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# Google and Oracle are partnering to bring Google TPUs to Oracle Cloud Infrastructure

**[Google Cloud](https://daily.dev/sources/gcp)** · 4 min read · 0 upvotes · 0 comments

## Summary

Google and Oracle are partnering to bring Google TPUs to Oracle Cloud Infrastructure, making OCI the first hyperscaler outside Google to offer them. TPU capacity deployment on OCI starts in 2027. Google's eighth-generation TPUs deliver up to 12.6 PFLOPS of native FP4 compute per chip. The control plane sustains over 97% goodput across thousands of chips on large training runs. The latest generation TPUs deliver up to 80% better performance per dollar for low-latency serving. TorchTPU, Google's native PyTorch stack for TPUs, is now open source on GitHub. Oracle Acceleron networking connects TPU capacity to the rest of OCI.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://cloud.google.com/blog/products/infrastructure/bringing-google-tpus-to-oracle-cloud-infrastructure>

## Questions this post answers

### When will Google TPUs be available on Oracle Cloud Infrastructure?

Google and Oracle plan to deploy TPU capacity on OCI starting in calendar year 2027, making OCI the first hyperscaler outside Google to offer TPUs. The partnership pairs Google's TPU hardware with Oracle Acceleron networking and OCI's liquid-cooled data centers, letting enterprises run training and inference near their existing Oracle database data.

_Teams planning multi-year AI infrastructure budgets can track this rollout timeline on daily.dev._

### How much faster is Google's eighth-generation TPU compared to the original TPU v1?

The eighth-generation TPU delivers up to 12.6 PFLOPS of native FP4 compute per chip, over 100 times TPU v1's 92 TFLOPS, while also achieving up to 2x better performance per watt than the previous generation. A new low-diameter interconnect topology also cuts network hops by more than 50%, improving performance per dollar for low-latency serving by up to 80%.

_Engineers comparing accelerator generations for cost per token can follow these benchmarks on daily.dev._

### Can I run PyTorch workloads natively on Google TPUs?

Yes, TorchTPU is Google's native PyTorch stack for TPUs and is now available as open source on GitHub. It supports tools including vLLM, SGLang, llm-d, TorchTitan, Ray, TorchRec, Hugging Face, and LiteRT, letting teams train, serve, and deploy models on TPUs using their existing PyTorch tooling without rewriting model code.

_Developers porting PyTorch pipelines to new accelerators can keep up with TorchTPU's progress on daily.dev._

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---

Tags: [#cloud](https://daily.dev/tags/cloud), [#pytorch](https://daily.dev/tags/pytorch), [#oracle](https://daily.dev/tags/oracle), [#ai-infrastructure](https://daily.dev/tags/ai-infrastructure)

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