---
id: nvidia-cuda-cccl-cu12
version: "12.9.27"
license: NVIDIA Proprietary Software
license_treatment: unclear
maintenance: aging
---

# nvidia-cuda-cccl-cu12 — CUDA CCCL

License: unclear · Maintenance: aging · Downloads: 627.6K/mo

## What it is and what it does

This package distributes NVIDIA's CUDA C++ Core Compute Libraries (CCCL) as a Python wheel for CUDA 12 environments. It serves as a low-level runtime component for GPU-accelerated computing, typically used as a dependency by higher-level frameworks rather than directly by end users. The package supports Python 3.5 through 3.11 across Linux (x86_64 and aarch64) and Windows (x86_64) platforms.

The package carries medium install friction due to platform-specific wheel distributions and requires a CUDA 12-capable GPU and matching CUDA toolkit. Its aging maintenance status—no releases for 470 days—suggests it may be in a stable maintenance phase rather than active development. The proprietary NVIDIA license requires explicit verification before use in commercial or redistributed contexts.

Use it for:

- As a dependency for CUDA-accelerated machine learning frameworks that require low-level compute library access.
- Building custom GPU-accelerated C++ applications that need CCCL bindings through Python.
- Scientific computing pipelines that rely on NVIDIA's optimized parallel compute primitives.
- Deep learning research environments where CUDA 12 toolkit components are required.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides NVIDIA's CUDA C++ Core Compute Libraries (CCCL) for GPU-accelerated computing on CUDA 12 platforms.

Yes, if you are building or using CUDA 12-based GPU applications and this package is listed as a dependency. No, if you are looking for a standalone Python library—this is a runtime component distribution. Verify NVIDIA's proprietary license terms before deployment. The aging maintenance status is not a blocker for stable, mature CUDA 12 environments but may indicate limited future updates.

## Install

pip install nvidia-cuda-cccl-cu12
uv add nvidia-cuda-cccl-cu12
poetry add nvidia-cuda-cccl-cu12

## Installing nvidia-cuda-cccl-cu12

Before you install: Medium install friction due to platform-specific wheel distributions (Linux x86_64, Linux aarch64, Windows x86_64). Package is aging—last release was 470 days ago—which may indicate slower maintenance cadence relative to active CUDA development.

License in practice: Licensed under NVIDIA Proprietary Software with unclear treatment. Users should verify licensing terms directly with NVIDIA before deployment, particularly for commercial or redistributed applications.

Quickstart:

pip install nvidia-cuda-cccl-cu12==12.9.27

# Import and use within CUDA-enabled Python code
import nvidia.cuda.cccl

Requires a CUDA 12-capable NVIDIA GPU and matching CUDA toolkit installation; only available for Linux (x86_64, aarch64) and Windows (x86_64).

Verify before relying:

- Whether this package is intended for direct Python import or is primarily a dependency for other CUDA libraries.
- Specific API surface and typical usage patterns within CUDA applications.
- Support status and maintenance roadmap beyond the 470-day gap since last release.

## Package facts

- License: NVIDIA Proprietary Software (unclear)
- Python support: supports_current
- Install friction: medium
- Maintenance: aging
- Downloads: 627.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

cuda c++ core compute libraries, nvidia cccl gpu acceleration, cuda 12 runtime libraries, gpu parallel computing libraries, nvidia cuda toolkit components, gpu-computing, cuda-runtime, nvidia

[View on SkillFed](https://skillfed.io/packages/nvidia-cuda-cccl-cu12) · [View on PyPI](https://pypi.org/project/nvidia-cuda-cccl-cu12/)