Performance tests aim to evaluate the speed of the software under different circumstances. For this purpose, we developed a test code to gauge the visualization performance of ChemPlot for the well-known molecular datasets of sizes between 642 and 41,127 molecules. The performance metrics of ChemPlot on an ordinary personal computer (processor with 2.80 GHz clock speed and 8 GB of RAM) are shown in Table . The data shows the elapsed-time (s) for the two sequential phases of the visualization process. The former is the construction phase, which shows the time spent for converting SMILES notations into numeric multi-dimensional representations. The latter is the reduction phase, which shows the time spent for reducing the multi-dimensions to 2D. We separately executed the reduction phase for the three different algorithms of PCA, t-SNE, and UMAP. The construction phase of the structural similarity is linearly correlated with the size of the dataset and it is about three to six times faster than the tailored similarity. For the largest dataset shown in Table , the construction time is approximately 74 and 453 s for structural and tailored similarities, respectively. In the reduction phase, the elapsed-time for PCA is linearly correlated with the size of the dataset, whereas it is polynomially correlated for UMAP and t-SNE. For the largest dataset, the reduction time using structural similarity was approximately 19, 180, and 429 s for PCA, UMAP, and t-SNE.