Comprehensive atmospheric chemical mechanisms for volatile organic compound (VOC) oxidation contain thousands to millions of reactions and species, presenting major computational challenges for large-scale or long-term simulations. As mechanism complexity continues to increase, reduction strategies are required to enable their use in atmospheric modeling while preserving accuracy.</p> <p>This paper presents the GENerator of Optimized Atmospheric chemical mechanisms (GENOA v3), a major advancement over earlier GENOA versions that enables scalable reduction of highly detailed mechanisms containing up to millions of reactions and species. GENOA v3 combines fast, strategy-driven threshold-based reduction (TBR) with simulation-based reduction (SBR) that explicitly controls accuracy. The framework is modular, graph-aware, and user-configurable, resulting in compact and chemically interpretable reduced mechanisms.</p> <p>Applications to GECKO-A mechanisms for diverse VOC precursors across a range of scenarios show that TBR achieves mechanism size reductions of 20&ndash;90 % while preserving reasonable accuracy for metrics related to secondary organic aerosol (SOA) formation and gas-phase chemistry, with performance systematically dependent on precursor structure and chemical complexity across mechanisms. SBR achieves further reductions in mechanism size by several orders of magnitude; when trained with 15 % mean error constraints, SBR produces schemes within 0.02 % of the original size for preservation of SOA mass and 0.05 % when also considering gas-phase reactivity (e.g., OH, O₃, and NO₃).</p> <p>These results demonstrate for the first time that GENOA v3 can reduce highly detailed chemical mechanisms while jointly preserving SOA mass and gas-phase reactivity, achieving substantial size reductions with reasonable accuracy across a wide range of scenarios. Continued application of GENOA v3 and growth of a user community will potentially support the development of libraries of reduced mechanisms and optimized reduction strategy sets tailored to specific modeling applications.