Google's strategy isn't just to sell AI chips; it's a platform play. By offering its powerful and potentially cheaper TPUs to companies, Google can create a powerful incentive for those customers to run their entire AI workloads on Google Cloud, creating a sticky, integrated ecosystem that challenges AWS and Azure.

Google is offering its TPUs externally for the first time as a strategic move to gain market share while it has a temporary hardware advantage over Nvidia. This classic tactic aims to build a crucial install base that can be upgraded later, even after its competitive performance edge inevitably narrows.

In a significant strategic misstep, Google sold a large volume of its custom TPU accelerators to rival Anthropic. Immediately after, demand for Google's own Gemini model surged, leaving Google compute-constrained and trying to secure more capacity from a sold-out TSMC.

Google Cloud's impressive growth is attributed to servicing the massive compute needs of Anthropic, a company it heavily invested in. This highlights a circular dynamic where cloud providers fund AI companies, which in turn become their captive, high-margin customers for GPUs and TPUs.

Anthropic is pioneering a new hardware strategy. Instead of just renting Tensor Processing Units (TPUs) from Google Cloud, it is buying the chips directly from co-designer Broadcom. This gives Anthropic more control over its infrastructure, a significant move away from the standard cloud-centric model for AI companies.

While competitors pay Nvidia's ~80% gross margins for GPUs, Google's custom TPUs have an estimated ~50% margin. In the AI era, where the cost to generate tokens is a primary business driver, this structural cost advantage could make Google the low-cost provider and ultimate winner in the long run.

Google's cloud division (GCP), incentivized to sell compute, is allocating scarce TPU chips to external customer Anthropic. This directly constrains Google's own AI lab, Gemini, hindering its progress in the hyper-competitive AI race and revealing significant internal friction between business units with conflicting goals.

Google Cloud's growth is dramatically outpacing rivals, fueled by a 400% year-over-year increase in its backlog. The key is its integrated model, selling its entire AI stack from custom TPU infrastructure to Gemini apps. This full-stack approach is resonating strongly with enterprise customers.

Google's internal TPU hardware is competitive with NVIDIA's. If Google sold these chips on the open market, instead of just as cloud instances, that business could theoretically exceed its current valuation. However, a massive cultural and organizational overhaul prevents this strategic pivot.