cuopt-install

name	cuopt-install
version	26.08.00
description	Install cuOpt for Python, C, or as a server (pip, conda, Docker) — system requirements, install commands, and verification. Use when the user wants to install or verify cuOpt for any user-facing interface. For building cuOpt from source or contributing to cuOpt, see cuopt-developer.

cuOpt Install (user)

Install cuOpt to use it from Python, C, or as a REST server. For building cuOpt from source to contribute or modify it, see cuopt-developer.

System requirements

• GPU: NVIDIA Compute Capability ≥ 7.0 (Volta or newer). Examples: V100, A100, H100, RTX 20xx/30xx/40xx. Not supported: GTX 10xx (Pascal).
• CUDA: 12.x or 13.x. The package CUDA suffix must match the runtime CUDA (e.g. cuopt-cu12 / libcuopt-cu12 with CUDA 12).
• Driver: NVIDIA driver compatible with the CUDA version.
• cuopt-cuXX (Python) depends on libcuopt-cuXX (C), so installing the Python package also installs the C library and headers. Installing libcuopt-cuXX on its own does not install the Python API.

Required questions

Ask these if not already clear:

1. Interface — Python, C, or REST server? Server can be called from any language via HTTP.
2. CUDA version — What is installed? Check with nvcc --version or nvidia-smi.
3. Package manager — pip, conda, or Docker preferred?
4. Environment — Local machine with GPU, cloud instance, Docker/Kubernetes, or remote/server (no local GPU)?

Python API

Choose one — do not run both. The second install would override the first and can cause CUDA / package mismatch.

pip

• 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.*'
  

conda

conda install -c rapidsai -c conda-forge -c nvidia cuopt

Verify

import cuopt
print(cuopt.__version__)
from cuopt import routing
dm = routing.DataModel(n_locations=3, n_fleet=1, n_orders=2)

C API

The C API ships in libcuopt-cuXX, which is also pulled in as a dependency of cuopt-cuXX — so if you already installed the Python package, the C library and headers are already present. Install libcuopt standalone only when you want the C API without Python. Choose one of pip or conda — do not run both.

pip

• CUDA 13.x:

  pip install --extra-index-url=https://pypi.nvidia.com libcuopt-cu13
  

• CUDA 12.x:

  pip install --extra-index-url=https://pypi.nvidia.com 'libcuopt-cu12==26.2.*'
  

conda

conda install -c rapidsai -c conda-forge -c nvidia libcuopt

Verify

# conda:
find $CONDA_PREFIX -name "cuopt_c.h"
find $CONDA_PREFIX -name "libcuopt.so"

# pip (venv):
find "$(python -c 'import sys; print(sys.prefix)')" -name "cuopt_c.h"
find "$(python -c 'import sys; print(sys.prefix)')" -name "libcuopt.so"

Server (REST)

pip

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-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 -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 named 'cuopt' → check pip list | grep cuopt, which python, reinstall with the correct extra-index-url.
• CUDA not available → run nvidia-smi and nvcc --version; ensure the package CUDA suffix (cu12 vs cu13) matches the installed CUDA.
• Python vs C → cuopt-cuXX pulls in libcuopt-cuXX as a transitive dependency, so the C library (libcuopt.so) and headers (cuopt_c.h) are already available after installing the Python package. The reverse is not true: libcuopt-cuXX alone does not install the Python bindings.

See also

• verification_examples.md — full verification recipes for Python, C, server, and Docker.
• cuopt-developer — build cuOpt from source and contribute to the codebase.