# cuopt-install

Installs NVIDIA cuOpt for Python, C, or as a REST server via pip, conda, or Docker, then verifies the setup. Helpful when configuring GPU-accelerated routing environments.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 2500 installs · ★ 3735
- Author: NVIDIA cuOpt Team
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/NVIDIA/skills/tree/HEAD/skills/cuopt-install/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/cuopt-install

## What it does

The skill guides you through deploying NVIDIA cuOpt across different environments. It clarifies the target interface (Python, standalone C, or HTTP REST server), package manager (pip, conda, or Docker), and the exact CUDA version (12.x or 13.x). Matching the package suffix to the installed CUDA runtime is mandatory to prevent runtime mismatches. It also provides verification steps, such as checking Python imports, C headers, or pinging the `/cuopt/health` endpoint.

Hardware requirements are strict: an NVIDIA GPU with Compute Capability 7.0 or newer (Volta through modern architectures like V100, A100, H100, and RTX 20xx/30xx/40xx). Pascal-based cards like the GTX 10xx series are unsupported, which prevents running cuOpt on older GPUs. If you install the Python package `cuopt-cuXX`, it automatically pulls in the C library `libcuopt-cuXX`, while installing C alone will not provide Python bindings.

## Requirements
- Works with: Docker

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill cuopt-install -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/cuopt-install/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/cuopt-install/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill cuopt-install -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/cuopt-install/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill cuopt-install -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/cuopt-install/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install NVIDIA/skills cuopt-install
```

2. **Manually: put the files in place**
- File: `.github/skills/cuopt-install/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill cuopt-install -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/NVIDIA/skills --path skills/cuopt-install
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/cuopt-install/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill cuopt-install -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/NVIDIA/skills/tree/HEAD/skills/cuopt-install/SKILL.md

## When to use it
- select matching cuOpt install commands for pip, conda, or Docker
- align cuOpt packages with CUDA 12.x or 13.x runtimes
- deploy the cuOpt REST server locally or in a container
- verify Python imports, C headers, and the `/cuopt/health` endpoint

## Example prompts
- Help me install cuOpt for Python with CUDA 12 using pip
- How do I run the cuOpt REST server in Docker and verify it?
- Install the standalone libcuopt C library using conda for CUDA 13

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 8eed639813cf55ac.

BEGIN THIRD-PARTY FILE 8eed639813cf55ac
````text
---
name: cuopt-install
version: "26.10.00"
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:**
  ```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.

### 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`](references/verification_examples.md)
````
END THIRD-PARTY FILE 8eed639813cf55ac

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