The representation of organic aerosol (OA) in global chemistry–climate models remains computationally challenging due to the large number of volatility-resolved tracers required to simulate gas–particle partitioning and aging. We present ORACLE-lite (v3.0), a reduced-complexity version of the ORACLE module implemented within the ECHAM/MESSy Atmospheric Chemistry (EMAC) model, specifically designed for multi-decadal simulations. ORACLE-lite preserves the core mechanisms governing OA formation while employing the minimum number of surrogate tracers required to represent organic compounds across the principal volatility classes, including low-volatility (LVOC), semi-volatile (SVOC), intermediate-volatility (IVOC), and volatile organic compounds (VOC). This structured reduction lowers the computational cost per model time step by a statistically robust speed-up of 13.9 ± 1.1 %, enabling efficient multi-decadal simulations while maintaining a dynamic representation of volatility evolution. ORACLE-lite is evaluated in a 21-year global simulation (2000–2020) and compared against the standard ORACLE configuration. The simplified volatility basis set modifies gas–particle partitioning, leading to enhanced primary organic aerosol (POA) concentrations of up to 5 µg m^-3 over major biomass-burning and industrial regions, while secondary organic aerosol (SOA) concentrations decrease over biomass-burning regions and increase over anthropogenic source regions due to differences in precursor allocation among volatility bins. Model performance is assessed against long-term aerosol mass spectrometer (AMS) and aerosol chemical speciation monitor (ACSM) observations across North America, Europe, and Eastern Asia. Simulated total OA agrees well with observations over North America (normalized mean bias, NMB = −4 %) and Eastern Asia (NMB = −29 %), while larger seasonal biases occur in Europe, particularly in winter. Over tropical and subtropical regions, the model shows an overall underestimation (NMB ≈ −39 %) with substantial regional variability. Across all regions, the model reproduces the observed spatial distribution and seasonal variability of OA mass and its primary and secondary components within a factor of two for the majority of sites. These results demonstrate that ORACLE-lite provides a computationally efficient and physically grounded framework capable of reproducing the key features of global OA variability, making it suitable for long-term chemistry–climate simulations.