  We present OpenVNA, an open-source framework designed for analyzing the
behavior of multimodal language understanding systems under noisy conditions.
OpenVNA serves as an intuitive toolkit tailored for researchers, facilitating
convenience batch-level robustness evaluation and on-the-fly instance-level
demonstration. It primarily features a benchmark Python library for assessing
global model robustness, offering high flexibility and extensibility, thereby
enabling customization with user-defined noise types and models. Additionally,
a GUI-based interface has been developed to intuitively analyze local model
behavior. In this paper, we delineate the design principles and utilization of
the created library and GUI-based web platform. Currently, OpenVNA is publicly
accessible at \url{https://github.com/thuiar/OpenVNA}, with a demonstration
video available at \url{https://youtu.be/0Z9cW7RGct4}.
