In the race to dominate AI, the most important metric might not be who builds the smartest model. It might be who builds the cheapest one.
Gavin Baker, managing partner and CIO of Atreides Management, has been making a pointed case that Anthropic holds a decisive edge over OpenAI in one of the most consequential dimensions of AI competition: cost per token. Speaking on the Invest Like the Best podcast, Baker laid out a thesis that reframes how investors should evaluate AI labs, and the numbers are striking.
The efficiency gap
Baker’s core claim is that Anthropic burned roughly 80% less capital than OpenAI to reach a similar revenue run rate.
The source of this efficiency advantage, according to Baker, is twofold. Anthropic’s models achieve higher “intelligence density per token,” meaning they extract more useful output from each unit of computation. And they simply use fewer tokens to get the job done.
Claude Opus, Anthropic’s flagship model, reportedly generates around 70% fewer tokens per query compared to earlier iterations. In practical terms, Anthropic can deliver comparable answers to competitors while consuming roughly half as many tokens.
Baker frames this through what he calls the “paro frontier,” a concept describing the optimal balance between intelligence and cost among leading AI developers. The companies currently sitting on that frontier, per Baker’s analysis: Anthropic, OpenAI, and Grok 4.3.
Revenue velocity tells the story
Baker noted that Anthropic added $11B in annualized recurring revenue within a single month.
Baker describes Anthropic as roughly four times more capital efficient than OpenAI. In an industry where companies routinely raise billions in funding rounds, the ability to convert less capital into equivalent or superior commercial outcomes represents a potentially insurmountable structural advantage.
Commentary on LinkedIn in late July 2026 reinforced Baker’s observations, with multiple voices in the investment community echoing the thesis that Anthropic’s efficiency metrics are widening the gap.
What this means for the AI pricing war
OpenAI is reportedly considering drastic price cuts to remain competitive against Anthropic.
Baker’s broader thesis positions token production efficiency as the single most important variable in determining long-term AI winners. The lab that can deliver the most intelligence per dollar spent will compound its advantage over time, reinvesting savings into further model improvements while competitors scramble to keep pace.