The metaverse is undergoing repaid evolution with metaverse services emerging as a significant focal point of research across virtual reality, augmented reality, and metaverse social networking. However, a key challenge lies in the scarcity of datasets that accurately represent metaverse services, impeding the advancement of metaverse service technologies and applications. To address this challenge, we have categorized metaverse services into virtual scene services and meta-services. Subsequently, we introduced a metaverse service dataset called “VMeta”. VMeta encompasses comprehensive information about virtual scene services and meta-services, including essential QoS (Quality of Service) data. This dataset serves as a valuable resource for researchers exploring various aspects of metaverse services, with the ultimate goal of enhancing user satisfaction in the metaverse. We have conducted evaluations and tests on VMeta to optimize metaverse QoS. The results demonstrate its substantial value for metaverse service research. Our datasets are available at https://github.com/Gelieziman/VMeta .