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Economics of neolabs: why GPU spend makes frontier-chasing hard

Original titleThe economics of a Neolab.

AISummary

A neolab is a startup of AI researchers that raises large pre-production funding to finance GPU compute, with 1000 GB300s (about 14 NVL72 racks) costing $125-150M over 3 years, roughly 2-2.5MW. That buys about 10^25 FLOPs per quarter, enough for a GPT-4-level model that is 1-2 OOMs behind the frontier for pretraining.

Recouping $10M in training at 50% inference margin would take serving about 10T tokens at a $2/M blended price, so neolabs often pivot to a different model game, proprietary data, or high-revenue niches.

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Source: Deedy · x.comPublished · added here