How to Install Pytorch on Windows in 2025?

PyTorch Installation Guide

How to Install PyTorch on Windows in 2025: A Step-By-Step Guide

In recent years, PyTorch has rapidly become one of the most preferred machine learning frameworks thanks to its dynamic computational graph support and efficient execution. As of 2025, installing PyTorch on Windows has become easier and more optimized for various use cases. In this guide, we will walk you through the straightforward steps to install PyTorch on a Windows system effectively.

Step 1: Verify System Requirements

Before the installation, ensure that your Windows machine meets the following requirements:

  • Windows 10 or later version.
  • Python 3.8 or higher installed.
  • Adequate processor and memory to handle machine learning workloads.

Step 2: Install Python

If Python is not already installed on your machine, download the latest version from the official Python website. During installation, make sure to select “Add Python to PATH.”

Step 3: Install PyTorch via Conda or Pip

For a seamless installation experience, you can choose between Conda or Pip. Both package managers are well-suited for PyTorch installation.

Using Conda

  1. Install Anaconda or Miniconda from the official website.
  2. Open the Anaconda Command Prompt.
  3. Execute the following command for a GPU or CPU-based installation:
   conda install pytorch torchvision torchaudio cudatoolkit=11.7 -c pytorch

Using Pip

  1. Open the Command Prompt as an Administrator.
  2. Execute the following pip command for installation:
   pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117

Step 4: Verify Installation

To ensure PyTorch is successfully installed, open Python from the Command Prompt and run:

import torch
print(torch.__version__)

A version number confirmation indicates that the installation was successful.

Additional Resources

Once PyTorch is installed, you can explore advanced functionalities such as:

By following these steps, you should have PyTorch up and running on your Windows machine, ready to handle all your machine learning and deep learning needs in 2025. “`

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