custatevec-cu13
cuStateVec - a component of NVIDIA cuQuantum SDK
Decision gist · record as of 2026-08-14
Yes, if you are developing quantum simulators on NVIDIA CUDA 13 hardware and need GPU acceleration. The package is actively maintained, has no known vulnerabilities, and fills a specialized role in the quantum computing ecosystem. However, verify the NVIDIA Proprietary Software license terms for your use case first, and confirm your system has CUDA 13 and a compatible GPU before installing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires NVIDIA CUDA 13 and compatible GPU; wheels are only available for Linux x86_64 and aarch64 architectures.
- The package is actively maintained with recent releases and carries medium install friction due to platform-specific wheels (x86_64 and aarch64 Linux only).
- No runtime dependencies simplify deployment once the wheel is available for your architecture.
License · maintenance · safety
NVIDIA Proprietary Software (unclear) — Licensed under NVIDIA Proprietary Software with no SPDX identifier; the exact terms and redistribution rights are unclear from the metadata alone and should be verified against NVIDIA's licensing documentation before production use.
last release 2026-06-29 (46 days) · last repo commit 2026-06-29 · 494 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 92,754 downloads/mo, #13,430 on PyPI
Alternatives
Verify before relying
pip install custatevec-cu13
import custatevec
# Access cuStateVec C API or use via cuQuantum Python wrapper- Exact licensing terms and permitted use cases under NVIDIA Proprietary Software license
- Whether Python API is directly exposed or requires cuQuantum Python wrapper
- Minimum Python version requirement (not specified in metadata)
What it is and what it does
cuStateVec is NVIDIA's high-performance library for state vector quantum simulation operations, part of the cuQuantum SDK. It provides GPU-accelerated computation on NVIDIA CUDA hardware, enabling researchers and developers to build quantum simulators that leverage GPU parallelism for faster state vector manipulations and measurements.
The package is distributed as platform-specific wheels for Linux (x86_64 and aarch64) and requires CUDA 13 to be installed on the system. It has no Python runtime dependencies, meaning once installed, it provides direct access to the underlying C library. The documentation notes that for Python-level APIs, users should install the cuQuantum Python wrapper instead, suggesting this package is primarily a lower-level component.
Use it for
- Building GPU-accelerated quantum circuit simulators that need fast state vector operations
- Prototyping quantum algorithms on NVIDIA GPUs without writing CUDA C code directly
- Integrating state vector quantum simulation into larger scientific computing pipelines on GPU clusters
- Research into quantum algorithm performance on modern GPU hardware
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are developing quantum simulators on NVIDIA CUDA 13 hardware and need GPU acceleration.
The package is actively maintained, has no known vulnerabilities, and fills a specialized role in the quantum computing ecosystem. However, verify the NVIDIA Proprietary Software license terms for your use case first, and confirm your system has CUDA 13 and a compatible GPU before installing.
Install
custatevec-cu13 on PyPI
Before you install
The package is actively maintained with recent releases and carries medium install friction due to platform-specific wheels (x86_64 and aarch64 Linux only). No runtime dependencies simplify deployment once the wheel is available for your architecture.
Requires NVIDIA CUDA 13 and compatible GPU; wheels are only available for Linux x86_64 and aarch64 architectures.
License in practice
Licensed under NVIDIA Proprietary Software with no SPDX identifier; the exact terms and redistribution rights are unclear from the metadata alone and should be verified against NVIDIA's licensing documentation before production use.
Quickstart
pip install custatevec-cu13
import custatevec
# Access cuStateVec C API or use via cuQuantum Python wrapperVerify before relying
- Exact licensing terms and permitted use cases under NVIDIA Proprietary Software license
- Whether Python API is directly exposed or requires cuQuantum Python wrapper
- Minimum Python version requirement (not specified in metadata)
Package facts
| License | NVIDIA Proprietary Software unclear |
| Python support | Not specified |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 46 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 92,754 / month, #13,430 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Environment :: GPU :: NVIDIA CUDAEnvironment :: GPU :: NVIDIA CUDA :: 13Topic :: Scientific/Engineering |
Evidence: custatevec_cu13-1.14.0-py3-none-manylinux2014_aarch64.whl; custatevec_cu13-1.14.0-py3-none-manylinux2014_x86_64.whl
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See also cudensitymat-cu13 · custatevec-cu12 · cutensornet-cu13 · pennylane-lightning · cuvs-cu12 · nvidia-libnvcomp-cu12 · nvidia-cusolver-cu11 · nvidia-cuda-cccl · nvidia-cuda-cccl-cu12 · nvidia-cusolver-cu12