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# Google Cloud unveils Ironwood TPU and Axion instances
- URL: https://www.testingcatalog.com/google-cloud-unveils-ironwood-tpu-and-axion-instances/
- Published: 2025-11-06T15:27:47.000Z
- Updated: 2025-11-06T16:43:15.000Z
- Description: Google Cloud unveils Ironwood, its seventh-gen TPU for large AI training and inference, with Axion N4A preview and upcoming C4A metal instances.
- Author: Alexey Shabanov
- Tags: Latest AI News

Google Cloud announced [Ironwood](https://blog.google/products/google-cloud/ironwood-tpu-age-of-inference/?ref=testingcatalog.com), its seventh-generation TPU, along with new Axion instances on November 6\. Ironwood is designed for large-scale training, complex reinforcement learning, and high-volume, low-latency serving. It is expected to reach general availability in the coming weeks. The Axion N4A, an Arm-based virtual machine optimized for price-performance, is currently in preview, and the C4A metal, a bare-metal Arm instance, will soon be available in preview. The target audience includes AI labs, SaaS platforms, and enterprises transitioning their spending from training to inference at scale.

![Ironwood](https://storage.ghost.io/c/2a/1b/2a1b1782-8506-4d7d-bf53-ad3fb52e2a0f/content/images/2025/11/EXTERNAL-Ironwood-Axion-Press-Kit-Google-Docs-11-06-2025_04_26_PM.jpg)

Ironwood significantly increases throughput, offering a 10× peak gain over TPU v5p and more than 4× per-chip performance compared to TPU v6e. A pod can connect up to 9,216 chips via a 9.6 Tb/s Inter-Chip Interconnect and provides 1.77 PB of shared HBM. Optical Circuit Switching allows for rerouting around faults, and pods can scale into multi-pod clusters. Google claims 118× more FP8 ExaFLOPS at the pod level compared to the next competitor, indicating substantial capacity for frontier model serving.

> Our 7th gen TPU Ironwood is coming to GA!   
>  
> It’s our most powerful TPU yet: 10X peak performance improvement vs. TPU v5p, and more than 4X better performance per chip for both training + inference workloads vs. TPU v6e (Trillium). We use TPUs to train + serve our own frontier… [pic.twitter.com/HvNt2VHtFX](https://t.co/HvNt2VHtFX?ref=testingcatalog.com)
> 
> — Sundar Pichai (@sundarpichai) [November 6, 2025](https://twitter.com/sundarpichai/status/1986463934543765973?ref%5Fsrc=twsrc%5Etfw&ref=testingcatalog.com)

Software co-design plays a crucial role: MaxText introduces SFT and GRPO paths; vLLM support enables teams to switch between GPUs and TPUs with minimal configuration changes; GKE Inference Gateway reduces time-to-first-token by up to 96% and serving costs by up to 30%. Early feedback includes Anthropic planning access to up to 1 million TPUs; Lightricks reporting quality improvements in generative AI media; on Axion, Vimeo experienced approximately 30% better transcoding performance, ZoomInfo observed around 60% price-performance gains, and Rise reduced compute by about 20%. The N4A offers up to 64 vCPUs, 512 GB DDR5, and 50 Gbps; the C4A metal is aimed at hypervisors, native Arm development, and large test farms.

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Google’s history of custom silicon development supports this launch. Over a decade, TPUs, YouTube VCUs, and five generations of Tensor processors have been built with system-level co-design. The first TPU was introduced eight years ago, preceding the Transformer. Titanium storage, advanced liquid cooling at gigawatt scale, and approximately 99.999% fleet uptime since 2020 underpin today’s claims for cost, scale, and reliability across the AI Hypercomputer stack. Availability: Ironwood will be generally available in the coming weeks; Axion N4A is in preview now; C4A metal will be in preview soon.

[Source](https://cloud.google.com/blog/products/compute/ironwood-tpus-and-new-axion-based-vms-for-your-ai-workloads?ref=testingcatalog.com)