6G cellular networks are being developed with the use of Massive multiple-input multiple-output (MIMO) technology, which is advancing data rates and energy efficiency. In order to optimize downlink power allocation in Massive MIMO 6G networks, we present a hybrid genetic algorithm (GA) and Particle Swarm Optimization (PSO) in this research. Through the integration of GA’s exploratory capabilities and PSO’s swift convergence, the hybrid technique proficiently addresses intricate power optimization problems. We evaluate the hybrid GA-PSO’s performance against the independent GA and PSO versions. We discovered through simulations that the hybrid algorithm systematically improves the sum-rate, increases energy efficiency, and lowers transmit power compared to the individual algorithms. These findings highlight the potential of the hybrid approach to meet the high-performance demands of 6G networks, delivering balanced power distribution and optimal system efficiency.