---
id: nvidia-cudnn-cu11
version: "9.10.2.21"
license: LicenseRef-NVIDIA-Proprietary
license_treatment: unclear
maintenance: aging
---

# nvidia-cudnn-cu11 — cuDNN runtime libraries

License: unclear · Maintenance: aging · Downloads: 2.5M/mo

## What it is and what it does

nvidia-cudnn-cu11 is a runtime library distribution that bundles NVIDIA's cuDNN primitives for GPU-accelerated machine learning workloads on CUDA 11 hardware. It is a thin packaging layer that delivers precompiled cuDNN binaries—you import it to ensure the runtime libraries are available to downstream frameworks that depend on cuDNN for their GPU operations.

The package targets developers building or deploying deep learning applications on NVIDIA GPUs. It handles the complexity of distributing platform-specific binary libraries (separate wheels for Linux and Windows) and manages the dependency chain through nvidia-cublas-cu11. Installation requires a compatible NVIDIA GPU and drivers; the package itself is not a high-level API but rather a prerequisite that other libraries consume.

Use it for:

- Ensuring cuDNN primitives are available in containerized deep learning environments.
- Providing GPU-accelerated neural network operations for research or production ML pipelines.
- Bundling with custom CUDA applications that directly call cuDNN functions.
- Supporting deep learning frameworks that require cuDNN on CUDA 11 hardware.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides cuDNN runtime libraries for GPU-accelerated deep neural network operations on NVIDIA CUDA 11 hardware.

Yes, if you are building or deploying deep learning workloads on NVIDIA GPUs with CUDA 11 and your framework requires cuDNN. No, if you do not have compatible NVIDIA hardware or are using a different CUDA version. Be aware: the proprietary license terms are unclear in the fact sheet, so verify NVIDIA's licensing requirements for your use case before production deployment. The aging maintenance status (434 days) warrants checking whether CUDA 11 is still actively supported.

## Install

pip install nvidia-cudnn-cu11
uv add nvidia-cudnn-cu11
poetry add nvidia-cudnn-cu11

## Installing nvidia-cudnn-cu11

Before you install: Medium install friction due to platform-specific wheels (Linux x86_64 and Windows x64 only). Maintenance status is aging—last release was 434 days ago, though the package continues to receive updates. Depends on nvidia-cublas-cu11.

License in practice: Licensed under a proprietary NVIDIA license (LicenseRef-NVIDIA-Proprietary) with unclear treatment. Users should review NVIDIA's licensing terms before deploying in production or commercial contexts.

Quickstart:

pip install nvidia-cudnn-cu11==9.10.2.21

import nvidia_cudnn_cu11

Requires NVIDIA CUDA 11 compatible GPU and drivers; only available for Linux x86_64 and Windows x64 platforms.

Verify before relying:

- Whether the package includes documentation or examples for using cuDNN primitives.
- Current status of NVIDIA's proprietary license terms and any restrictions on commercial use.
- Whether aging maintenance (434 days since last release) signals end-of-life or stable long-term support.

## Package facts

- License: LicenseRef-NVIDIA-Proprietary (unclear)
- Python support: supports_current
- Install friction: medium
- Maintenance: aging
- Downloads: 2.5M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

cudnn gpu acceleration, nvidia deep learning primitives, cuda neural network libraries, gpu tensor operations, nvidia cudnn runtime, gpu-acceleration, cuda, deep-learning

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