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Plasmids are one of the key drivers of microbial adaptation and evolution. However, their diversity and role in adaptation, especially in extreme environments, remains largely unexplored. In this study, we aimed to identify, characterize, and compare plasmid sequences originating from samples collected from deep-sea hydrothermal vents located in Arctic Mid-Ocean Ridges. To achieve this, we employed, and benchmarked three recently developed plasmid identification tools-PlasX, GeNomad, and PLASMe-on metagenomic data from this unique ecosystem. To date, this is the first direct comparison of these computational methods in the context of data from extreme environments. Upon recovery of plasmid contigs, we performed a multiapproach analysis, focusing on identifying taxonomic and functional biases within datasets originating from each tool. Next, we implemented a majority voting system to identify high-confidence plasmid contigs, enhancing the reliability of our findings. By analysing the consensus plasmid sequences, we gained insights into their diversity, ecological roles, and adaptive significance. Within the high-confidence sequences, we identified a high abundance of Pseudomonadota and Campylobacterota, as well as multiple toxin-antitoxin systems. Our findings ensure a deeper understanding of how plasmids contribute to shaping microbial communities living under extreme conditions of hydrothermal vents, potentially uncovering novel adaptive mechanisms., (© The Author(s) 2024. Published by Oxford University Press on behalf of FEMS.)