nvidia-cuda-nvcc
CUDA nvcc
Decision gist · record as of 2026-08-14
Yes, if you need to compile CUDA code from Python on a GPU-equipped system. The package is actively maintained, has no known vulnerabilities, and is widely used (top 5000 on PyPI). Install friction is moderate due to platform-specific wheels and GPU hardware requirements, but this is inherent to CUDA development. Verify that your system meets the GPU and driver prerequisites before installing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires NVIDIA GPU hardware and CUDA-capable system; wheels are platform-specific (Linux or Windows only).
- Medium install friction due to platform-specific wheels (Linux aarch64, Linux x86_64, Windows) and three NVIDIA runtime dependencies (nvidia-nvvm, nvidia-cuda-runtime, nvidia-cuda-crt).
- Active maintenance with a recent release.
License · maintenance · safety
(unclear)
last release 2026-06-29 (46 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,539,204 downloads/mo, #3,013 on PyPI
Alternatives
Verify before relying
pip install nvidia-cuda-nvcc
import nvidia.cuda.nvcc
# Use nvcc compiler for CUDA source files- Whether the package provides direct CLI access to nvcc or only programmatic bindings.
- What CUDA compute capabilities and driver versions are supported by version 13.3.73.
- Whether documentation or examples are available beyond the NVIDIA developer homepage.
What it is and what it does
nvidia-cuda-nvcc is a Python package that bundles the NVIDIA CUDA nvcc compiler, enabling developers to compile CUDA C/C++ code as part of Python-based build workflows. It packages the compiler with three runtime dependencies (nvidia-nvvm, nvidia-cuda-runtime, nvidia-cuda-crt) to provide a self-contained compilation environment. The package is classified as Beta and targets developers, educators, and researchers working with GPU-accelerated computing, machine learning, and deep learning applications.
Installation requires a CUDA-capable NVIDIA GPU and the appropriate platform (Linux aarch64, Linux x86_64, or Windows). The package supports Python 3.5 through 3.11 and is actively maintained, with its latest release dated 2026-06-29. It carries no known security vulnerabilities as of the last check.
Use it for
- Compile custom CUDA kernels as part of a Python machine learning pipeline or build system.
- Develop GPU-accelerated libraries that require CUDA source compilation during installation.
- Integrate CUDA compilation into continuous integration workflows for GPU-accelerated applications.
- Build custom CUDA extensions for deep learning frameworks that need kernel-level optimization.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to compile CUDA code from Python on a GPU-equipped system.
The package is actively maintained, has no known vulnerabilities, and is widely used (top 5000 on PyPI). Install friction is moderate due to platform-specific wheels and GPU hardware requirements, but this is inherent to CUDA development. Verify that your system meets the GPU and driver prerequisites before installing.
Install
nvidia-cuda-nvcc on PyPI
Before you install
Medium install friction due to platform-specific wheels (Linux aarch64, Linux x86_64, Windows) and three NVIDIA runtime dependencies (nvidia-nvvm, nvidia-cuda-runtime, nvidia-cuda-crt). Active maintenance with a recent release.
Requires NVIDIA GPU hardware and CUDA-capable system; wheels are platform-specific (Linux or Windows only).
Quickstart
pip install nvidia-cuda-nvcc
import nvidia.cuda.nvcc
# Use nvcc compiler for CUDA source filesVerify before relying
- Whether the package provides direct CLI access to nvcc or only programmatic bindings.
- What CUDA compute capabilities and driver versions are supported by version 13.3.73.
- Whether documentation or examples are available beyond the NVIDIA developer homepage.
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 3 packagesnvidia-nvvmnvidia-cuda-runtimenvidia-cuda-crt |
| Maintenance | Actively maintained 46 days since the last release |
| First released | |
| Downloads | 2,539,204 / month, #3,013 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_nvcc-13.3.73-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; nvidia_cuda_nvcc-13.3.73-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; nvidia_cuda_nvcc-13.3.73-py3-none-win_amd64.whl
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See also nvidia-cuda-nvcc-cu12 · nvidia-cuda-nvdisasm · nvidia-nvfatbin · nvidia-nvvm · nvidia-cuda-nvrtc-cu12 · nvidia-cuda-nvrtc · nvidia-nvjitlink · nvidia-cuda-tileiras · cuda-toolkit · nvidia-cuda-nvrtc-cu11