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How Google Cloud’s Ironwood TPUs and Axion VMs Supercharge AI and ML Workloads

Google Cloud Ironwood TPUs & Axion VMs: A New Era of High-Performance AI Infrastructure

Google Cloud Ironwood TPUs & Axion VMs: A New Era of High-Performance AI Infrastructure

Last Updated: 27 November 2025

Google Cloud AI Infrastructure

Google Cloud has introduced its latest custom silicon innovations: Ironwood TPUs and Axion-based VMs. These technologies significantly enhance AI compute performance and efficiency — ideal for AI researchers, developers, cloud architects, and tech-driven enterprises.

Quick Summary:
Ironwood TPUs deliver a major leap in AI model training + inference performance, while Axion VMs provide powerful, cost-efficient Arm-based compute for production workloads.

Why These New Compute Platforms Matter

AI models are shifting toward real-time agentic behavior — continuously running inside products. This requires:

  • Accelerators for heavy AI math
  • Efficient CPUs to run business logic + data pipelines

Ironwood + Axion together answer that demand.

Ironwood TPUs — The Most Powerful Google TPU Yet

Perfect for training and serving the world’s most advanced AI models.

  • 10× faster peak performance than TPU v5p
  • 4× more compute per chip vs TPU v6e
  • 9,216 chips per TPU pod → exascale compute
  • Huge memory + bandwidth for massive LLMs
  • Optimized for low-latency inference at scale
Ironwood TPUs allow companies to train and deploy larger models faster — at a lower operational cost.

Ideal Workloads

  • Large Language Models (LLMs)
  • Multimodal AI (vision + audio + text)
  • Personalization + Recommender systems
  • Enterprise AI agents

Axion VMs — Efficient Arm Compute for AI Applications

Designed to power everything that surrounds the model.

  • Up to 2× better price-performance vs x86 cloud VMs
  • Fast DDR5 memory + high networking bandwidth
  • Perfect for microservices & orchestration layers

Two Axion Families

  • N4A: Price-optimized compute for cloud apps
  • C4A Metal: Bare-metal Arm for performance-critical workloads

Why They Work Best Together

In real AI systems: TPUs run the model — and CPUs run the product.

  • Axion → APIs, feature stores, pipelines
  • Ironwood → training and real-time inference

This hybrid platform improves:

  • Scalability
  • Reliability
  • Cost efficiency

Who Benefits Most?

  • Startups building AI agents
  • Enterprises deploying LLMs in production
  • Cloud engineers optimizing cost
  • Research labs scaling breakthroughs

Final Thoughts

Google Cloud’s Ironwood TPUs & Axion VMs pave the way for the next stage of AI — bigger models, real-time intelligence, and cost-efficient hyperscale deployment.

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