Sixth-generation (6G) wireless systems are envisioned to support unprecedented data connectivity demands, thereby necessitating the advent of communication techniques for efficient spectrum utilization and interference mitigation. While conventional non-orthogonal multiple access (NOMA) provides advancements to the connections of IoT devices, rate-splitting multiple access (RSMA) offers superior flexibility in managing co-interference and enhancing the IoT network’ communication performance. Thereby, this article investigates the effectiveness of exploiting RSMA into a system employing unmanned aerial vehicle (UAV)-enabled mobile-edge computing (MEC) for enhanced computation offloading performance within the Internet of Things (IoT) networks. Additionally, the proposed MEC-based system performance critically depends on the reliability of computation offloading under stringent latency constraints. Therefore, the derivation of a closed-form formulation termed successful computation probability (SCP) is leveraged under Nakagami- \(m\) fading channels. Eventually, the precision of the system model is validated through extensive numerical simulations across a wide range of critical parameters. Accordingly, the results provide a comparative evaluation, highlighting the superior computation offloading performance of RSMA compared to NOMA.