Each Ironwood chip packs 192GB of memory and can work in massive clusters of up to 9,216 chips. Google says it doubles the performance-per-watt compared to its previous chip, Trillium.
The chip specializes in "inference" - running existing AI models rather than training new ones. This focus matters as companies rush to deploy AI applications at scale.
Google built Ironwood specifically for cloud customers who need to run large language models efficiently. The chip includes a specialized core for recommendation systems and ranking tasks.
The launch highlights Google's push to compete with Nvidia, which dominates the AI chip market. Unlike Nvidia's products, Google's chips are only available through its cloud service.
Google plans to integrate Ironwood into its AI Hypercomputer system later this year, though it hasn't named the manufacturer producing the chips.
Why this matters:
- Google joins the race to build specialized AI hardware, challenging Nvidia's grip on the market
- The focus on efficiency shows how running AI has become a major cost for tech companies
Marcus Schuler
