The AI landscape is dominated by massive language models (LLMs), but bigger isn’t always better. Small Language Models (SLMs) are emerging as powerful, efficient, and cost-effective alternatives, especially when combined with Retrieval-Augmented Generation (RAG). But when should you choose an SLM over an LLM?
In this session, we’ll explore the real-world advantages of SLMs, from faster inference and lower computational costs to improved privacy and customization. We’ll break down scenarios where SLMs outperform their larger counterparts and demonstrate a high-performing RAG pipeline that enables an SLM to function like an LLM.
Sometimes, small is the smarter choice.