Abstract: The macroalgae, including Sargassum muticum (labeled as SM), Sargassum thunbergii (ST), Sargassum horneri (SH) and Sargassum pallidum (SP), are common Sargassum species distributed in the intertidal zone of Yellow Sea and Bohai Sea in China. These Sargassum species serve as essential components of seaweed beds, creating an optimal habitat for marine life, playing an important role in the conservation of fishery resources, marine eutrophication, and improvement of the ecological environment in coastal waters. The close interactions between macroalgae and their epiphytic microorganisms have a significant impact on the growth and development of the host macroalgae. Consequently, describing the microbial diversity associated with Sargassum species is an essential step towards a comprehensive understanding of gulfweed ecosystem dynamics. Previous studies primarily focused on individual Sargassum species, leaving a notable gap in the comparison of microbial diversity among closely related sympatric host species. In this study, the epiphytic microbial communities on four sympatric Sargassum species (SM, ST, SH, and SP) and the overlaying seawater (labeled as W) were investigated by high-throughput sequencing of 16S rRNA for the first time. The results showed that a total of 8793 ASVs were obtained from 15 samples, only 12 ASVs were shared between macroalgae and water sample groups. ST displayed the highest number unique ASVs among Sargassum groups. The alpha diversity analyses showed that the microbial richness and diversity were obviously higher in water than that in macroalgae. Comparing the Sargassum groups, ST displayed the highest Shannon and Chao 1 values. The NMDS analysis showed that replicates exhibited high similarity, except for the SH group, as the microbial communities in macroalgae and water groups formed clear separate clusters. Further PERMANOVA analysis confirmed no significant differences between Sargassum groups (P>0.05). The composition of microbial communities on macroalgae were assessed at both the phylum and genus levels. Dominant phyla included Proteobacteria, Bacteroidota and Firmicutes varied from 80.39% to 94.54%. At genus level, the microbial communities differed between macroalgae and water samples, with common predominant genera across all sample groups, such as Yoonia-Loktanella (from 2.46% to 12.10%), Rikenellaceae_RC9_gut_group (2.54% to 7.02%) and UCG-005 (2.84% to 7.96%). Some genera presented the host-specificity character, e.g. Acaryochloris_MBIC11017, Aeromicrobium and Stenotrophomonas were unique in SM, SP, and ST, respectively. The distribution and abundance percentage of the 10 most abundant ASVs in the four Sargassum groups were more distinct. LEfSe was used to discover and interpret the high taxa biomarkers, resulting in the identification of 18 biomarkers, including 9 of W, 4 of SH, 3 of SM and 2 of ST. MetaStat analysis showed that the microbial community differences among the four Sargassum groups were mainly concentrated in SM and the other three Sargassum groups. The metagenome function prediction of macroalgae was carried out using Tax4Fun software, predicting six primary level biological functional pathways. These pathways mainly included metabolism, genetic information processing, environmental information processing and cellular processes, with metabolism being the prominent common function in Sargassum groups. A total of 44 ecological functions were summarized at level 2, and Carbohydrate metabolism (10.71% to 11.13%) was the highest in abundance in all sample groups. This study provides valuable theoretical basis for further understanding the ecological effects of Sargassum by comparing the epiphytic microbial communities on four species of Sargassum.