Fungal spores are a major component of ambient bioaerosols, contributing to environmental pollution relevant for human health, agriculture, and ecosystem management. Timely monitoring is critical, as spores can rapidly induce infections or allergic responses. Conventional Hirst-type samplers rely on time-consuming microscopic analysis, limiting near real-time reporting. Automated measurement systems offer an alternative, although their counting efficiency across fungal spore sizes and morphologies remains unclear. This study evaluates the performance of the BAA500 and Hirst-type sampler for five fungal spore types grouped by size: small (Cladosporium, Ganoderma), medium (Epicoccum, Polythrincium), and large (Alternaria). After genus data labelling, the BAA500 effectively discriminated all groups. The BAA500 capture efficiency was highest for medium-sized spores, capturing 2.1- and 3.4-fold higher concentrations of Epicoccum and Polythrincium, respectively, whereas small spores were underestimated more than tenfold compared to the Hirst-type sampler. The strongest correlation between devices was observed for Alternaria (ρ = 0.84), but moderate to weak for small spores. These differences likely result from sampler design, airflow rate, and optical processing algorithms. Meteorological factors influenced spore concentrations similarly for both devices, although with different magnitudes. Air temperature explained most of the variability between samplers (BAA500 is temperature-controlled, Hirst is not), and elevated spore concentrations persisted even at temperatures of 30-35 °C. These findings demonstrate the potential of automated systems for fungal spore monitoring, while highlighting the need for size-specific optimization or correction factors to improve exposure assessment across the full bioaerosol spectrum.