Software fuzzing is a strong testing technique that has become the de facto approach for automated software testing and software vulnerability detection in the industry. The random nature of fuzzing makes monitoring and understanding the behavior of fuzzers difficult. In this paper, we report the development of Fuzzer Mutation Visualizer (FMViz), a tool that focuses on visualizing byte-level mutations in fuzzers. In particular, FMViz extends American Fuzzy Lop (AFL) to visualize the generated test inputs and highlight changes between consecutively generated seeds as a fuzzing campaign progresses. The overarching goal of our tool is to help developers and students comprehend the inner-workings of the AFL fuzzer better. In this paper, we present the architecture of FMViz, discuss a sample case study of it, and outline the future work. FMViz is open-source and publicly available at https://github.com/AftabHussain/afl-test-viz.