Owing to the heterogeneity and high degree of connectivity of various networks, there likely exist multiple available paths between a source and a destination. To be able to simultaneously and efficiently use such parallel paths, it is essential to facilitate high quality network services at high speeds. So, traffic splitting, having a significant impact on quality of services (QoS), is an important means to achieve load balancing. In general, most existing models can be classified into flow-based or packet-based models. Unfortunately, both classes exhibit some drawbacks, such as low efficiency under the high variance of flow size in flow-based models and the phenomenon of packet reordering in packet-based models. In contrast, Table-based Hashing with Reassignment (THR) and Flowlet Aware Routing Engine (FLARE), both belonging to the class of flow-based models, attempt to achieve both efficient bandwidth utilization and packet order preservation. An original flow can be split into several paths. As compared to the traditional flow-based models, load balancing deviation from ideal distribution decreases while the risk of packet reordering increases. In this paper, we introduce analytical models of THR and FLARE, and derive the probabilities of traffic splitting and packet reordering for each model. Our analysis shows that FLARE is superior to THR in packet order preservation. Also, the performance of FLARE on bursty traffic is demonstrated and discussed.