Google and Meta open-source TorchTPU, bringing native PyTorch support to TPUs
New backend replaces PyTorch/XLA, aims for one-line model porting; AWS offers similar backend for Trainium
At the PyTorch Conference North America 2026 in San Jose, Google and Meta announced the open-sourcing of TorchTPU, a native PyTorch backend for Google's Tensor Processing Units (TPUs). The backend is designed to replace PyTorch/XLA, a bridge technology that required intrusive code changes, with a simpler interface that allows models to be ported with a change from model.to('cuda') to model.to('tpu').