AMD and Intel announced on October 20, 2026, that they will work together to make it easier to build AI applications on x86 processors. The two chipmakers plan to combine their CPU optimization work for PyTorch in a single open-source library.
PyTorch is a widely used framework for building AI models. The shared work will take place in oneDNN, a deep learning library that helps AI workloads run efficiently on CPUs.
oneDNN is governed by the Unified Acceleration Foundation, also known as UXL. The library is open source, which means developers can view and contribute to its code.
One Software Path for Two Chipmakers
Developers have often dealt with separate software paths to get the best performance from AMD and Intel CPUs. The companies say the new approach will give developers a common path across both brands of processors.
AMD and Intel have agreed that oneDNN will be the default open-source library for x86 acceleration within PyTorch. The goal is to reduce fragmentation in the AI software ecosystem.
The move was recommended by the x86 Ecosystem Advisory Group. The group works on shared technologies for x86 chips.
As part of the effort, AMD is integrating its ZenDNN optimizations into oneDNN. ZenDNN is AMD’s own library for speeding up deep learning on its processors.
AMD has also joined the UXL Foundation as a steering member. The company said this will help advance the work through open collaboration.
“By working with the x86 Ecosystem Advisory Group, we’re bringing the industry together around common technologies that simplify development across x86 processors,” said Robert Hormuth, corporate vice president of Architecture and Strategy at AMD.
What Intel and Partners Are Saying
Intel said the partnership removes the need for developers to manage different software for each chip brand. “Developers shouldn’t have to think about separate software paths to get the best from an x86 CPU,” said Jeff McVeigh, vice president and general manager of Data Center Strategic Programs at Intel.
McVeigh added that working with AMD gives the PyTorch community a consistent approach for modern processors. He said it also creates a way to bring future capabilities into the framework.
Red Hat, a member of the PyTorch community, welcomed the news. Stephen Watt, a vice president and distinguished engineer at Red Hat, called it “a major step forward in eliminating ecosystem fragmentation.”
Watt is also a PyTorch ambassador. He said Red Hat is excited to see this level of open collaboration between the two companies.
For developers, the change means one place to access CPU optimizations for PyTorch. The companies say this should make AI applications easier to build, maintain and deploy across x86 systems.
The two chipmakers are also working together on AI Compute Extensions, known as ACE. ACE is a next-generation instruction set architecture for x86 processors.
ACE is designed to speed up matrix multiplication, a core math operation used in AI workloads. The companies said ACE will be added to PyTorch through future oneDNN updates.
