This paper proposes a novel fluid antenna (FA)-enabled mobile edge computing (MEC) scheme to minimize total system delay by leveraging the mobility of FAs to enhance channel conditions and improve computational offloading efficiency. The authors formulate an optimization problem that jointly optimizes computation offloading and antenna positioning, and introduce an alternating iterative algorithm based on the interior point method and particle swarm optimization (IPPSO). Numerical results demonstrate that the proposed scheme significantly reduces total system delay compared to traditional fixed antenna positions, showing improvements in transmission rates and reduced delays. The IPPSO algorithm exhibits robust convergence properties, validating the effectiveness of the proposed method. The study highlights the potential of FA technology in optimizing MEC system performance, particularly in reducing computing and communication delays.This paper proposes a novel fluid antenna (FA)-enabled mobile edge computing (MEC) scheme to minimize total system delay by leveraging the mobility of FAs to enhance channel conditions and improve computational offloading efficiency. The authors formulate an optimization problem that jointly optimizes computation offloading and antenna positioning, and introduce an alternating iterative algorithm based on the interior point method and particle swarm optimization (IPPSO). Numerical results demonstrate that the proposed scheme significantly reduces total system delay compared to traditional fixed antenna positions, showing improvements in transmission rates and reduced delays. The IPPSO algorithm exhibits robust convergence properties, validating the effectiveness of the proposed method. The study highlights the potential of FA technology in optimizing MEC system performance, particularly in reducing computing and communication delays.