Super duplex stainless steel (SDSS) has been widely applied in the oil, gas, and chemical sectors owing to its remarkable corrosion resistance and high strength. On the other hand, it suffers from poor thermal conductivity and a pronounced work-hardening effect, which leads to significant cutting forces, high temperatures, faster tool wear, and erratic chip formation. In the present research, a nanofluid based on magnetorheological (MR) minimum quantity lubrication process has been proposed for turning SDSS. MR fluids have been produced using jojoba oil as the base fluid with carbonyl iron (CI) particles and n-CuO, n-graphene oxide (GO) as nanoadditives. Different lubrication environments, including dry, flood, minimum quantity lubrication (MQL), and MR-MQL, were experimentally evaluated, and MR-MQL-GO demonstrated superior machining performance. Response surface methodology (RSM) with a Box–Behnken design was used to model and optimize machining parameters, including feed rate, cutting speed, depth of cut, applied current, and complex viscosity. The optimized predicted values were cutting force 337 N, surface roughness 0.92 µm, chip thickness 0.013 mm, cutting temperature 76.5°C, and tool wear 0.027 mm. The experimental validation results were 340 N, 0.95 µm, 0.014 mm, 80°C, and 0.030 mm, respectively. The close agreement confirms the reliability of the RSM model and demonstrates that MR-MQL-GO significantly improves chip control and overall machining performance of SDSS.