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Official agent skill

Cuopt Install

by NVIDIA in NVIDIA/skills

Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install.

OfficialApache-2.0Auto-check passedDevOps & Cloud

Install Cuopt Install

skills CLI
$ npx skills add NVIDIA/skills --skill cuopt-install -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install NVIDIA/skills cuopt-install --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cuopt-install .claude/skills/cuopt-install && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cuopt-install
GitHub stars
3.5k
Token cost
~1.1k tokens
SKILL.md length
373 words
Files
7 (incl. references)
Skills in repo
380
Repo updated
First seen
Licence
Apache-2.0

At a glance

Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install.

  • Works in 4 steps: Interface — Python, C, or REST server?… → CUDA version — What is installed? Check… → Package manager — pip, conda, or Docker… → …
  • Tasks that involve Containers
  • SKILL.md covers System requirements, Required questions, Python API and C API, plus 3 more sections
  • Calls pip, conda and docker; reaches pypi.nvidia.com

What it does

Cuopt Install is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `BENCHMARK.md`, `benchmark/evals.json` and `evals/evals.json`).

It sits in DevOps & Cloud, covering Containers. It works with Python, Docker, CUDA and NVIDIA AI Platform. The repository describes itself as: Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Containers

Example prompts

  • “/cuopt-install”

Requirements

  • Python 3
  • Docker

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  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)?

What it can do on your machine

Read from SKILL.md and the folder at commit 67a13c0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pip
    • conda
    • docker
    • python
    • curl
    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • pypi.nvidia.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cuopt Install loads about 1.1k tokens when it runs, and up to ~2.1k if it reads all its reference files. Until then it costs about 38 tokens; SKILL.md has 373 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~38
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from NVIDIA/skills at commit 67a13c0, republished under its Apache-2.0 licence (© NVIDIA). 373 words, ~1,051 tokens.

Download SKILL.mdSave it as .claude/skills/cuopt-install/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
cuopt-install
description
Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
version
26.10.00
license
Apache-2.0
metadata.author
NVIDIA cuOpt Team
metadata.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:
    bash
    pip install --extra-index-url=https://pypi.nvidia.com cuopt-cu13
  • CUDA 12.x:
    bash
    pip install --extra-index-url=https://pypi.nvidia.com 'cuopt-cu12==26.2.*'
conda
bash
conda install -c rapidsai -c conda-forge -c nvidia cuopt
Verify
python
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.

Show full SKILL.md (136 more words)Show less
pip
  • CUDA 13.x:
    bash
    pip install --extra-index-url=https://pypi.nvidia.com libcuopt-cu13
  • CUDA 12.x:
    bash
    pip install --extra-index-url=https://pypi.nvidia.com 'libcuopt-cu12==26.2.*'
conda
bash
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
bash
pip install --extra-index-url=https://pypi.nvidia.com cuopt-server-cu12 cuopt-sh-client
conda
bash
conda install -c rapidsai -c conda-forge -c nvidia cuopt-server cuopt-sh-client
Docker
bash
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
bash
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.

© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (references) in skills/cuopt-install of NVIDIA/skills.

  • SKILL.md
  • BENCHMARK.md
  • benchmark/evals.json
  • evals/evals.json
  • references/verification_examples.md
  • skill-card.md
  • skill.oms.sig

Open the folder on GitHubat commit 67a13c0

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Migrate Workflow Ec2 To Osdcpytorch/test-infra113—~2kAutomated safety check: PassCustom licence
Vllm Deploy Dockervllm-project/vllm-skills103—~2.5kAutomated safety check: NotesApache-2.0

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Works with

Categories

Questions about Cuopt Install

What does Cuopt Install do?

Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. Cuopt Install is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install.

When should I use Cuopt Install?

Cuopt Install fits situations like: tasks that involve Containers.

How do I install Cuopt Install in Claude Code?

Run `npx skills add NVIDIA/skills --skill cuopt-install -a claude-code`. Or copy the skill folder (skills/cuopt-install in NVIDIA/skills) into .claude/skills/cuopt-install in your project. Claude Code loads it when a task matches its description.

How do I install Cuopt Install in Codex?

Run `npx skills add NVIDIA/skills --skill cuopt-install -a codex`. Or copy the skill folder (skills/cuopt-install in NVIDIA/skills) into .agents/skills/cuopt-install in your project. Codex loads it when a task matches its description.

Can I use Cuopt Install in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill cuopt-install -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cuopt-install, .gemini/skills/cuopt-install, .github/skills/cuopt-install and .opencode/skills/cuopt-install in your project.

What does Cuopt Install need to run?

Going by SKILL.md and its folder, Cuopt Install needs the command-line tools its instructions call (pip, conda, docker, python, curl and jq). Our summary lists: Python 3; Docker.

Does Cuopt Install access the network?

SKILL.md names 1 domain. In commands or code: pypi.nvidia.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Cuopt Install safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Cuopt Install use?

Cuopt Install is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cuopt Install use?

About 1.1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.1k tokens, read only when the agent opens those files.

What are the alternatives to Cuopt Install?

Skills that share tags, products or a category with Cuopt Install: Cosmos3 Env Troubleshoot (NVIDIA/cosmos-framework, 558 stars), Generate Nemo Gym Env (adithya-s-k/FineEnvs, 443 stars), Init GPU Server (drawthingsai/draw-things-community, 580 stars) and Migrate Workflow Ec2 To Osdc (pytorch/test-infra, 113 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cuopt Install?

NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,539 GitHub stars. The repository holds 380 skills in this directory. The repository was last updated on October 7, 2026.

Source: NVIDIA/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.