SAN FRANCISCO, Oct. 22, 2025 — The PyTorch Foundation, a community-driven hub for open source AI under the Linux Foundation, today announced that it has welcomed Ray as its newest foundation-hosted project. Originally developed by Anyscale, Ray is an open source distributed computing framework for AI workloads, including data processing, model training and inference at scale.
In the race to make AI a key differentiator, engineering teams are often hampered by complexity and wasted compute due to hand-built, fragmented systems, steepening the path to production. Created to eliminate distributed computing bottlenecks, which slow down AI innovation, Ray complements PyTorch and vLLM and offers teams a seamless way to execute data processing, model training, and serving workloads from a single machine to thousands of nodes. Since its development at UC Berkeley, Ray now has over 39,000 GitHub stars and more than 237 million downloads.
“The PyTorch Foundation is committed to fostering an open, interoperable, and production-ready AI ecosystem,” said Matt White, GM of AI at the Linux Foundation and Executive Director of the PyTorch Foundation. “By bringing Ray under the PyTorch Foundation umbrella, alongside projects like vLLM and DeepSpeed, we are uniting the critical components needed to build next-generation AI systems. Ray’s inclusion strengthens our collective mission to support developers with the tools to efficiently train, serve, and deploy AI models at scale.”
Ray addresses the unique computational demands of modern AI by providing a compute framework that executes distributed workloads including:
Multimodal data processing: handles massive, diverse datasets (text, images, audio, video) in parallel, with efficiency.
Pre-training and post-tuning: scales PyTorch and other ML frameworks across thousands of GPUs for both pre-training and post-training tasks.
Distributed inference: serves models in production with high throughput and low latency, orchestrating bursts of dynamic, heterogeneous workloads across clusters.
By contributing Ray to the PyTorch Foundation, Anyscale reinforces its commitment to open governance and long-term sustainability for Ray and open source AI.
“With Ray, our goal is to make distributed computing as straightforward as writing Python code,” said Robert Nishihara, co-founder of Anyscale. “Joining the PyTorch Foundation helps us stay true to that mission, ensuring Ray continues to be an open, community-driven backbone for developers and their organizations.”
With PyTorch for model development, vLLM for inference, and Ray for distributed execution, these projects now form an integrated open source foundation for AI. These unified layers allow teams to build and scale applications more efficiently without fighting disparate infrastructure or being locked into proprietary tools.
Developers and contributors that are interested in participating in the project are encouraged to attend Ray Summit 2025 in San Francisco from November 3-5, 2025. To follow Ray’s development, and join the growing ecosystem, visit https://github.com/ray-project/ray.
About the PyTorch Foundation
The PyTorch Foundation is a community-driven hub supporting the open source PyTorch framework and a broader portfolio of innovative open source AI projects. Hosted by the Linux Foundation, the PyTorch Foundation provides a vendor-neutral, trusted home for collaboration across the AI lifecycle—from model training and inference, to domain-specific applications. Through open governance, strategic support, and a global contributor community, the PyTorch Foundation empowers developers, researchers, and enterprises to build and deploy AI at scale. Learn more at https://pytorch.org/foundation.
About the Linux Foundation
The Linux Foundation is the world’s leading home for collaboration on open source software, hardware, standards, and data. Linux Foundation projects are critical to the world’s infrastructure, including Linux, Kubernetes, LF Decentralized Trust, Node.js, ONAP, OpenChain, OpenSSF, PyTorch, RISC-V, SPDX, Zephyr, and more. The Linux Foundation focuses on leveraging best practices and addressing the needs of contributors, users, and solution providers to create sustainable models for open collaboration. For more information, please visit us at linuxfoundation.org.
Source: PyTorch