nvidia-cuda-runtime
CUDA Runtime native Libraries
Decision gist · record as of 2026-08-14
Yes, if you are building or using GPU-accelerated Python applications on a system with an NVIDIA GPU and compatible driver. This is typically installed as a transitive dependency rather than directly. Verify the license terms with NVIDIA before use in proprietary contexts, and ensure your GPU and driver are compatible with CUDA 13.3.29. No known vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a compatible GPU and NVIDIA driver installed on the system; wheels are platform-specific (Linux x86_64, Linux aarch64, or Windows x86_64).
- Medium install friction due to platform-specific wheels (aarch64, x86_64, Windows).
- Package is actively maintained with a release within the last 80 days.
License · maintenance · safety
(unclear) — License treatment is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify licensing terms directly with NVIDIA before use in proprietary or restricted contexts.
last release 2026-05-26 (80 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 40,109,653 downloads/mo, #686 on PyPI
Alternatives
Verify before relying
pip install nvidia-cuda-runtime==13.3.29- Whether this package alone is sufficient for CUDA development or if additional NVIDIA packages are required.
- Exact license terms and any restrictions on commercial or derivative use.
- Compatibility matrix between CUDA Runtime version 13.3.29 and specific GPU architectures and driver versions.
- Whether direct import is typical or if this is primarily a transitive dependency.
What it is and what it does
nvidia-cuda-runtime is a distribution of NVIDIA's CUDA Runtime native libraries packaged for Python. It provides the low-level runtime components needed for GPU-accelerated computation. The package is platform-specific, with separate wheels for Linux (x86_64 and aarch64) and Windows (x86_64), and requires a compatible NVIDIA GPU and driver to function.
This is a foundational package rather than a user-facing library. Installation is straightforward but platform-dependent; the correct wheel must match your system architecture. The package supports Python versions from 3.5 through 3.11 and is actively maintained.
Use it for
- Dependency for machine learning frameworks that require GPU acceleration.
- Base runtime for scientific computing libraries that offload computation to NVIDIA GPUs.
- Development environment setup for CUDA-based applications on Windows or Linux systems.
- Containerized GPU workloads where CUDA Runtime libraries must be bundled with Python.
- Cross-platform GPU application distribution via wheels rather than system package managers.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building or using GPU-accelerated Python applications on a system with an NVIDIA GPU and compatible driver.
This is typically installed as a transitive dependency rather than directly. Verify the license terms with NVIDIA before use in proprietary contexts, and ensure your GPU and driver are compatible with CUDA 13.3.29. No known vulnerabilities.
Install
nvidia-cuda-runtime on PyPI
Before you install
Medium install friction due to platform-specific wheels (aarch64, x86_64, Windows). Package is actively maintained with a release within the last 80 days. No runtime dependencies to manage.
Requires a compatible GPU and NVIDIA driver installed on the system; wheels are platform-specific (Linux x86_64, Linux aarch64, or Windows x86_64).
License in practice
License treatment is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify licensing terms directly with NVIDIA before use in proprietary or restricted contexts.
Quickstart
pip install nvidia-cuda-runtime==13.3.29Verify before relying
- Whether this package alone is sufficient for CUDA development or if additional NVIDIA packages are required.
- Exact license terms and any restrictions on commercial or derivative use.
- Compatibility matrix between CUDA Runtime version 13.3.29 and specific GPU architectures and driver versions.
- Whether direct import is typical or if this is primarily a transitive dependency.
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 80 days since the last release |
| First released | |
| Downloads | 40,109,653 / month, #686 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_runtime-13.3.29-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; nvidia_cuda_runtime-13.3.29-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; nvidia_cuda_runtime-13.3.29-py3-none-win_amd64.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “cuda native bindings”
- nvidia-cuda-runtimeProvides NVIDIA CUDA Runtime native libraries for GPU-accelerated…
- nvidia-cusolverProvides CUDA solver native runtime libraries for GPU-accelerated…
- ucxx-cu12ucxx-cu12 provides Python bindings for the Unified Communication X…
Give your agent the search over MCP, or paste the wish link into any chat.
More Software Development packages
Provides backported and experimental type hints for Python 3.9+, allowing use of newer typing features on older Python versions and enabling early experimentation with type system PEPs before they enter the standard library.
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
FastAPI is a Python web framework for building REST APIs using type hints, with automatic request validation, serialization, and interactive API documentation.
Provides a way to document function parameters, class attributes, return types, and variables inline using Python's `Annotated` type hint syntax instead of traditional docstrings.
Typer builds command-line applications from Python functions using type hints, automatically generating help text, argument parsing, and shell completion.
Install it if you are building CLIs in Python.
Distlib provides low-level packaging utilities for building, distributing, and managing Python software—including metadata handling, version specifiers, wheel support, script installation, and dependency resolution.
See also nvidia-cuda-runtime-cu11 · pycuda · nvidia-cuda-crt · nvidia-cuda-runtime-cu12 · cuda-toolkit · nvidia-cuda-cccl · nvidia-cufile · nvidia-cublas · nvidia-cublas-cu11 · nvidia-curand