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The Future of Inference: PyTorch ATX Event
November 26, 2025 in Blog, Community
The Future of Inference: PyTorch ATX Event
On September 17, 2025, PyTorch ATX partnered with the vLLM community and Red Hat to host “The Future of Inferencing” at Capital Factory’s Voltron room in downtown Austin. The gathering…
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OpenReg: A Self-Contained PyTorch Accelerator Simulator
November 21, 2025 in Blog
OpenReg: A Self-Contained PyTorch Accelerator Simulator
Introduction The PyTorch community is actively working to build a growing ecosystem of specialized accelerators by offering a standardized and adaptable way for developers to add custom hardware support. As…
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PINA Joins the PyTorch Ecosystem: A Unified Framework for Scientific Machine Learning
November 18, 2025 in Announcements, Blog
PINA Joins the PyTorch Ecosystem: A Unified Framework for Scientific Machine Learning
Scientific Machine Learning (SciML) is reshaping how complex physical and scientific systems are modelled and simulated. As researchers tackle increasingly sophisticated problems, the need for flexible and scalable tools has…
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Join PyTorch Foundation
As a member of the PyTorch Foundation, you’ll have access to resources that allow you to be stewards of stable, secure, and long-lasting codebases. You can collaborate on training, local and regional events, open-source developer tooling, academic research, and guides to help new users and contributors have a productive experience.
Key Features & Capabilities
Production Ready
Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe.
Distributed Training
Scalable distributed training and performance optimization in research and production is enabled by the torch.distributed backend.
Robust Ecosystem
A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more.
Cloud Support
PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling.
Install PyTorch
Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, builds that are generated nightly. Please ensure that you have met the prerequisites below (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies. You can also install previous versions of PyTorch. Note that LibTorch is only available for C++.
NOTE: Latest Stable PyTorch requires Python 3.9 or later. Latest Preview (Nightly) PyTorch requires Python 3.10 or later.
PyTorch Build
Your OS
Package
Language
Compute Platform
Run this Command:
PyTorch Build
Stable (2.9.1)
Preview (Nightly)
Your OS
Linux
Mac
Windows
Package
Pip
LibTorch
Source
Compute Platform
CUDA 12.6
CUDA 12.8
CUDA 13.0
ROCm 6.4
CPU
Run this Command:
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126
Quick Start With Cloud Partners
Get up and running with PyTorch quickly through popular cloud platforms and machine learning services.
Amazon Web Services
Google Cloud Platform
Microsoft Azure
Lightning Studios
Ecosystem
Featured Projects
Explore a rich ecosystem of libraries, tools, and more to support development.
Captum
Captum (“comprehension” in Latin) is an open source, extensible library for model interpretability built on PyTorch.
PyTorch Geometric
PyTorch Geometric is a library for deep learning on irregular input data such as graphs, point clouds, and manifolds.
skorch
skorch is a high-level library for PyTorch that provides full scikit-learn compatibility.
Companies & Universities Using PyTorch
Amazon Advertising
Reduce inference costs by 71% and scale out using PyTorch, TorchServe, and AWS Inferentia.
Salesforce
Pushing the state of the art in NLP and Multi-task learning.
Stanford University
Using PyTorch’s flexibility to efficiently research new algorithmic approaches.
Docs
Access comprehensive developer documentation for PyTorch
Tutorials
Get in-depth tutorials for beginners and advanced developers
Resources
Find development resources and get your questions answered
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