đ Googleâs New Power Move in AI Hardware
Google is officially stepping into the ring with Nvidia as it launches its most powerful AI chip to date â the seventh-generation Ironwood Tensor Processing Unit (TPU).
Designed to handle the most compute-intensive AI workloads, Ironwood is set to become the backbone for large-scale model training, reinforcement learning (RL), inferencing, and model serving.
After months of testing since April 2025, Ironwood TPUs are finally rolling out for general availability, promising to revolutionize how frontier AI models are trained and deployed.
âď¸ Built for Extreme AI Workloads
According to Googleâs official announcement, Ironwood TPUs are purpose-built for next-gen applications like Google Gemini and Anthropicâs Claude, both of which rely heavily on TPU infrastructure.
Compared to previous generations, Ironwood delivers:
- 10x the performance of the fifth-generation TPU
- 4x the speed of the sixth-gen Trillium chip
Its architecture allows each chip to connect directly to others, forming a âsuperpodâ capable of uniting up to 9,216 TPUs. These are interconnected via Googleâs proprietary Inter-Chip Interconnect (ICI) network operating at 9.6 terabits per second, supported by a staggering 1.77 petabytes of shared high-bandwidth memory.
The result? Virtually zero data bottlenecks â even for the worldâs largest and most complex AI models.
đ¤ The Agentic AI Connection
The timing of Ironwoodâs release couldnât be more strategic. As agentic AI workflows â where AI systems act autonomously to achieve goals â become more prevalent, thereâs a growing demand for tighter integration between compute infrastructure and machine learning acceleration.
Custom silicon like Ironwood enables precisely that:
- Faster coordination between model training and inference
- Greater efficiency for continuous learning systems
- Improved scalability for next-gen AI models
In fact, Anthropic has already committed to utilizing up to 1 million TPUs. According to James Bradbury, Anthropicâs Head of Compute:
âIronwoodâs improvements in both inference performance and training scalability will help us scale efficiently while maintaining the speed and reliability our customers expect.â
đ° Massive Investment, Massive Potential
While Google hasnât disclosed financial details, industry estimates suggest the Anthropic deal could be worth billions of dollars â a clear sign of how valuable custom AI chips have become in the global tech race.
In parallel with Ironwood, Google is also enhancing its Axion family of Arm-based CPUs for general-purpose workloads. The upcoming C4A Metal, its first Arm-based bare-metal instance, will soon enter preview.
đ AI Infrastructure Driving Googleâs Record Growth
The explosion in AI infrastructure demand has directly boosted Alphabetâs financial performance. For the first time, the company reported $100 billion in quarterly revenue (Q3 2025).
Alphabet and Google CEO Sundar Pichai emphasized the role of AI hardware in this growth, stating:
âWe are seeing substantial demand for our AI infrastructure products, including TPU-based and GPU-based solutions. Itâs been one of the key drivers of our growth, and we expect strong continued demand as we invest to meet it.â
đ Conclusion: A New Era of Compute Power
With Ironwood, Google is not just catching up to Nvidia â itâs setting the stage for the next leap in agentic and generative AI. The combination of raw speed, high-bandwidth architecture, and tight integration across compute and inference layers positions Ironwood as a cornerstone in the AI infrastructure landscape.
The message is clear: as the world races toward ever more capable AI, Google wants its TPUs at the center of it all.
đˇď¸ Key Takeaways
- Ironwood TPUs are 10x faster than Googleâs 5th-gen chips.
- Designed for AI model training, reinforcement learning, and inference.
- Up to 9,216 TPUs can be connected in a single superpod.
- Anthropic to access up to 1 million TPUs for Claude models.
- Part of Googleâs broader AI infrastructure expansion, contributing to record $100B quarterly revenue.