Fit beats size
A compact model that performs one task reliably can be more useful than a general model that is expensive to operate. Classification, extraction and simple routing are common examples where specialization may pay.
The challenge is knowing when a narrow solution has reached its limits and needs escalation.
The edge advantage
Models that run near the user or on local hardware can reduce latency and avoid sending every input to a remote server. But devices impose constraints on memory, heat and battery life.
Techniques such as distillation and quantization make these tradeoffs more manageable.
Architecture over spectacle
Teams increasingly need a portfolio strategy: simple rules when appropriate, small models for routine decisions and powerful models for complex work.
The best AI experience does not advertise how many parameters it used; it delivers the right result efficiently.