By Andrew Hoblitzell
Publication Date: 2026-10-25 18:00:00
At PyTorch Conference North America 2026 in San Jose, Google and Meta open-sourced TorchTPU, a native PyTorch backend for Google’s Tensor Processing Units (TPUs). Meta, which created PyTorch in 2016, plans to move larger-scale LLM workloads onto TPUs with it, Meta software engineer Zongwei Zhou said in the October 21 keynotes.
TorchTPU replaces PyTorch/XLA, a lazy-tensor bridge from 2020 that, according to the announcement, “required intrusive source-code modifications.” The new backend aims to make porting a model as simple as changing model.to("cuda") to model.to("tpu"). “With TorchTPU, TPUs join GPUs and CPUs as a native option for PyTorch,” Google Cloud wrote in its announcement, co-authored by Bill Jia, VP of engineering for Core ML/AI.
Jia presented the keynote “Workload Fungibility in the Agentic Era: Bringing Native PyTorch to Cloud TPUs” with Zhou, after two talks that framed the demand. Mark Collier, executive director of the…
