Deconstructing AI Inference Costs: Why OpenAI and Anthropic May Be More Profitable Than Claimed
By
martinald
A baker's-dozen of insight crammed into one ring.
Summary
The article challenges the common narrative that AI companies like OpenAI and Anthropic are losing money on inference (running AI models at scale). The author uses napkin math based on their experience with cloud economics to deconstruct the real costs of running inference. They argue that the economics might be far more profitable than commonly claimed, suggesting that the margins on inference could be substantial despite widespread claims of it being a "cash incinerator."
Key quotes
· 4 pulledI keep hearing what a cash incinerator AI is, especially around inference.
I haven't seen anyone really try to deconstruct the costs in running inference at scale and the economics really interest me.
This is really napkin math.
My napkin math suggests the economics might be far more profitable than commonly claimed.
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