In recent years, there has been a significant increase in the demand for environmentally sustainable machining processes to minimize the extravagant use of traditional cutting fluids, thereby reducing their detrimental impact on the environment and the operator's health. This experimental study aims to improve the Minimum Quantity Lubrication (MQL) sustainable approach's efficiency while machining AISI 304 austenitic stainless steel with a carbide insert. Optimum turning parameters were attained through the genetic algorithm (GA) optimization method based on response surface methodology (RSM) models. Present work has claimed the superiority of hybrid nanofluid MQL turning over MQL and nanofluid MQL turning operations. The most prominent achievement of this study is the improvement of surface roughness by 20.29% and 5.17% under hybrid nanofluid MQL compared to MQL and nanofluid MQL conditions, respectively. Similarly, hybrid nanofluid MQL slightly reduced cutting force by 2.36% and 0.83% over MQL and nanofluid MQL conditions, respectively. It is worth mentioning that the adding of nanoparticles in cutting fluid enhances the MQL turning efficiency in the machining of AISI 304 stainless steel.