cupy-cuda11x

library13.6.0pypypi✓ verified 90d ago

CuPy is a NumPy/SciPy-compatible array library for GPU-accelerated computing with CUDA 11.x. This package is specifically built for CUDA 11.x environments. Current version: 13.6.0. Release cadence: regular, matching the main CuPy release cycle.

ai-ml data

pip install cupy-cuda11x

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · CUPY-CUDA11X

cupy-cuda11x

ai-mlpythonv13.6.0

Install

8.1s avg

Import

884ms

Disk

298MB

Pass rate

5/ 10

Env Coverage5 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v13.6.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

build_error

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 8.1s · import 0.884s · 295MB

298MB installed

● package 298MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

cupy

✓ import cupy

Standard import for CuPy

cupyx

✓ import cupyx

CuPy extensions (scipy, sparse, etc.)

Basic usage of CuPy on GPU with CUDA 11.x.

import cupy as cp import numpy as np # Create a GPU array x_gpu = cp.array([1, 2, 3, 4, 5]) print(x_gpu) # Perform operations on GPU print(cp.sum(x_gpu)) # Create a random matrix on GPU A = cp.random.randn(1000, 1000) print(A.shape) # Verify CUDA and CuPy version print(cp.__version__) print(cp.cuda.runtime.runtimeGetVersion())

Debug

Known issues

breakingCuPy v13 drops support for CUDA 11.0-11.3; only CUDA 11.4+ is supported. Ensure your CUDA version is 11.4 or higher.

fix

Upgrade CUDA to 11.4+ or use cupy-cuda11x version 12.x for older CUDA 11.x.

affects: >=13.0

gotchaInstalling cupy-cuda11x on a system with mismatched CUDA runtime version may cause import errors or silent fallback to CPU. Check with `nvidia-smi` and `nvcc --version`.

fix

Ensure that the installed CUDA toolkit version matches the package: CUDA 11.4+ for cupy-cuda11x.

affects: all

gotchaCuPy arrays created on one GPU device cannot be directly accessed on another device. Use `cp.cuda.Device(n)` context manager to switch devices.

fix

Use `with cp.cuda.Device(1):` to perform operations on a different GPU.

affects: all

deprecatedThe `cupy.cuda.Device` context management API is deprecated in favor of `cupy.cuda.Device.__enter__` and `__exit__`; use the `with` statement as usual.

fix

Use `with cupy.cuda.Device(0):` syntax; it remains the same but is no longer considered experimental.

affects: >=12.0

Errors

Common errors & fixes

ImportError: libcudart.so.11.0: cannot open shared object file: No such file or directory

The installed cupy-cuda11x package expects CUDA 11.x runtime, but the system has a different or missing CUDA installation.

fix

Install the correct CUDA toolkit version (11.4+) or use a cupy-cuda package matching your CUDA version (e.g., cupy-cuda12x).

cupy.cuda.runtime.CUDARuntimeError: cudaErrorNoDevice: no CUDA-capable device is detected

No NVIDIA GPU is available or the GPU driver is not properly installed.

fix

Check GPU presence with `nvidia-smi`. Install appropriate NVIDIA drivers.

ModuleNotFoundError: No module named 'cupy'

CuPy has not been installed or the wrong package (e.g., cupy-cuda11x vs cupy) was not installed.

fix

Install with `pip install cupy-cuda11x` and verify import with `import cupy`.

Upgrade

Version history

13.6.0latest on PyPI · released Aug 18, 2025

Audit

Dependencies

fastrlockrequiredRequired for CuPy runtime

Agent activity

29 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/cupy/cupy ↗

packagehttps://pypi.org/project/cupy-cuda11x/ ↗

homepagehttps://cupy.dev/ ↗

docshttps://docs.cupy.dev/ ↗