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PyTorch

Client Challenge PyTorch 2.13 Release Blog – PyTorch Bringing PyTorch Monarch to AMD GPUs: Single-Controller Distributed Training on ROCm – PyTorch Understanding PyTorch’s Test Infrastructure – PyTorch Building the Future of On-Device AI at the ExecuTorch Hackathon – PyTorch Shopify Joins the PyTorch Foundation as a Platinum Member – PyTorch A PyTorch-Native Stack for Large-Scale LLM RL Post-Training – PyTorch Scalable CI for PyTorch’s Out-of-Tree Backends – PyTorch Portable APIs and High-Performance Kernels for Multi-Silicon LLM Inference – PyTorch Serving DeepSeek-V4 on GB300 with SGLang: 5x Higher Throughput at the Same Interactivity Since Day-0 – PyTorch Client Challenge JUST LAUNCHED! PyTorch Certified Associate (PTCA) – PyTorch Client Challenge Nominations Open for the 2026 PyTorch Foundation Contributor Awards – PyTorch A milestone in APAC – PyTorch Portable vLLM Model Inference Kernels in Helion – PyTorch Using Muon Optimizer with DeepSpeed – PyTorch How LinkedIn Uses PyTorch to Solve Extreme-Scale Optimization Problems – PyTorch Why Is PyTorch Compile So Fast: Kernel Fusion – PyTorch Up to 580tps! New Speed Record of Qwen3.5-397B-A17B on GPU for Agentic Workloads with TokenSpeed – PyTorch Alibaba Cloud Joins the PyTorch Foundation as a Platinum Member – PyTorch A Warp-Specialized Blackwell Kernel for Fixed-Block Sparse Self-Attention – PyTorch Join the PyTorch Foundation Ambassador Program: A Global Network of Community Leaders – PyTorch Client Challenge Running PyTorch Models on Apple Silicon GPUs with the ExecuTorch MLX Delegate – PyTorch PyTorch 2.12 Release Blog – PyTorch Efficient Edge AI on Arm CPUs and NPUs: Understanding ExecuTorch through Practical Labs – PyTorch Co-Designing Kernels for RecSys Inference – PyTorch The Case for Disaggregating CPU from GPU in LLM Serving – PyTorch IBM Research uses vLLM at the heart of its RITS Platform – PyTorch Client Challenge
PyTorch Docathon 2026 Results in 150+ Merged Pull Requests – PyTorch
By PyTorch Foundation · 2026-05-20 · via PyTorch

Featured projects

PyTorch Docathon 2026 Top Community ContributorsThank you to everyone who participated in the PyTorch Docathon 2026! Once again, the community showed up with incredible energy and dedication to make PyTorch documentation better for developers everywhere.

The PyTorch Docathon ran from May 5th 2026 through May 19th 2026, bringing together more than 260+ registrants and 30+ active participants. Participants tackled issues across difficulty levels, resulting in over 150 merged pull requests that fixed various issues, added API documentation and contributed to the ExecuTorch documentation.

We want to give a special shout-out to our top contributors, whose dedication and expertise went above and beyond. Your work directly improves the experience for millions of PyTorch users worldwide. See the full list of contributors in the leaderboard.

Meet the top contributors:

First place: ymrohit

Second place: XAheli, PyDevC, darknight054

Third place: JonathanColetti, Kadermiyanyedi

Honorable mentions: AswaniSahoo, Vasanthadithya-mundrathi, Nazim-fad, ozgecinko, kiszk, saurabhkthakur, spzala

As we wrap up this Docathon, we want to remind everyone that great documentation is an ongoing effort. Whether this was your first open source contribution or your hundredth, your work matters. Clear docs lower the barrier to entry and help the entire deep learning community move faster, and shortens the path from research to production in machine learning. And as AI development accelerates, documentation matters even more. LLMs and AI agents increasingly rely on public technical documentation to learn APIs, generate code, and troubleshoot workflows. High-quality PyTorch docs don’t just help humans, they help ensure AI-generated guidance is more accurate, up-to-date, and aligned with best practice.

We encourage you to keep contributing to PyTorch documentation and code.Thank you for being part of this, and we look forward to seeing you at the next one.

Team PyTorch