nvidia-nvjitlink
Nvidia JIT LTO Library
Decision gist · record as of 2026-08-14
Yes, if required by another package you are installing—this is a foundational NVIDIA runtime library. Install directly only if you are building CUDA applications that explicitly need JIT LTO compilation. No known security vulnerabilities. License status is unclear, so verify compatibility with your project's licensing requirements before use.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a compatible CUDA-capable GPU and appropriate NVIDIA drivers; platform-specific wheel (Linux x86_64/aarch64 or Windows x86_64 only).
- Medium install friction due to platform-specific wheel distributions (x86_64 Linux, aarch64 Linux, Windows).
- Package is actively maintained with a recent release cycle.
License · maintenance · safety
(unclear)
last release 2026-05-26 (80 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 43,189,183 downloads/mo, #646 on PyPI
Alternatives
Verify before relying
pip install nvidia-nvjitlink==13.3.33
import nvidia.nvjitlink
# Typically used indirectly via higher-level CUDA frameworks- Whether this package requires a separate CUDA toolkit installation or system libraries beyond the wheel.
- Specific use cases and API surface for the JIT LTO functionality.
- Whether this is a standalone library or a dependency typically pulled in by other NVIDIA packages.
What it is and what it does
nvidia-nvjitlink is NVIDIA's compiler library for JIT (just-in-time) and LTO (link-time optimization) functionality, distributed as a Python package. It provides low-level compilation capabilities for CUDA-based workloads and is primarily used as a runtime dependency by higher-level machine learning and deep learning frameworks. The package is platform-specific, with separate wheels for Linux (x86_64 and aarch64) and Windows, and requires Python 3 or later.
This is a foundational library rather than a user-facing tool—most developers encounter it indirectly as a transitive dependency of CUDA-enabled machine learning frameworks. It handles the compilation and linking stages of GPU code, enabling dynamic optimization of CUDA kernels at runtime.
Use it for
- Dependency for CUDA-enabled machine learning frameworks that need JIT compilation of GPU kernels.
- Runtime support for applications performing dynamic CUDA code generation and optimization.
- Enabling link-time optimization for CUDA workloads in scientific computing and deep learning pipelines.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if required by another package you are installing—this is a foundational NVIDIA runtime library.
Install directly only if you are building CUDA applications that explicitly need JIT LTO compilation. No known security vulnerabilities. License status is unclear, so verify compatibility with your project's licensing requirements before use.
Install
nvidia-nvjitlink on PyPI
Before you install
Medium install friction due to platform-specific wheel distributions (x86_64 Linux, aarch64 Linux, Windows). Package is actively maintained with a recent release cycle.
Requires a compatible CUDA-capable GPU and appropriate NVIDIA drivers; platform-specific wheel (Linux x86_64/aarch64 or Windows x86_64 only).
Quickstart
pip install nvidia-nvjitlink==13.3.33
import nvidia.nvjitlink
# Typically used indirectly via higher-level CUDA frameworksVerify before relying
- Whether this package requires a separate CUDA toolkit installation or system libraries beyond the wheel.
- Specific use cases and API surface for the JIT LTO functionality.
- Whether this is a standalone library or a dependency typically pulled in by other NVIDIA packages.
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 | 43,189,183 / month, #646 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_nvjitlink-13.3.33-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl; nvidia_nvjitlink-13.3.33-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; nvidia_nvjitlink-13.3.33-py3-none-win_amd64.whl
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See also nvidia-nvjitlink-cu12 · drjit · nvidia-nvvm · nvidia-cuda-nvrtc-cu12 · nvidia-cuda-nvrtc-cu11 · nvidia-cuda-nvcc · nvidia-nvfatbin · numba · nvidia-cuda-nvrtc · llvmlite