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May 13, 2025 in Blog

PyTorch/XLA 2.7 Release Usability, vLLM boosts, JAX bridge, GPU Build

PyTorch/XLA is a Python package that uses the XLA deep learning compiler to enable PyTorch deep learning workloads on various hardware backends, including Google Cloud TPUs, GPUs, and AWS Inferentia/Trainium.…
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May 12, 2025 in Blog

MetaShuffling: Accelerating Llama 4 MoE Inference

Mixture-of-Experts (MoE) is a popular model architecture for large language models (LLMs). Although it reduces computation in training and inference by activating fewer parameters per token, it imposes additional challenges…
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May 7, 2025 in Blog

PyTorch: The Open Language of AI

Key takeaways: PyTorch today powers the generative AI world with major AI players like Meta, OpenAI, Microsoft, Amazon, Apple and many others building cutting edge AI systems. PyTorch has evolved…
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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.

EXPLORE BENEFITS

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 PyTorch requires Python 3.9 or later.

PyTorch Build
Your OS
Package
Language
Compute Platform
Run this Command:
PyTorch Build
Stable (2.7.0)
Preview (Nightly)
Your OS
Linux
Mac
Windows
Package
Pip
LibTorch
Source
Language
Python
C++ / Java
Compute Platform
CUDA 11.8
CUDA 12.6
CUDA 12.8
ROCm 6.3
CPU
Run this Command:
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
Previous versions of PyTorch

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.

READ CASE STUDIES
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.