© 2021 by authors.Low Poly Modeling, as one of the most common abstraction methods, initially emerged to maximize the efficiency of the digital modeling process. Besides decreasing the file size, novel designs may develop by simplifying the 3D objects by low poly modeling. There are various simplification methods via different software. In this paper, polygon reduction algorithms named (i) Decimate-Collapse in Blender 2.80, (ii) ProOptimizer in 3dsMax 2019, and (iii) "Clustering Decimation" in MeshLab 2019 are compared through sphere geometry to understand the potential of low poly modeling. Low poly sphere models in different levels of detail are produced from each algorithm. The comparison criteria are (i) geometric change/level of fidelity, (ii) number of polygons, and (iii) file size. Accordingly, algorithms are evaluated within and compared with each other. As a result, 3ds Max ProOptimizer comes forward as the most efficient tool to reduce the file size. Therefore, it is efficient for saving time. Blender Decimate-Collapse is more efficient at preserving the geometry to low levels of detail, so it is the best abstraction method of fidelity. On the other hand, MeshLab Clustering Decimation is more efficient at creating a new form without losing fidelity, but it cannot produce models in every level of detail. As a future study, MeshLab Clustering Decimation has potential in artificial intelligence studies in designing new objects.