Why are some spatial patterns remembered more easily than others? There are many possible mechanisms underlying spatial working memory function. Here, I explore different mechanisms simultaneously in a single conceptual model. I conduct a large-scale experiment (35.4 million responses used to measure human observers’ spatial working memory across 80,000 patterns) and build a convolutional neural network (CNN) as a benchmark for what is expected to be explainable. I then create a quasi-comprehensive exploration model of spatial working memory (QCE-SWM) based on classic concepts, as well as new notions, including spatial uncertainty, Bayesian integration, out-of-range responses, averaging, grouping, categorical memory, line detection, gap detection, blurring, lateral inhibition, chunking, multiple-spatial-frequency channels, redundancy, response bias, and random guess. This model provides a tentative overarching framework for the mechanisms of spatial working memory. This study has been published in Nature Human Behaviour and can be found on https://doi.org/10.1038/s41562-023-01559-z