Google announced Tuesday that TorchTPU, its version of PyTorch for TPUs, is now available as an open-source project, adding a native torch.device("tpu") backend so existing PyTorch training scripts need only minimal device-initialization changes. Google and Meta co-developed TPU-native execution passes inside TorchTitan, and a TorchTitan TPU fork is published on GitHub; Google says it worked with Hugging Face, Inferact (vLLM) and RadixArk (SGLang) on tool compatibility. Google reports vendor benchmarks including about 57% MFU for Llama 3 405B from 128 to 1,024 TPU v7x chips and 32.42% MFU for Qwen3 235B on a single 1,024-chip slice, while Amazon released its own PyTorch variant, TorchNeuron, for Trainium and AWS a day earlier.