nvidia-cusolver-cu12
CUDA solver native runtime libraries
Decision gist · record as of 2026-08-14
Yes, if you are installing a GPU-accelerated framework (PyTorch, TensorFlow, CuPy) that declares it as a dependency. No, if you are looking for a standalone package to use directly—this is a runtime library meant to be pulled in transitively. Verify NVIDIA's proprietary license terms apply to your use case before deployment.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an NVIDIA GPU and CUDA Compute Capability support; only wheels available for Windows (amd64), Linux x86_64, and Linux aarch64.
- Medium install friction due to platform-specific wheels (Windows, Linux aarch64, Linux x86_64) and three compiled runtime dependencies.
- Last release was 435 days ago; maintenance status is aging.
License · maintenance · safety
LicenseRef-NVIDIA-Proprietary (unclear) — Licensed under a proprietary NVIDIA license (LicenseRef-NVIDIA-Proprietary) with unclear treatment. Review NVIDIA's licensing terms before deploying in commercial or redistributed contexts.
last release 2025-06-05 (435 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 26,003,308 downloads/mo, #894 on PyPI
Alternatives
Verify before relying
pip install nvidia-cusolver-cu12
import nvidia.cusolver
# Use through higher-level frameworks like CuPy or PyTorch that depend on this runtime- Whether this package is intended for direct use or only as a transitive dependency of higher-level libraries.
- Current maintenance status and whether updates are planned beyond the 435-day gap since last release.
What it is and what it does
nvidia-cusolver-cu12 is a runtime library distribution for NVIDIA's CUDA solver suite, providing native binaries for GPU-accelerated linear algebra operations. It is not typically imported directly by user code; instead, it serves as a low-level dependency for frameworks like CuPy, PyTorch, or other CUDA-aware libraries that need access to cuSOLVER functions for matrix decomposition, linear system solving, and eigenvalue computation on NVIDIA GPUs.
The package depends on three other NVIDIA runtime libraries: nvidia-cublas-cu12, nvidia-nvjitlink-cu12, and nvidia-cusparse-cu12. Installation requires a platform-specific wheel matching your OS and architecture. The proprietary NVIDIA license and aging maintenance status (435 days since last release) mean you should verify compatibility with your target CUDA version and check whether your use case is covered by NVIDIA's licensing terms.
Use it for
- Dependency for PyTorch or TensorFlow GPU installations that need cuSOLVER for linear algebra kernels.
- Runtime library for CuPy-based scientific computing requiring GPU-accelerated matrix operations.
- Backend for custom CUDA applications that directly call cuSOLVER functions via ctypes or Cython bindings.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are installing a GPU-accelerated framework (PyTorch, TensorFlow, CuPy) that declares it as a dependency.
No, if you are looking for a standalone package to use directly—this is a runtime library meant to be pulled in transitively. Verify NVIDIA's proprietary license terms apply to your use case before deployment.
Install
nvidia-cusolver-cu12 on PyPI
Before you install
Medium install friction due to platform-specific wheels (Windows, Linux aarch64, Linux x86_64) and three compiled runtime dependencies. Last release was 435 days ago; maintenance status is aging.
Requires an NVIDIA GPU and CUDA Compute Capability support; only wheels available for Windows (amd64), Linux x86_64, and Linux aarch64.
License in practice
Licensed under a proprietary NVIDIA license (LicenseRef-NVIDIA-Proprietary) with unclear treatment. Review NVIDIA's licensing terms before deploying in commercial or redistributed contexts.
Quickstart
pip install nvidia-cusolver-cu12
import nvidia.cusolver
# Use through higher-level frameworks like CuPy or PyTorch that depend on this runtimeVerify before relying
- Whether this package is intended for direct use or only as a transitive dependency of higher-level libraries.
- Current maintenance status and whether updates are planned beyond the 435-day gap since last release.
Package facts
| License | LicenseRef-NVIDIA-Proprietary unclear |
| Python support | Supports the current Python release >=3 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 3 packagesnvidia-cublas-cu12nvidia-nvjitlink-cu12nvidia-cusparse-cu12 |
| Maintenance | Aging 435 days since the last release |
| First released | |
| Downloads | 26,003,308 / month, #894 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/ResearchLicense :: Other/Proprietary LicenseNatural 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_cusolver_cu12-11.7.5.82-py3-none-manylinux_2_27_aarch64.whl; nvidia_cusolver_cu12-11.7.5.82-py3-none-manylinux_2_27_x86_64.whl; nvidia_cusolver_cu12-11.7.5.82-py3-none-win_amd64.whl
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See also nvidia-cusolver · nvidia-cusolver-cu11 · linear-operator · pyamg · nvidia-cusparse-cu12 · nvidia-cublas-cu12 · nvidia-cublas · nvidia-cublas-cu11 · cudensitymat-cu13 · nvidia-curand-cu12