Install cuOpt to use it from Python. Standalone skill (no separate common).
System requirements
- GPU: NVIDIA Compute Capability ≥ 7.0 (Volta+). CUDA 12.x or 13.x; match package (cuopt-cu12 / cuopt-cu13).
- Driver: Compatible NVIDIA driver.
pip (Python)
Choose one — do not run both. The second install would override the first and can cause CUDA/package mismatch.
- CUDA 13.x:
pip install --extra-index-url=https://pypi.nvidia.com cuopt-cu13 - CUDA 12.x:
pip install --extra-index-url=https://pypi.nvidia.com 'cuopt-cu12==26.2.*'
pip: Server + Client
pip install --extra-index-url=https://pypi.nvidia.com cuopt-server-cu12 cuopt-sh-client
conda
conda install -c rapidsai -c conda-forge -c nvidia cuopt
conda install -c rapidsai -c conda-forge -c nvidia cuopt-server cuopt-sh-client
Docker
docker pull nvidia/cuopt:latest-cuda12.9-py3.13
docker run --gpus all -it --rm -p 8000:8000 nvidia/cuopt:latest-cuda12.9-py3.13
Verify Python
import cuopt
print(cuopt.__version__)
from cuopt import routing
dm = routing.DataModel(n_locations=3, n_fleet=1, n_orders=2)
Verify Server
python -m cuopt_server.cuopt_service --ip 0.0.0.0 --port 8000 &
sleep 5
curl -s http://localhost:8000/cuopt/health | jq .
Common Issues
- No module 'cuopt' → check
pip list | grep cuopt,which python, reinstall with correct index. - CUDA not available →
nvidia-smi,nvcc --version, match cuopt-cu12 vs cuopt-cu13 to CUDA.
Examples
- verification_examples.md — Python and server verification