Neither of these is particularly great; I actually prefer ROI-based analyses: carry out the analyses in predefined (independent) regions, either chosen from the hypotheses (e.g., visual or motor regions) or from a full brain parcellation (e.g., Schaefer 2018 https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal).
Very briefly, searchlights can identify focal areas well, but get hard to interpret when areas vary across people or are not focal, e.g. my paper https://www.ncbi.nlm.nih.gov/pubmed/23558106 (and associated blog posts http://mvpa.blogspot.com/search/label/SA%3APPP).
Weight maps can also be incredibly hard to interpret; perhaps even more so than searchlights. I listed some references in a reply on a previous thread NILEARN: Are SVM weights can be useful for group analysis?.