This research presents a pioneering plasmonic nanotweezer (PNT) designed in a bowtie configuration utilizing graphene, aimed at markedly improving optical trapping effectiveness at the nanoscale. Through the application of the particle swarm optimization (PSO) algorithm, the optimal geometrical parameters—width of 189.24 nm, length of 234.19 nm, and a gap distance of 6.2 nm—that optimize electromagnetic field localization are determined. The transfer matrix method is employed to simulate electromagnetic wave transmission, while 3D finite-difference time-domain simulations confirm the emergence of intense plasmonic hotspots at the vertices of the bowtie, which generates a trapping force of ≈6 nN W−1 for a bioparticle of 10 nm. The thermal analysis demonstrates a direct relationship between input power density and temperature elevation, achieving an impressive stability threshold of S = 1.32 at a mere 1 mW μm−2—substantially lower than the 6 mW μm−2 typically necessary for conventional gold or silver nanotweezers. Additionally, at an input power of 10 mW μm−2, the stability metric escalates to 13, emphasizing the resilience of the trapping mechanism. This PSO-optimized graphene PNT not only amplifies plasmonic efficacy but also reduces energy consumption, representing a significant advancement in nanoscale optical trapping technologies for bioanalytical purposes.