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Introduction: Empowering the Next Generation of AI Builders We are excited to announce a partnership…

Introduction Torchcomms is a new experimental, lightweight communication API intended for use with PyTorch Distributed…

Introduction to Helion In modern machine learning, the demand for high-performance computation has led to…

TLDR ExecuTorch enables seamless, production-ready deployment of PyTorch models directly to edge devices (mobile, embedded,…

We now live in a world where ML workflows (pre-training, post training, etc) are heterogeneous,…

In this post, we announce torchforge: A PyTorch-native agentic RL library that lets you focus…

What is vLLM V1? In January 2025, the vLLM team announced the alpha release of…

We are excited to announce the release of PyTorch® 2.9 (release notes)! This release features: …

TLDR: Efficient full-parameter fine-tuning of GPT-OSS-20B & Qwen3-14B models on a single NVIDIA GH200 and…

PyTorch now offers native quantized variants of Phi4-mini-instruct, Qwen3, SmolLM3-3B and gemma-3-270m-it through a collaboration…

The Challenge of PyTorch 2.0 Compilation Since the release of PyTorch 2.0 (PT2) and its…

PyTorch 2.8 has just been released with a set of exciting new features, including a…

Intel announces a major enhancement for distributed training in PyTorch 2.8: the native integration of…

As training jobs become larger, the likelihood of failures such as preemptions, crashes, or infrastructure…

In this blog post, we explore the kernel design details presented in the paper Fast…

Large Language Models (LLMs) have transformed tasks across numerous industries, including drafting emails, generating code,…

tldr: 1.22x - 1.28x training acceleration with MXFP8, equivalent convergence compared to BF16. We recently…