Although leaves have to accommodate markedly different metabolic flux patterns in the light and the dark, models of leaf metabolism based on flux-balance analysis (FBA) have so far been confined to consideration of the network under continuous light. An FBA framework is presented that solves the two phases of the diel cycle as a single optimization problem and, thus, provides a more representative model of leaf metabolism. The requirement to support continued export of sugar and amino acids from the leaf during the night and to meet overnight cellular maintenance costs forces the model to set aside stores of both carbon and nitrogen during the day. With only minimal constraints, the model successfully captures many of the known features of C 3 leaf metabolism, including the recently discovered role of citrate synthesis and accumulation in the night as a precursor for the provision of carbon skeletons for amino acid synthesis during the day. The diel FBA model can be applied to other temporal separations, such as that which occurs in Crassulacean acid metabolism (CAM) photosynthesis, allowing a system-level analysis of the energetics of CAM. The diel model predicts that there is no overall energetic advantage to CAM, despite the potential for suppression of photorespiration through CO 2 concentration. Moreover, any savings in enzyme machinery costs through suppression of photorespiration are likely to be offset by the higher flux demand of the CAM cycle. It is concluded that energetic or nitrogen use considerations are unlikely to be evolutionary drivers for CAM photosynthesis.Photosynthetic metabolism continues to be studied intensively because of its importance for crop performance and the global carbon cycle in relation to climate change. The metabolic pathways and enzymes involved in carbon fixation and related metabolic processes, such as the synthesis of Suc and starch, have been wellcharacterized. However, it is apparent that full appreciation of leaf metabolism requires these metabolic processes to be placed in the context of the wider metabolic network (Szecowka et al., 2013). This is particularly important for predicting how strategies for engineering improved photosynthesis (Maurino and Weber, 2013) may affect network properties, such as redox and energy balancing (Kramer and Evans, 2011).Flux balance analysis (FBA) has emerged as the method of choice for predicting fluxes in large metabolic network models (Sweetlove and Ratcliffe, 2011), and several flux balance models have explicitly considered photosynthetic metabolism in a variety of plants species and microorganisms, including cyanobacteria (Synechocystis sp. PCC 6803; Knoop et al