Rethinking Scale: Deployment Trade-offs of Small Language Models under Agent Paradigms

ArXi:2604.19299v1 Announce Type: cross Despite the impressive capabilities of large language models, their substantial computational costs, latency, and privacy risks hinder their widespread deployment in real-world applications. Small Language Models (SLMs) with fewer than 10B parameters present a promising alternative; however, their inherent limitations in knowledge and reasoning curtail their effectiveness.