Gavin Baker: open-weight models compress margins but boost AI infra demand
RihardJarc · x · 2026-10-09
Gavin Baker argues open-weight models that compress margins at the model layer are net positive for AI infrastructure demand: an open-weight token consumes roughly the same compute as a frontier token of similar size, so hyperscalers still capture the compute spend.
Related event: Open-Weight Models Squeeze Model Margins but Boost Compute Demand(3 posts)→
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