Gas Source Localization (GSL) is a challenging field of research within the robotics community, with high-stakes search-and-rescue applications. Existing methods vary widely and each has its strengths and weaknesses. Comparisons of different methods are limited due to the lack of a broadly adopted and standardized testing methodology. Existing GSL evaluations vary in environment size, wind conditions, and gas simulation fidelity. They also lack photo-realistic rendering for the integration of obstacle avoidance. In this paper, we propose GSL-Bench, a benchmarking tool that can evaluate the performance of existing GSL algorithms. GSL-Bench features high-fidelity graphics and gas simulation, featuring NVIDIA’s^® Isaac Sim and OpenFOAM computational fluid dynamics software (CFD). Realism is further increased by simulating relevant gas and wind sensors. Scene generation is simplified with the introduction of AutoGDM+, capable of procedural environment generation, CFD and particle-based gas dispersion simulation. To illustrate GSL-Bench’s capabilities, three algorithms are compared in six warehouse settings of increasing complexity: E. Coli, dung beetle, and a random walker. Our results demonstrate GSL-Bench’s ability to provide valuable insights into algorithm performance.Site: https://sites.google.com/view/gslbench/