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README.md

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+---
+language:
+- en
+pretty_name: WebHarbor-4B
+library_name: sglang
+pipeline_tag: image-text-to-text
+base_model: OpenWebRL/OpenWebRL-4B-SFT
+datasets:
+- ChilleD/WebHarbor
+tags:
+- webharbor
+- web-agent
+- gui-agent
+- computer-use-agents
+- reinforcement-learning
+- qwen3-vl
+---
+
+<h1 align="center">WebHarbor: Docking Real Websites for Evolving GUI Agent Environments</h1>
+
+<h2 align="center">WebHarbor-4B Model</h2>
+
+<p align="center">
+  <a href="https://aiming-lab.github.io/WebHarbor/"><img src="https://img.shields.io/badge/Project-Page-0A7EA4.svg" alt="Project Page"></a>
+  <a href="https://github.com/aiming-lab/WebHarbor"><img src="https://img.shields.io/badge/Code-GitHub-181717.svg" alt="Code"></a>
+  <a href="https://huggingface.co/datasets/ChilleD/WebHarbor"><img src="https://img.shields.io/badge/🤗-153_Environments-yellow.svg" alt="153 Environments"></a>
+  <a href="https://hub.docker.com/r/wildawm/webharbor"><img src="https://img.shields.io/badge/Docker-wildawm%2Fwebharbor-2496ED.svg" alt="Docker Images"></a>
+</p>
+
+<p align="left">
+  <b>WebHarbor-4B</b> is a GUI web agent trained with reinforcement learning entirely inside <a href="https://aiming-lab.github.io/WebHarbor/">WebHarbor</a>, 153 executable reconstructions of real websites with logins, carts, bookings and 3,518 tasks. It never touches the live web during RL training, yet it transfers there: it reaches a <b>75.8</b> average on WebVoyager and Online-Mind2Web, the best among the open-source web agents compared. The model is a 4B <a href="https://huggingface.co/Qwen/Qwen3-VL-4B-Thinking">Qwen3-VL</a> policy that starts from OpenWebRL-4B-SFT and acts through the <a href="https://github.com/OpenWebRL/OpenWebRL">OpenWebRL</a> browser interface.
+</p>
+
+---
+
+## 🔮 Resources
+
+| Resource | Link |
+|---|---|
+| 🌐 Project page | [WebHarbor](https://aiming-lab.github.io/WebHarbor/) |
+| 💻 Code (environments, evaluation) | [WebHarbor repository](https://github.com/aiming-lab/WebHarbor) |
+| 📦 Environments | [ChilleD/WebHarbor](https://huggingface.co/datasets/ChilleD/WebHarbor) |
+| 🐳 Docker images | [wildawm/webharbor](https://hub.docker.com/r/wildawm/webharbor) |
+| 🤖 WebHarbor-4B | [ChilleD/WebHarbor-4B](https://huggingface.co/ChilleD/WebHarbor-4B) |
+
+## ✨ Highlights
+
+| Benchmark | OpenWebRL-4B-SFT | OpenWebRL-4B | **WebHarbor-4B** |
+|---|:---:|:---:|:---:|
+| WebVoyager | 60.2 | 74.1 | **81.2** |
+| Online-Mind2Web | 47.0 | 67.0 | **70.4** |
+| WebArena | 26.1 | 20.4 | **28.8** |
+| WebArena without auto-login | 21.2 | 16.8 | **26.1** |
+| WebHarbor test set | 29.1 | 19.7 | **30.0** |
+
+- **Live web from offline training:** a 75.8 average on WebVoyager and Online-Mind2Web, ahead of GPT-5 (74.2) and every listed open-source agent.
+- **Strongest on real-world workflows:** the largest gains are on logins, multi-page navigation, stateful operations and transactions, the workflows that live-web training rarely covers.
+- **Unseen sites and tasks:** all 15 WebVoyager websites are held out of training, and Online-Mind2Web and WebArena tasks are not in the training data.
+
+## 📦 Setup
+
+```bash
+uv pip install "sglang==0.5.6.post2"
+```
+
+## 🔥 Serving
+
+A single-GPU launch with the 32K context used in our evaluation:
+
+```bash
+python -m sglang.launch_server \
+  --model-path ChilleD/WebHarbor-4B \
+  --served-model-name webharbor-4b \
+  --host 0.0.0.0 --port 30000 \
+  --dtype bfloat16 \
+  --context-length 32768 \
+  --mem-fraction-static 0.9 \
+  --trust-remote-code \
+  --attention-backend flashinfer \
+  --mm-attention-backend triton_attn
+```
+
+This exposes an OpenAI-compatible Chat Completions endpoint at `http://localhost:30000/v1`. The chat template already opens the `<think>` block, so clients should not add their own. For the browser harness and to evaluate on WebHarbor, see the [WebHarbor repository](https://github.com/aiming-lab/WebHarbor).
+
+## Citation
+
+If you find this work useful, please cite:
+
+```bibtex
+@misc{webharbor2026,
+  title        = {WebHarbor: Docking Real Websites for Evolving GUI Agent Environments},
+  author       = {{WebHarbor Team and Contributors}},
+  year         = {2026},
+  url          = {https://aiming-lab.github.io/webharbor.github.io},
+  note         = {Project website.}
+}
+```