The complexity of text comprehension demands a computational approach to describe the cognitive processes involved. In this article, we present the computational implementation of the landscape model of reading. This model captures both on-line comprehension processes during reading and the off-line memory representation after reading is completed, incorporating both memory-based and coherence-based mechanisms of comprehension. The overall architecture and specific parameters of the program are described, and a running example is provided. Several studies comparing computational and behavioral data indicate that the implemented model is able to account for cycle-by-cycle comprehension processes and memory for a variety of text types and reading situations.