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NVIDIA cuDNN

NVIDIA cuDNN is a free GPU-accelerated library of primitives for deep neural networks, listed as free under the NVIDIA Software License Agreement.

Place
#23 of 35
Score
5.9
NVIDIA cuDNN's website

What NVIDIA cuDNN is

NVIDIA cuDNN is a free GPU-accelerated library of primitives for deep neural networks, listed as free under the NVIDIA Software License Agreement. It supplies tuned implementations for convolution, attention, matrix multiplication, pooling, and normalization. The Graph API models operations as nodes connected by tensor edges, with flexible fusions around matrix multiplication and convolution plus specialized attention and convolution-with-normalization patterns. NVIDIA recommends its open-source Python/C++ Frontend API, while a lower-level C Backend API is also available. cuDNN accelerates frameworks including PyTorch, JAX, Caffe2, Chainer, Keras, MATLAB, MxNet, PaddlePaddle, and TensorFlow. Installation options include pip, Docker, and package managers. The backend supports Linux and Windows, but compatible operating system, CUDA, driver, and NVIDIA hardware versions are required. Only one CUDA Toolkit version of cuDNN 9 can be installed at a time.

Good

  • Free at no cost
  • Tuned deep-learning operation implementations
  • Graph API with fusion support
  • Integrates with many frameworks
  • Linux and Windows backend

Watch out

  • Requires compatible NVIDIA hardware and software
  • Only one CUDA Toolkit version for cuDNN 9
  • License agreement compliance required
  • Platform support excludes other operating systems

Who it suits

cuDNN is for developers building deep-learning software with supported NVIDIA hardware and frameworks. It suits users comfortable checking compatibility and complying with NVIDIA’s license.

Verdict

cuDNN provides operation libraries, graph interfaces, and framework integrations for NVIDIA-based deep-learning development. Compatibility requirements and the CUDA Toolkit installation limit should be checked before setup.

Plans and prices

From NVIDIA cuDNN's own pricing page, checked 11 Oct 2026.

All about pricing
PlanPriceWhat it gives you
NVIDIA cuDNNFreeNVIDIA Software License Agreement applies

The facts

Each one read from NVIDIA cuDNN's own pages, with the date it was checked.

What it does

Framework integrations
NVIDIA lists PyTorch, JAX, Caffe2, Chainer, Keras, MATLAB, MxNet, PaddlePaddle, and TensorFlow among the frameworks cuDNN accelerates.checked 11 Oct 2026
Frontend
NVIDIA recommends its open-source Python/C++ Frontend API for accessing the Graph API, with a lower-level C Backend API also available.checked 11 Oct 2026
Fusion
cuDNN supports flexible fusions around matrix multiplication and convolution, plus specialized patterns such as attention and convolution with normalization.checked 11 Oct 2026
Graph API
The cuDNN Graph API represents operations as nodes and tensors as edges.checked 11 Oct 2026
Installation
NVIDIA provides cuDNN downloads and installation options including pip, Docker, and package managers.checked 11 Oct 2026
Installation limit
Only one CUDA Toolkit version of cuDNN 9 can be installed at a time.checked 11 Oct 2026
License
Downloading and using cuDNN requires compliance with the NVIDIA Software License Agreement.checked 11 Oct 2026
Operations
It provides tuned implementations for convolution, attention, matrix multiplication, pooling, and normalization.checked 11 Oct 2026
Purpose
cuDNN is a GPU-accelerated library of primitives for deep neural networks.checked 11 Oct 2026
Requirements
cuDNN requires compatible operating system, CUDA, driver, and NVIDIA hardware versions, and the current compatibility details are in its support matrix.checked 11 Oct 2026
Security
NVIDIA’s cuDNN page directs users to report security vulnerabilities or NVIDIA AI concerns.checked 11 Oct 2026
Support
NVIDIA provides cuDNN documentation and a developer forum from the product page.checked 11 Oct 2026

Where it runs

Supported platforms
The cuDNN backend is supported on Linux and Windows.checked 11 Oct 2026

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