/cuopt-install

name: cuopt-install
version: "26.08.00"
description: Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
license: Apache-2.0
metadata:
  author: NVIDIA cuOpt Team
  tags:
    - cuopt
    - install
    - deployment
    - python
    - server

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

See [`references/verification_examples.md`](references/verification_examples.md) for the canonical C-API header/library `find` commands (conda and pip/venv variants).

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