A key goal in psycholinguistics is to quantify real-time language processing effort. A notable amount of literature links the processing effort to the amount of unexpected information carried by the new input. However, such theories fail to capture the dynamic evolution of comprehenders’ interpretation which may involve revision and operate under cognitive constraints. We propose peak information flux, a metric that better captures the cost of reanalysis through a resource rational framework. We characterize language comprehension as continuous belief updating under finite information processing capacity and that the maximal rate of belief change signals language processing effort. We validate the performance of peak information flux on Syntactic Ambiguity Processing and Natural Stories corpora featuring self-paced reading time and a variety of eye-tracking metrics representing different stages of lexical processing. Peak information flux predicts reading behavior across multiple measures and complements surprisal in measures associated with reinterpretation and recovery. Additional analyses reveal that garden-path constructions exhibit delayed and asymmetric information flux dynamics, supporting the hypothesis of a sustained probabilistic revision process. Our model provides an information-theoretic metric for language comprehension under resource constraints.