Comprehensive, large-sample hydrological datasets, such as CAMELS (Catchment Attributes and MEteorology for Large-sample Studies), have provided the basis for advances in many aspects of hydrological research in recent years. They can be utilised for several purposes, such as training or calibrating hydrological models, comparisons between regions dominated by different types of hydrological processes and testing of general validity of hydrological theories. The value of these datasets is in combining a multitude of data sources into one easily accessible and usable, harmonised high-quality package. We present CAMELS-FI, an extensive dataset for 320 catchments in Finland. It combines hydrological and meteorological time series with biophysical and human influence catchment attributes in a format that enables comparisons between catchments within the dataset but also between earlier CAMELS datasets. CAMELS-FI includes a diverse set of catchments with human influence varying from near natural to heavily regulated. CAMELS-FI is available at https://doi.org/10.5281/zenodo.15853357 (Seppä et al., 2025).