---
title: webrl-glm-4-9b
canonical_url: "https://www.modelscope.cn/models/ZhipuAI/webrl-glm-4-9b"
md_url: "https://www.modelscope.cn/models/ZhipuAI/webrl-glm-4-9b.md"
repository: ZhipuAI/webrl-glm-4-9b
last_updated: 2026-01-20
license: other
model_type:
  - chatglm
architectures:
  - ChatGLMForConditionalGeneration
base_model:
  - THUDM/glm-4-9b
base_model_relation: finetune
parameters: 9.4B
tensor_type:
  - BF16
library_name:
  - safetensors
  - pytorch
frameworks:
  - pytorch
language:
  - en
inference_backends:
  - "deploy_task text/emb"
  - "lmdeploy_turbomind 0.9.1"
  - "vllm 0.9.2"
downloads: 97
stars: 0
tags:
  - webrl
  - glm
  - webarena-lite
  - llm
  - agent
---

# webrl-glm-4-9b

> webrl-glm-4-9b - ZhipuAI 在 ModelScope 开源的模型。Model Introduction WebRL-GLM-4-9B is the open-source version of WebRL in GLM-4-9B released by Zhipu AI. It has the ability to complete web operations on five websites in WebArena: OpenStreetMap (Map), Reddit,…

ZhipuAI/webrl-glm-4-9b 是 ModelScope 魔搭社区上的 9.4B 参数机器学习模型，采用 other 许可，基于 THUDM/glm-4-9b 构建，可用 deploy_task text/emb、lmdeploy_turbomind 0.9.1、vllm 0.9.2 部署。

- **Repository**: ZhipuAI/webrl-glm-4-9b
- **License**: other
- **Parameters**: 9.4B
- **Base model**: THUDM/glm-4-9b
- **Inference backends**: deploy_task text/emb, lmdeploy_turbomind 0.9.1, vllm 0.9.2
- **Tags**: webrl, glm, webarena-lite, llm, agent
- **Downloads**: 97
- **Stars**: 0
- **Last updated**: 2026-01-20

Source: https://www.modelscope.cn/models/ZhipuAI/webrl-glm-4-9b

---

# WebRL-GLM-4-9B

## Model Introduction
WebRL-GLM-4-9B is the open-source version of WebRL in GLM-4-9B released by Zhipu AI.
It has the ability to complete web operations on five websites in WebArena: OpenStreetMap (Map), Reddit, GitLab, online store content management system (CMS) and OneStopShop (OSS).

## Evaluation Results

We evaluated the WebRL-GLM-4-9B model on WebArena-Lite and obtained the following results:

| Model               | Reddit | Gitlab | CMS | Map | OSS | Avg.SR  |
|:--------------------|:------:|:------:|:------:|:------:|:------:|:--------:|
| Llama-3.1-8B-Instruct |     0.0      |   3.3   | 2.9  | 3.3 | 11.1 |  4.8  |
| GLM-4-9B-Chat       |     5.3     |   10.0  |  6.7 | 3.3  |  6.7  | 6.1   |
| WebRL-GLM-4-9B      |     57.9     |   50.0  |  48.6| 36.7 | 37.8  |  43.0 |

**For more inference code and requirements, please visit our [github page](GitHub - THUDM/WebRL).**

## Citations

If you find our work useful, please consider citing the following paper.

```
@artical{qi2024webrl,
      title={WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning}, 
      author={Zehan Qi and Xiao Liu and Iat Long Iong and Hanyu Lai and Xueqiao Sun and Xinyue Yang and Jiadai Sun and Yu Yang and Shuntian Yao and Tianjie Zhang and Wei Xu and Jie Tang and Yuxiao Dong},
      journal={arXiv preprint arXiv:2411.02337},
      year={2024},
}
```