Agent skill · software engineering · 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.
Why this skill is useful
Provides specific installation commands and verification steps for cuOpt that are not widely known or documented.
What it needs
Requires conda, docker, pip installed locally. About 2k tokens when loaded. Last updated 2026-08-07. 2,816 stars on the source repository.
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