Make a Video Call with LLM: A Measurement Campaign over Five Mainstream Apps

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Authors: Jiayang Xu, Xiangjie Huang, Zijie Li, Zili Meng
Cited by: 2
References: 7

Abstract

In 2025, Large Language Model (LLM) services have launched a new feature-AI video chat-allowing users to interact with AI agents via real-Time video communication (RTC), just like chatting with real people. Despite its significance, no systematic study has characterized the performance of existing AI video chat systems. To address this gap, this paper proposes a comprehensive benchmark with carefully designed metrics across three dimensions: quality, latency, and internal mechanisms. Using custom testbeds, we further evaluate five mainstream AI video chatbots with this benchmark. This work provides the research community a baseline of real-world performance and identifies unique system bottlenecks. In the meantime, our benchmarking results also open up several research questions for future optimizations of AI video chatbots.

Fields of Study & Subjects

AI in Service Interactions Usability and User Interface Design Speech and dialogue systems

Publication details

Journal / source
Proceedings of the 36th Workshop on Network and Operating System Support for Digital Audio and Video
Publisher
ACM
Pages
148–154
Publication date
4 April 2026
Language
EN