Elemental sulfur is often used in organic synthesis as its low cost and high abundance make it a highly desirable source of sulfur atoms. However, sulfur’s unpredictable catenation behavior poses challenges to its widespread usage due to difficulties in designing new reactions that can account for its multifaceted reactivity. In order to accurately model sulfur’s mechanisms using computational approaches, it is necessary to identify Density Functional Theory (DFT) methods that are accurate on these systems. This study benchmarks 12 well-known DFT functionals that include local, non-local, and hybrid methods against DLPNO-CCSD(T)/aug-cc-pV(Q+d)Z // MP2/aug-cc-pV(T+d)Z/SMD(MeCN) for the accurate treatment of organic polysulfides, taking cyanide as a nucleophile. Our benchmarking results indicate that the M06-2X and B3LYP-D3(BJ) density functionals are the most accurate for calculating reaction energies, while local functionals performed the worst. For activation energies, MN15, MN15-L, M06-2X, and ωB97X-D are the most accurate. Our analysis of structural parameters shows that all functionals perform well for ground state optimizations except B97D3, while MN15-L and M06-2X performed best for transition structure optimizations. Overall, the four hybrid functionals MN15, M06-2X, ωB97X-D and B3LYP-D3(BJ) appear adequate for studying the reaction mechanisms of polysulfides.