Agent skill · NVIDIA
cuopt-install
Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
What it needs
About 2k tokens when loaded.
What this skill does
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: CUDA 12.x: conda Verify 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: CUDA 12.x: conda Verify See references/verificationexamples.md for the canonical C-API header/library find commands (conda and pip/venv variants). Server (REST) pip conda Docker Verify 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. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/cuopt-install