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Web-Bench is a benchmark designed to evaluate the performance of LLMs in actual Web development.
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| 2026-07-31 | 286 |
| 2026-08-06 | 286 |
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# Web-Bench
<p align="center">
<a href="./README.zh_CN.md">中文</a> •
<a href="#-installation">Install</a> •
<a href="https://arxiv.org/abs/2505.07473">Paper</a> •
<a href="https://huggingface.co/datasets/bytedance-research/Web-Bench">Datasets</a> •
<a href="https://huggingface.co/spaces/bytedance-research/Web-Bench-Leaderboard">LeaderBoard</a> •
<a href="#-citation">Citation</a>
</p>
## 📖 Overview
**Web-Bench** is a benchmark designed to evaluate the performance of LLMs in actual Web development. Web-Bench contains 50 projects, each consisting of 20 tasks with sequential dependencies. The tasks implement project features in sequence, simulating real-world human development workflows. When designing Web-Bench, we aim to cover the foundational elements of Web development: Web Standards and Web Frameworks. Given the scale and complexity of these projects, which were designed by engineers with 5-10 years of experience, each presents a significant challenge. On average, a single project takes 4–8 hours for a senior engineer to complete. On our given benchmark agent (Web-Agent), SOTA (Claude 3.7 Sonnet) achieves only 25.1\% Pass@1.
The distribution of the experimental data aligns well with the current code generation capabilities of mainstream LLMs.
<img width="500" alt="pass@1" src="./docs/assets/pass-1.png" />
HumanEval and MBPP have approached saturation. APPS and EvalPlus are approaching saturation. The SOTA for Web-Bench is 25.1\%, which is lower (better) than that of the SWE-bench Full and Verified sets.
<img width="500" alt="SOTAs" src="./docs/assets/sotas.png" />
## 🚀 Quick Start
Refer to the [Docker setup guide](https://docs.docker.com/engine/install/) for instructions on installing Docker on your machine
1. Create a new empty folder, add **two files** in this folder:
```
./config.json5
./docker-compose.yml
```
2. For `config.json5`, copy the json below and edit by [Config Parameters](https://github.com/bytedance/web-bench/wiki/Config-Parameters):
```json5
{
models: [
'openai/gpt-4o',
// You can add more models here
// "claude-sonnet-4-20250514"
],
// Eval one project only
// "projects": ["@web-bench/react"]
}
```
3. For `docker-compose.yml`, copy the yaml below and **set environment**
```yaml
services:
web-bench:
image: maoyiweiebay777/web-bench:latest
volumes:
- ./config.json5:/app/apps/eval/src/config.json5
- ./report:/app/apps/eval/report
environment:
# Add enviorment variables according to apps/src/model.json
- OPENROUTER_API_KEY=your_api_key
# Add more model's key
# - ANTHROPIC_API_KEY=your_api_key
```
4. Run docker-compose:
```bash
docker compose up
```
5. Evaluation Report will be generated under `./report/`
If you wish to evaluate from source code, refer to [Install from source](https://github.com/bytedance/web-bench/wiki/Installation).
## **🛠️** Contribution
- [Project Contribution](https://github.com/bytedance/web-bench/wiki/Project-Contribution)
## **📚** Citation
```bibtex
@article{xu2025webbench,
title={Web-Bench: A LLM Code Benchmark Based on Web Standards and Frameworks},
author={Xu, Kai and Mao, YiWei and Guan, XinYi and Feng, ZiLong},
journal={arXiv preprint arXiv:2505.07473},
year={2025}
}
```
## **📄** License
[Apache 2.0](./LICENSE.md)
## **🌟** Contact us
- Lark: Scan the QR code below with [Register Feishu](https://www.feishu.cn/en/) to join our Web Bench user group.
<img width="300" alt="pass@1" src="./docs/assets/lark-group-qr-code.png" />
- [Discord](https://discord.gg/Mhs4yEyD)
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