year={2025},
url={https://github.com/stepfun-ai/gelab-zero}
}
@misc{gelab_engine,
title={GUI Exploration Lab: Enhancing Screen Navigation in Agents via Multi-Turn Reinforcement Learning},
author={Haolong Yan and Yeqing Shen and Xin Huang and Jia Wang and Kaijun Tan and Zhixuan Liang and Hongxin Li and Zheng Ge and Osamu Yoshie and Si Li and Xiangyu Zhang and Daxin Jiang},
year={2025},
eprint={2512.02423},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2512.02423},
}
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.