nvidia-cuda-cccl
CUDA CCCL
Decision gist · record as of 2026-08-14
Yes, if you need direct access to NVIDIA CUDA C++ compute libraries and your system has compatible GPU hardware. The active maintenance, zero runtime dependencies, and top-5000 popularity suggest solid adoption. However, verify the unclear license terms with NVIDIA and confirm your system architecture matches an available wheel before installing. Not suitable without an NVIDIA GPU.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a compatible NVIDIA GPU and CUDA Toolkit installation on the system; wheel availability is platform-specific (Windows, x86_64 Linux, aarch64 Linux).
- Medium install friction due to platform-specific wheel distributions (x86_64, aarch64, Windows).
- Active maintenance with a recent release within 46 days.
License · maintenance · safety
(unclear) — License treatment is unclear—no SPDX identifier or raw license text is available. Verify licensing terms directly with NVIDIA before deploying in commercial or restricted environments.
last release 2026-06-29 (46 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,892,828 downloads/mo, #3,459 on PyPI
Alternatives
Verify before relying
pip install nvidia-cuda-cccl==13.3.3.4.1
import nvidia.cuda.cccl- Exact API surface and callable functions within the nvidia.cuda.cccl module are not documented in the fact sheet.
- Whether this package requires a separate CUDA Toolkit system installation or bundles runtime components.
- Compatibility matrix between specific CUDA Toolkit versions and this package version 13.3.3.4.1.
- License terms and any restrictions on use, modification, or redistribution.
What it is and what it does
nvidia-cuda-cccl is a Python package that wraps NVIDIA's CUDA C++ Core Compute Libraries, enabling GPU-accelerated computing for scientific and machine learning workloads. It targets developers working with deep learning, numerical computing, and AI applications on NVIDIA hardware.
The package provides low-level access to CUDA compute primitives and is designed to integrate with higher-level frameworks. It has no Python runtime dependencies, making it a lightweight addition to GPU-enabled environments. Installation requires matching your system architecture (x86_64, aarch64, or Windows) to the available wheels. The package is actively maintained and supports Python 3.5 through 3.11.
Use it for
- Integrate CUDA compute libraries into custom GPU acceleration pipelines for scientific computing.
- Provide foundational GPU compute support for machine learning frameworks and deep learning applications.
- Accelerate numerical algorithms and mathematical operations on NVIDIA GPUs.
- Build or extend GPU-enabled data processing workflows in research and production environments.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need direct access to NVIDIA CUDA C++ compute libraries and your system has compatible GPU hardware.
The active maintenance, zero runtime dependencies, and top-5000 popularity suggest solid adoption. However, verify the unclear license terms with NVIDIA and confirm your system architecture matches an available wheel before installing. Not suitable without an NVIDIA GPU.
Install
nvidia-cuda-cccl on PyPI
Before you install
Medium install friction due to platform-specific wheel distributions (x86_64, aarch64, Windows). Active maintenance with a recent release within 46 days. No runtime dependencies simplifies integration.
Requires a compatible NVIDIA GPU and CUDA Toolkit installation on the system; wheel availability is platform-specific (Windows, x86_64 Linux, aarch64 Linux).
License in practice
License treatment is unclear—no SPDX identifier or raw license text is available. Verify licensing terms directly with NVIDIA before deploying in commercial or restricted environments.
Quickstart
pip install nvidia-cuda-cccl==13.3.3.4.1
import nvidia.cuda.ccclVerify before relying
- Exact API surface and callable functions within the nvidia.cuda.cccl module are not documented in the fact sheet.
- Whether this package requires a separate CUDA Toolkit system installation or bundles runtime components.
- Compatibility matrix between specific CUDA Toolkit versions and this package version 13.3.3.4.1.
- License terms and any restrictions on use, modification, or redistribution.
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 46 days since the last release |
| First released | |
| Downloads | 1,892,828 / month, #3,459 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchNatural Language :: EnglishOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.5Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: MathematicsTopic :: Software DevelopmentTopic :: Software Development :: Libraries |
Evidence: nvidia_cuda_cccl-13.3.3.4.1-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; nvidia_cuda_cccl-13.3.3.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; nvidia_cuda_cccl-13.3.3.4.1-py3-none-win_amd64.whl
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See also nvidia-cuda-cccl-cu12 · nvidia-cuda-crt · nvidia-cuda-runtime-cu11 · nvidia-cuda-runtime-cu12 · nvidia-cuda-runtime · pyopencl · nvidia-nccl-cu13 · cpm-kernels · nvidia-cublas · nvidia-nccl-cu12