Reuters： Anthropic is considering a custom AI chip program， which would move it from renting other companies' compute to trying to control one of the most expensive bottlenecks in AI.

The pressure is simple： training and serving stronger models now depends on scarce chips， and scarcity can slow product growth even when demand is exploding.

Anthropic already uses Google TPUs and Amazon chips， so building its own silicon would not replace those overnight and would more likely give it bargaining power， supply insurance， and hardware tuned for Claude.

The timing is notable because Anthropic says its revenue run rate jumped from about $9B at the end of 2025 to more than $30B in 2026， which raises the value of every compute decision.

A custom chip effort can cost about $500M before mass deployment， because chip design， verification， software support， and manufacturing mistakes are all brutally expensive.