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Zihan1004/CADWorld
CADWorld is a machine learning model from Zihan1004. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
CADWorld is a computer-use benchmark for FreeCAD tasks. Agents interact with a prebuilt Ubuntu VM through screenshots and pyautogui actions, and CADWorld evaluates the saved FreeCAD result file on the host.
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Updated Jul 3, 2026
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From the Hugging Face model README
CADWorld is a computer-use benchmark for FreeCAD tasks. Agents interact with a prebuilt Ubuntu VM through screenshots and pyautogui actions, and CADWorld evaluates the saved FreeCAD result file on the host.
GitHub hosts the runnable CADWorld benchmark code, task examples, evaluators, baseline scripts, documentation, and issue tracker.
Hugging Face hosts heavyweight artifacts that should not live in GitHub, starting with the prebuilt FreeCAD Ubuntu VM image:
vm_data/FreeCAD-Ubuntu.qcow2
The benchmark downloads this image automatically when it is missing:
uv run python scripts/python/download_vm_image.py
or during a benchmark run unless --no-download_vm is passed.
The hook animation above is the project-level quick visual summary: CADWorld turns FreeCAD GUI work into reproducible computer-use tasks, records the agent trajectory, saves the CAD artifact, and evaluates the result outside the VM.
Use GitHub for new task contributions, evaluator fixes, model adapter improvements, reproducibility notes, and benchmark result discussions. Use this Hugging Face repository for VM image downloads, large release artifacts, and project-facing artifact metadata.
git clone https://github.com/Zdong104/CADWORLD.git
cd CADWORLD
uv sync --python 3.12
uv run python scripts/python/download_vm_image.py
uv run python scripts/python/run_cadworld.py \
--test_all_meta_path evaluation_examples/test_easy.json \
--agent api \
--api_provider gemini \
--model_name gemini-3-flash-preview \
--max_steps 3 \
--no-skip_finished
See the GitHub README for full installation, API provider configuration, local model evaluation, and contribution details.