AI & Enterprise
Agent era accelerates multi-model use; small models set to take larger share
Multi-model use inside generative AI services is already common, with different-sized models dividing work, a Ravlub researcher said. Small models handle routine tasks such as search, information gathering and summarisation, while frontier models take key decisions and generate outputs. As agents spread, repeatedly calling top-performance models can push inference costs higher. He said small models will not replace frontier models, citing scaling, but role-based use of multiple model sizes will expand.
