Our research at the Distributed Systems Laboratory of the University of Washington Bothell seeks to develop and release an agent-based simulator (Multi-Agent Spatial Simulation C++) for researchers in various fields such as in biology, business/industry, and economics/social sciences. Researchers already use agent-based modeling techniques; where the chosen micro-behavior for agents produce the simulation’s macro-behavior. For example, the life-cycle of a mosquito agent is a chosen micro-behavior a researcher would use to model the spread of disease in a city. Which contrasts with the assumed macro-behavior in differential equation based simulations. However, researchers do not use a universal application that is easily programmable, but instead have the overhead of learning how to use other dedicated applications. My objective is to utilize the identified core logic of new agent-based models by coding them as a benchmark test program, further improving the in-house simulator through the benchmark analysis. The benchmark analysis will compare speed, performance efficiency, and scalability with RepastHPC and FLAME. RepastHPC and FLAME will be considered the alternatives because of their known popularity and usability in the research of agent-based modeling. We expect and have already found that not all applications will be capable of being directly ported because of factors such as an agent’s micro-behavior, how agents communicate, even how the topology is constructed. Where a topology is how the system arranges the environmental elements such as in slices of a 2D plane, or a network of connected nodes. This information can be used to improve the in-house simulator’s library for future releases. Additionally, with the benchmark analysis we can determine empirically whether or not the in-house simulator is a better alternative for researchers.