nvidia-cufft
CUFFT native runtime libraries
Install
nvidia-cufft on PyPI
pip
pip install nvidia-cufftuv
uv add nvidia-cufftpoetry
poetry add nvidia-cufftPackage facts
| License | not declared (unclear) |
| Python support | supports the current Python release (>=3) |
| Install friction | medium — platform-specific wheel |
| Runtime dependencies | 1 — nvidia-nvjitlink |
| Maintenance | actively maintained — 79 days since the last release |
| First released | |
| Popularity | one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-13) |
Evidence: nvidia_cufft-12.3.0.29-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; nvidia_cufft-12.3.0.29-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; nvidia_cufft-12.3.0.29-py3-none-win_amd64.whl
Keywords: cuda, nvidia, runtime, machine learning, deep learning
About nvidia-cufft
from the package's own PyPI description — quoted content, verbatim
CUFFT native runtime libraries
AI interpretation — verify before relying
AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page
Provides NVIDIA CUFFT native runtime libraries for GPU-accelerated Fast Fourier Transform computations on CUDA-capable hardware.
Medium install friction due to platform-specific wheels (x86_64, aarch64, Windows); requires nvidia-nvjitlink at runtime. Package is actively maintained with a recent release (79 days old).
License treatment is unclear—no SPDX identifier or raw license text is declared. Verify licensing terms directly with NVIDIA before use in proprietary or redistributed contexts.
Usage
pip install nvidia-cufft==12.3.0.29
import nvidia.cufft
# Use via higher-level CUDA libraries (e.g., CuPy, PyTorch)
Requires NVIDIA CUDA Compute Capability 3.5+ GPU and nvidia-nvjitlink runtime dependency installed.
Verdict: A foundational NVIDIA runtime library for GPU-accelerated FFT operations, actively maintained and free of known vulnerabilities. Medium install friction stems from platform-specific wheels and the nvidia-nvjitlink dependency. Primary concern is unclear licensing—verify NVIDIA's terms before adoption in commercial or redistributed projects.
Needs verification
- Whether this package is intended for direct use or only as a transitive dependency of higher-level libraries
- Specific NVIDIA license terms and any restrictions on redistribution or commercial use
- Compatibility matrix across CUDA versions and GPU architectures beyond the wheel platforms listed
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