# Text2CAD-Bench 🏭

[![Version](https://img.shields.io/badge/version-v1.0-blue.svg)](https://github.com/xxx/Text2CAD-Bench)
[![License](https://img.shields.io/badge/license-CC%20BY%204.0-green.svg)](https://creativecommons.org/licenses/by/4.0/)

**Text2CAD-Bench** is the first comprehensive benchmark for evaluating text-to-CAD generation across geometric complexity and application diversity.


</p>

## 📢 News

- **[2026.02]** 🎉 v1.0 released with 30% prompts for preview
- **[Coming Soon]** v1.1 will include additional evaluation scripts and expanded documentation

## 📖 Overview

Text2CAD-Bench comprises **600 human-curated examples** organized into four benchmark levels:

| Level | Description | Examples | Key Features |
|-------|-------------|----------|--------------|
| **L1** | Basic | 200 | Primitives, simple spatial relationships |
| **L2** | Intermediate | 200 | Boolean operations, chamfer, fillet, patterns |
| **L3** | Advanced | 100 | Sweep, loft, shell, complex surfaces |
| **L4** | Real-world | 100 | Multi-domain applications |

Each example includes **dual-style prompts**:
- **Geometric (Geo)**: Appearance-based descriptions mimicking non-expert users
- **Sequence (Seq)**: Procedural descriptions aligned with expert-level CAD conventions

## 📁 Dataset Structure

```
Text2CAD-Bench/
├── prompts/                    # 30% sample prompts (preview)
│   ├── L1/
│   │   ├── L1_001_geo
│   │   ├── L1_001_seq
│   │   └── ...
│   ├── L2/
│   ├── L3/
│   └── L4/
├── evaluation/                 # Evaluation scripts
│   ├── metrics.py
│   ├── evaluate.py
│   └── requirements.txt
├── examples/                   # Example outputs
│   └── visualizations/
└── README.md
```

> ⚠️ **Note**: Ground truth STEP files are not publicly released to prevent benchmark contamination. The 30% prompt samples are provided to demonstrate data distribution and format. For full benchmark access, please contact us.

## 🏆 Leaderboard

> 📊 **Interactive Leaderboard**: See [leaderboard](leaderboard.html) for sortable results by different metrics.

Final results are **weighted by sample count**: L1 (200, 40%), L2 (200, 40%), L3 (100, 20%).

### General-purpose LLMs (Sorted by CD ↓)

| Rank | Model | CD ↓ | IR ↓ | IoU ↑ | 
|:----:|-------|-----:|-----:|------:|
| 🥇 | GPT-5.2 | **63.97** | 30.6% | **0.45** |
| 🥈 | Claude-4.5-Sonnet | 66.90 | 41.3% | 0.43 |
| 🥉 | DeepSeek-V3.2 | 76.25 | **29.7%** | 0.37 |
| 4 | MiniMax M2.11 | 83.16 | 42.7% | 0.37 |
| 5 | GLM-4.7 | 84.98 | 35.0% | 0.34 |
| 6 | Qwen3-max | 99.21 | 43.2% | 0.28 |

### Domain-specific Models (Sorted by CD ↓)

| Rank | Model | CD ↓ | IR ↓ | IoU ↑ |
|:----:|-------|-----:|-----:|------:|
| 🥇 | CADFusion | **224.35** | 60.5% | 0.03 |
| 🥈 | Text2CAD | 248.66 | **7.0%** | 0.05 |
| 🥉 | Text2CADQuery | 250.27 | 51.0% | 0.04 |



</details>

## 🚀 Quick Start

### Installation

```bash
git clone https://github.com/xxx/Text2CAD-Bench.git
cd Text2CAD-Bench
pip install -r evaluation/requirements.txt
```

### Evaluation

```python
from evaluation import evaluate

# Load your model outputs
results = evaluate(
    predictions_dir="path/to/your/outputs",
    metrics=["CD", "IR", "IoU"]
)

print(results.summary())
```

### Submit to Leaderboard

To submit your results to the leaderboard:

1. Run evaluation on the full benchmark by upload your model.
2. Generate results file using our evaluation script
3. Submit via [Google Form](https://forms.google.com/xxx) or email

```bash
python evaluation/generate_submission.py \
    --predictions_dir path/to/outputs \
    --output submission.json
```


## 📜 License

This work is licensed under a [Creative Commons Attribution 4.0 International License (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/).

You are free to:
- **Share** — copy and redistribute the material in any medium or format
- **Adapt** — remix, transform, and build upon the material for any purpose, even commercially

Under the following terms:
- **Attribution** — You must give appropriate credit, provide a link to the license, and indicate if changes were made.

## 📧 Contact

- **Email**:
- **Issues**: Please use GitHub Issues for bug reports and feature requests
- **Full benchmark access**: Contact us with your affiliation and intended use

## 🙏 Acknowledgements

We thank all annotators and reviewers who contributed to the construction of Text2CAD-Bench.

---

<p align="center">
  <i>Text2CAD-Bench: A Benchmark for LLM-based Text-to-Parametric CAD Generation</i>
</p>