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Google's models lag in agentic AI usage
Agentic workflows dominance is growing. Organizations can use LLMs for single shot use cases, or agentic use cases, like coding agents.
A good proxy for this is usage of cached tokens as a share of all tokens. We see a nice macro pattern in which businesses tend not to choose Google's models for agentic usage. Google's share of cached tokens is less than half that of it's peers.
This makes sense from my experience. Google has some great vision models, but few engineers I know use Google's models for agentic workflows
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