nvidia-nvfatbin
NVIDIA compiler library for fatbin interaction
Decision gist · record as of 2026-08-14
Yes, if you need to work with CUDA fatbin files in Python and are on a supported platform (Linux x86_64/aarch64 or Windows x64). The package is actively maintained and has no known vulnerabilities. However, verify the license terms before use in proprietary projects, and confirm that your system meets any undocumented CUDA runtime dependencies. Medium install friction is typical for NVIDIA GPU libraries.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3 or later; platform-specific wheels available only for x86_64/aarch64 Linux and Windows x64.
- Medium install friction due to platform-specific wheels (x86_64 Linux, aarch64 Linux, Windows).
- Last release 80 days ago with active maintenance status, though repository metadata is not publicly available.
License · maintenance · safety
(unclear) — License treatment is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify licensing terms before use in proprietary or redistributed projects.
last release 2026-05-26 (80 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 340,755 downloads/mo, #7,409 on PyPI
Alternatives
Verify before relying
pip install nvidia-nvfatbin==13.3.29
import nvidia.nvfatbin- What specific fatbin operations or APIs does this library expose—is it a thin wrapper or a full compiler interface?
- Are there undocumented system dependencies (e.g., CUDA Toolkit, driver versions) required at runtime?
- What is the actual license under which this package is distributed?
What it is and what it does
nvidia-nvfatbin is a Python interface to NVIDIA's fatbin compiler library, used for interacting with CUDA binary formats. Fatbin files are containers for GPU-compiled code and metadata; this package allows Python developers to work with these artifacts programmatically, likely for tasks like inspecting, manipulating, or embedding GPU binaries in larger applications.
The package targets developers working with CUDA, machine learning frameworks, and GPU computing. It has no declared runtime dependencies and is distributed as platform-specific wheels for Linux (x86_64 and aarch64) and Windows. The library is actively maintained and has seen recent releases, though its documentation and licensing terms are not clearly published.
Use it for
- Inspect or extract metadata from CUDA fatbin files in a Python workflow.
- Programmatically manipulate GPU binary artifacts during custom build or deployment pipelines.
- Integrate CUDA binary handling into machine learning or deep learning framework extensions.
- Automate GPU code packaging or versioning tasks that require fatbin introspection.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to work with CUDA fatbin files in Python and are on a supported platform (Linux x86_64/aarch64 or Windows x64).
The package is actively maintained and has no known vulnerabilities. However, verify the license terms before use in proprietary projects, and confirm that your system meets any undocumented CUDA runtime dependencies. Medium install friction is typical for NVIDIA GPU libraries.
Install
nvidia-nvfatbin on PyPI
Before you install
Medium install friction due to platform-specific wheels (x86_64 Linux, aarch64 Linux, Windows). Last release 80 days ago with active maintenance status, though repository metadata is not publicly available.
Requires Python 3 or later; platform-specific wheels available only for x86_64/aarch64 Linux and Windows x64.
License in practice
License treatment is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify licensing terms before use in proprietary or redistributed projects.
Quickstart
pip install nvidia-nvfatbin==13.3.29
import nvidia.nvfatbinVerify before relying
- What specific fatbin operations or APIs does this library expose—is it a thin wrapper or a full compiler interface?
- Are there undocumented system dependencies (e.g., CUDA Toolkit, driver versions) required at runtime?
- What is the actual license under which this package is distributed?
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 | 340,755 / month, #7,409 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_nvfatbin-13.3.29-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl; nvidia_nvfatbin-13.3.29-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; nvidia_nvfatbin-13.3.29-py3-none-win_amd64.whl
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See also nvidia-cuda-nvcc · nvidia-nvvm · nvidia-cuda-nvcc-cu12 · nvidia-nvjitlink · nvidia-nvjitlink-cu12 · nvidia-cuda-nvrtc · nvidia-cuda-nvrtc-cu12 · nvidia-cuda-nvrtc-cu11 · nvidia-cuda-runtime · nvidia-cuda-crt