Oracle and Google Cloud are partnering to bring Google Tensor Processing Units (TPUs) to Oracle Cloud Infrastructure (OCI) starting in 2027, making OCI the first non-Google hyperscaler to offer them. Google designed TPUs over a decade ago with a co-design philosophy, integrating custom silicon with optical networking, power delivery, liquid cooling, and compiler software to optimize performance per watt and total cost. Modern TPUs, like the eighth-generation, offer significant computational power and efficiency, serving Google's Gemini models. Beyond raw performance, TPUs emphasize "goodput" for training and low latency/cost per token for inference through system-level co-design. Features like on-die Inter-Chip Interconnect (ICI) routing and Optical Circuit Switching (OCS) ensure high goodput and availability by dynamically rerouting around faults. Enhanced memory and interconnect topology further improve performance per dollar for low-latency serving. Google has also open-sourced TorchTPU, its native PyTorch stack, on GitHub, promoting a developer-friendly ecosystem. This allows developers to use familiar tools and easily port workloads between accelerators for optimal cost and performance. Bringing TPUs to OCI offers several benefits: OCI's data centers are engineered for AI density and liquid cooling, providing flexible capacity. Oracle Acceleron's secure, high-performance networking connects TPU capacity to the rest of OCI. Proximity to Oracle databases allows organizations to run fine-tuning and inference near their enterprise data without costly cross-cloud transfers. Finally, OCI will offer a multi-architecture choice, providing both TPUs and GPUs for optimal workload assignment. This collaboration expands access to purpose-built AI systems, fostering innovation and efficiency across the industry.