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Cuopt Install Agent Skill

Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.

10k tokens
context cost
the whole folder, loaded on every use
7
files
instructions only
0
copies elsewhere
how many repositories repackaged it
999
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/NVIDIA/skills --skill cuopt-install

What comes with it

34 196 bytes besides the instruction
BENCHMARK.md
benchmark/evals.json
evals/evals.json
references/verification_examples.md
skill-card.md
skill.oms.sig

The instruction itself

18 sections, as written by the author

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:

  • Interface — Python, C, or REST server? Server can be called from any language via HTTP.
  • CUDA version — What is installed? Check with nvcc --version or nvidia-smi.
  • Package manager — pip, conda, or Docker preferred?
  • 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

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

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How to use it

Copy the folder

Take nvidia/cuopt-install from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip, docker. Without those the skill loads but fails at the first command.