Google Open-Sources TorchTPU, Enabling Native PyTorch on TPUs Without Code Rewrites

On October 20, 2026, Google announced that TorchTPU, its long-awaited version of PyTorch, is now available as an open-source project. This tool allows artificial intelligence applications to run natively on Google's Tensor Processing Units (TPUs) and Google Cloud without requiring developers to rewrite their code. The launch marks a significant step by Google, joining Amazon in an effort to break Nvidia's stranglehold on the AI industry, where most applications are traditionally written to run on Nvidia's GPUs.

PyTorch is the popular open-source toolkit used by approximately 85% of AI apps for building, training, and running models. Originally developed by Meta in 2016 when Nvidia GPUs were already the standard for AI research, many of PyTorch's features were designed specifically for Nvidia hardware. In 2022, Meta transferred PyTorch to the Linux Foundation. TorchTPU lowers the barrier for moving existing applications to TPUs and Google Cloud through simple configuration changes.

The day prior, Amazon released its own equivalent tool, TorchNeuron, which enables porting AI apps to Amazon's Trainium chips and AWS without rewriting. Amazon also stated it is submitting code to the main PyTorch project to decouple features from Nvidia chips, making the framework more hardware-agnostic. Google claims it worked directly with Meta, Hugging Face, and makers of vLLM and SGLang to ensure TorchTPU's compatibility with these popular development tools. Additionally, Google launched a dedicated 'TPU agent suite' to assist with migration and error fixing, and updated its LiteRT tool for better PyTorch support.