Meta has a third timing problem: Anthropic and OpenAI have a structural cost advantage in inference that is only increasing, and while Meta is investing in catching up, the frontier labs are already running ahead on both cost and data flywheels.

Thompson argues that Anthropic and OpenAI are accelerating and have a structural cost advantage in inference that is increasing, while Meta is making the kind of investments the frontier labs made in the past, and its data flywheel argument about billions of users echoes Microsoft's irrelevant Windows numbers argument from 15 years ago. ✦ AI generated

Ben Thompson · Stratechery · 2026-08-03 · original ↗

That leads to a third timing problem: right now Anthropic and OpenAI are accelerating and, as I argued a couple of weeks ago, almost certainly have a structural cost advantage in terms of inference that is only increasing. Meta is trying to sell investors on the future while making investments that the frontier labs made in the past. Moreover, those past investments aren't just paying off in terms of margin, but also data: Zuckerberg talked about the importance of data flywheels in the context of model improvements and the company's proven ability to scale out products to billions of people, but that had a whiff of Microsoft 15 years ago talking about a billion Windows computers in the face of the burgeoning smartphone segment. Trajectory and relevance matter more than sheer volume, and Meta does better on the latter than the former.

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