This article describes the features of the MAFFT online service for multiple sequence alignment (MSA). With the increasing availability of large biological sequence datasets, the need for sophisticated algorithms and intuitive tools for handling these data has become crucial. The service offers several options for computing large MSAs, including PartTree, DPartree, FFT-NS-1, FFT-NS-2, mafft-sparsecore, G-INS-1, Pileup, and Random chain. Each method has its own advantages and trade-offs in terms of accuracy, speed, and memory usage. The article also provides guidance on selecting suitable MAFFT options based on the characteristics of the input sequences, such as similarity level and sequence length. Additionally, the service includes interactive tools for sequence selection and visualization, which are particularly useful for handling large and potentially low-quality datasets. The article highlights the importance of large MSAs in various biological analyses and provides command-line options for both local and online usage.This article describes the features of the MAFFT online service for multiple sequence alignment (MSA). With the increasing availability of large biological sequence datasets, the need for sophisticated algorithms and intuitive tools for handling these data has become crucial. The service offers several options for computing large MSAs, including PartTree, DPartree, FFT-NS-1, FFT-NS-2, mafft-sparsecore, G-INS-1, Pileup, and Random chain. Each method has its own advantages and trade-offs in terms of accuracy, speed, and memory usage. The article also provides guidance on selecting suitable MAFFT options based on the characteristics of the input sequences, such as similarity level and sequence length. Additionally, the service includes interactive tools for sequence selection and visualization, which are particularly useful for handling large and potentially low-quality datasets. The article highlights the importance of large MSAs in various biological analyses and provides command-line options for both local and online usage.