Paper Title
Comparative Analysis of Open-Source Multimodal Language Models

Abstract
Multimodal language models (LLMs) have garnered significant interest for their ability to understand and generate text alongside other modalities like images and audio. This paper presents a rigorous comparative analysis of opensource multimodal LLMs and non-open source LLM’s, aiming to assess their performance across various tasks and datasets. We present a comprehensive comparison of open-source multimodal LLMs, leveraging a standardized evaluation. This work empowers researchers and practitioners in NLP and multimodal AI by providing crucial insights for informed decisionmaking. Keywords - Open Source, Multimodal Large Language Model, Vision Language Model, Large Language Model