The Kepler mission delivered thousands of exoplanets. TESS has already provided over 2,000 candidates, and nearly 100 new confirmed planets, and will deliver many more. At the same time, radial velocity surveys have provided us with many planets of their own, and masses for many transiting planets. With this incredible growth in the population of known exoplanets has come the realization that exoplanets are very diverse, terrestrial planets in particular — creating an urgent need for exoplanet climate modellers to simulate a wide range of planetary climates. However, most 3D climate models are computationally expensive, and take time to learn. While lower-dimensional models are faster, they lack the physical complexity of 3D models. We present ExoPlaSim, a fast and flexible intermediate-complexity 3D model with a convenient Python API, suitable both for HPC clusters and your laptop. This model, based on the PlaSim model for Earth, bridges a gap in the modelling hierarchy, enabling modellers to quickly produce thousands of 3D models across the habitable parameter space, adding complexity to 1D and 2D experiments, and guiding higher-complexity 3D models. I will discuss our efforts to validate the model against higher-complexity 3D models of Earth-like and tidally-locked planets, its overall performance, and showcase the science made possible by ExoPlaSim.