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arXiv · 2606.30062

Little Brains, Big Feats: Exploring Compact Language Models

Dari Baturova·Elena Bruches·Ivan Chernov·Roman Derunets·Arsenii Fomin·Andrey Kostin
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Abstract

While large language models have been dominating the research landscape recently, small language models remain highly relevant across various domains; yet, they receive far less attention. In this study, we investigate how smaller language models perform during the generation stage within a Retrieval-Augmented Generation (RAG) system. To benchmark these models effectively, we utilised both open-source and proprietary datasets covering diverse subject areas and question types. Our findings demonstrate that a RAG system with small language models can be executed directly on-device without requiring any GPU hardware within a reasonable time. The experimental code and links to the supplementary materials can be accessed through the GitHub repository: https://github.com/SibNN/SLM-RAG-EVAL.

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Dari Baturova, Elena Bruches, Ivan Chernov, Roman Derunets, Arsenii Fomin, Andrey Kostin. 2026-06-29. Little Brains, Big Feats: Exploring Compact Language Models. https://arxiv.org/abs/2606.30062

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