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Developers · Updated 20 Oct, 10:19 pm IST

Google adds TorchTPU support to TorchTitan for Cloud TPUs

Image: Google Developers Blog

Why it matters for readers: It shows Google is making TPUs easier to use with mainstream PyTorch workflows, not just JAX.

  • PyTorch now has a native TPU backend accessible via torch.device("tpu").1
  • Google published a TorchTitan TPU fork that adapts Meta’s TorchTitan for training on Google Cloud TPUs.1
  • The integration reduces the need to rewrite PyTorch code into JAX or use legacy torch_xla, requiring only small changes to device initialization.1
  • TorchTitan on TPU provides production-grade, distributed training recipes for large dense and MoE models such as Llama 3, Qwen 3, and FLUX.1
  • The fork is available on GitHub at https://github.com/google-pytorch/torchtitan/.1
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