windows - What are the recommended Python and CUDA versions for PyTorch 2.5? - Stack Overflow

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I am planning to install PyTorch 2.5 for a deep learning project on a Windows 10 PC with a compatible NVIDIA GPU. I want to ensure that I choose the most compatible versions of Python and CUDA to avoid issues with installation and runtime.

Key Details:

• I am using Miniconda3 for managing my Python environments.
• The current NVIDIA driver version installed on my system is 566.36
• I prefer stable and officially supported configurations for production-level work.

1. Which version of Python is best suited for PyTorch 2.5 to ensure compatibility with its dependencies?
2. Are there any additional dependencies or compatibility considerations I should be aware of (e.g., specific versions of cuDNN)?

What I tried:

I attempted to install PyTorch 2.5 using Conda with a compatible CUDA version. I started by selecting Python 3.13 and installed the CUDA toolkit for version 12.4.

What I expected to happen:

I expected the installation to be smooth, and for PyTorch 2.5 to work with CUDA 12.4 on my GPU, enabling efficient hardware acceleration for deep learning tasks.

What actually happened:

The installation completed without errors, but when I tested PyTorch using torch.cuda.is_available(), it returned False, indicating that the CUDA-enabled GPU wasn't detected. I’m not sure if the Python or CUDA versions I selected are fully compatible with PyTorch 2.5.

I am planning to install PyTorch 2.5 for a deep learning project on a Windows 10 PC with a compatible NVIDIA GPU. I want to ensure that I choose the most compatible versions of Python and CUDA to avoid issues with installation and runtime.

Key Details:

• I am using Miniconda3 for managing my Python environments.
• The current NVIDIA driver version installed on my system is 566.36
• I prefer stable and officially supported configurations for production-level work.

1. Which version of Python is best suited for PyTorch 2.5 to ensure compatibility with its dependencies?
2. Are there any additional dependencies or compatibility considerations I should be aware of (e.g., specific versions of cuDNN)?

What I tried:

I attempted to install PyTorch 2.5 using Conda with a compatible CUDA version. I started by selecting Python 3.13 and installed the CUDA toolkit for version 12.4.

What I expected to happen:

I expected the installation to be smooth, and for PyTorch 2.5 to work with CUDA 12.4 on my GPU, enabling efficient hardware acceleration for deep learning tasks.

What actually happened:

The installation completed without errors, but when I tested PyTorch using torch.cuda.is_available(), it returned False, indicating that the CUDA-enabled GPU wasn't detected. I’m not sure if the Python or CUDA versions I selected are fully compatible with PyTorch 2.5.

• python
• windows
• deep-learning
• pytorch
• cuda

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1 Answer 1

Sorted by: Reset to default -3

when installing PyTorch 2.5 try to use Python versions from 3.9 up to 3.12, because PyTorch 2.5 officially supports Python versions from 3.9 up to 3.12.

CUDA 12.4 is compatible with NVIDIA driver version is 566.36.

For cuDNN cuDNN 9.1.0.70 version is compatible with CUDA 12.4.

For Installation:

1. Create a new virtual environment using conda with python version 3.12.0:

   conda create -n pytorch_env python==3.12.0

2. Activate the env:

   conda activate pytorch_env

3. Install pyTorch with CUDA 12.4:

   conda install pytorch torchvision torchaudio pytorch-cuda=12.4 -c pytorch -c nvidia

4. Now try to verify it:

   print(torch.cuda.is_available())

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