Google's Ironwood: Its Most Powerful AI Chip Yet

Google just dropped a hardware bombshell: Ironwood, its most powerful AI processor yet. Designed to push Gemini’s capabilities into uncharted territory, this 7th-gen TPU isn’t just an upgrade, it’s a quantum leap for AI inference. Here’s why it matters.

Ironwood by the Numbers

• 9,216-chip clusters (liquid-cooled)
• 42.5 exaflops of inferencing power per pod
• 4,614 TFLOPS/chip (FP8 precision)
• 192GB memory/chip (6x more than Trillium TPU)
• 7.2 Tbps memory bandwidth (4.5x boost)

For context, one Ironwood pod outperforms segments of the world’s fastest supercomputers by 24x, according to Google. (Though skeptics note their benchmark comparisons are… creative.)

Why Google Built This Beast

Ironwood isn’t just about raw power, it’s engineered for agentic AI:
🔹 Simulated reasoning ("thinking" in Google-speak)
🔹 Proactive data gathering (AI that acts autonomously)
🔹 Massively scaled context windows

Translation: Future Gemini versions could analyze, decide, and execute tasks with near-human fluidity.

Liquid-Cooled Superclusters

The real magic lies in Ironwood’s scalability:

• 256-chip servers for developers
• Full 9,216-chip pods for Google’s heaviest workloads

Each pod uses a revamped Inter-Chip Interconnect (ICI) to minimize latency, critical for complex AI workflows.

The Fine Print

• FP8 precision benchmarks dominate, but rival chips (like AMD’s MI300X) use different standards.
• Google skipped TPU v6 comparisons, noting Ironwood succeeds v5p, not Trillium.
• Real-world gains? Likely 2x efficiency over last-gen TPUs.

What This Means for AI

With Gemini 2.5 still running on older TPUs, Ironwood sets the stage for:
🚀 Gemini 3.0’s "reasoning" upgrades
🌐 Cloud AI accessible via Google’s Vertex platform
💡 Startups leveraging near-supercomputer power

One thing’s clear: The age of inference has arrived and Google’s betting big on hardware to lead it.