Google Open-Sources TorchTPU, a Native PyTorch Backend for Cloud TPUs

Google has released TorchTPU as an open-source native PyTorch backend, enabling developers to run PyTorch workloads directly on Cloud TPUs without requiring the XLA abstraction layer that previously complicated TPU adoption. The release closes a longstanding gap between TPU hardware performance and PyTorch usability, which had kept many ML engineers on GPU-only stacks even when TPUs offered better cost-efficiency at scale. TorchTPU integrates with the standard PyTorch dispatcher, meaning existing PyTorch code can be adapted with minimal changes rather than requiring a full rewrite to JAX or XLA-specific APIs. For teams training large models or running high-throughput inference on Google Cloud, this substantially lowers the barrier to leveraging TPU v4 and v5 hardware. The open-source release also means the community can contribute optimizations and custom kernel support directly.