nvidia-curand
CURAND native runtime libraries
Decision gist · record as of 2026-08-14
Yes, if you are building or using a CUDA-dependent application or framework that lists nvidia-curand as a dependency. No, if you are looking for a user-facing random number library—install a higher-level package like PyTorch or NumPy instead. The unclear license status warrants verification before use in proprietary projects.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires NVIDIA CUDA-capable GPU and compatible CUDA runtime; platform-specific wheel must match your OS (Linux x86_64/aarch64 or Windows amd64).
- Medium install friction due to platform-specific wheels (manylinux_2_27 x86_64/aarch64, Windows amd64).
- No runtime dependencies.
License · maintenance · safety
(unclear) — License treatment is unclear—no SPDX identifier or raw license text provided. 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) · 41,392,726 downloads/mo, #672 on PyPI
Alternatives
Verify before relying
pip install nvidia-curand==10.4.3.29
import nvidia.curand
# Use CURAND functions via the nvidia.curand module- Exact CUDA version compatibility and minimum GPU compute capability required
- Whether this is a standalone library or requires separate CUDA toolkit installation
- API surface and typical usage patterns beyond native runtime provision
What it is and what it does
nvidia-curand is a Python package that exposes NVIDIA's CURAND native runtime libraries, enabling GPU-accelerated random number generation. It is a low-level runtime distribution rather than a high-level API wrapper—it packages the compiled CURAND libraries for direct use in CUDA applications and frameworks that depend on them.
The package is primarily consumed as a dependency by higher-level machine learning and scientific computing libraries rather than used directly by end developers. It supports Python 3.5 through 3.11 on Linux (x86_64 and aarch64) and Windows (amd64). Installation requires selecting the correct platform-specific wheel, and the underlying GPU hardware must be NVIDIA-compatible.
Use it for
- Dependency for deep learning frameworks (PyTorch, TensorFlow) that need GPU random number generation
- Scientific computing pipelines requiring reproducible GPU-accelerated stochastic simulations
- CUDA application development where CURAND functions are called directly or indirectly
- Machine learning training on GPU where random initialization and dropout require fast parallel RNG
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building or using a CUDA-dependent application or framework that lists nvidia-curand as a dependency.
No, if you are looking for a user-facing random number library—install a higher-level package like PyTorch or NumPy instead. The unclear license status warrants verification before use in proprietary projects.
Install
nvidia-curand on PyPI
Before you install
Medium install friction due to platform-specific wheels (manylinux_2_27 x86_64/aarch64, Windows amd64). No runtime dependencies. Last release 80 days ago with active maintenance status.
Requires NVIDIA CUDA-capable GPU and compatible CUDA runtime; platform-specific wheel must match your OS (Linux x86_64/aarch64 or Windows amd64).
License in practice
License treatment is unclear—no SPDX identifier or raw license text provided. Verify licensing terms before use in proprietary or redistributed projects.
Quickstart
pip install nvidia-curand==10.4.3.29
import nvidia.curand
# Use CURAND functions via the nvidia.curand moduleVerify before relying
- Exact CUDA version compatibility and minimum GPU compute capability required
- Whether this is a standalone library or requires separate CUDA toolkit installation
- API surface and typical usage patterns beyond native runtime provision
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 | 41,392,726 / month, #672 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_curand-10.4.3.29-py3-none-manylinux_2_27_aarch64.whl; nvidia_curand-10.4.3.29-py3-none-manylinux_2_27_x86_64.whl; nvidia_curand-10.4.3.29-py3-none-win_amd64.whl
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See also nvidia-curand-cu11 · nvidia-curand-cu12 · pyudorandom · nvidia-cublas-cu11 · nvidia-cuda-crt · nvidia-cuda-runtime · pytorch-seed · nvidia-cufft · nvidia-cublas · arm-pytorch-utilities