In this talk, a parameterized, SPICE-compatible compact model of a Graphene Nano-Ribbon Field-Effect Transistor (GNRFET) with doped reservoirs is presented. The current and charge models closely match numerical TCAD simulations. In addition, process variation in transistor dimension, edge roughness, and doping level in the reservoir are accurately modeled. This model provides a means to analyze delay and power of graphene-based circuits under process variation, and offers design and fabrication insights for graphene circuits in the future. It is shown that edge roughness severely degrades the advantages of GNRFET circuits; however, GNRFET is still a good candidate for low-power applications.