In terms of generating sustainable energy resources, the prospect of producing energy and other useful materials using cyanobacteria has been attracting increasing attention since these processes require only carbon dioxide and solar energy. To establish production processes with a high productivity, in silico models to predict the metabolic activity of cyanobacteria are highly desired. In this study, we reconstructed a genome-scale metabolic model of the cyanobacterium Synechocystis sp. PCC6803, which included 465 metabolites and 493 metabolic reactions. Using this model, we performed constraint-based metabolic simulations to obtain metabolic flux profiles under various environmental conditions. We evaluated the simulated results by comparing these with experimental results from C-13-tracer metabolic flux analyses, which were obtained under heterotrophic and mixotrophic conditions. There was a good agreement of simulation and experimental results under both conditions. Furthermore, using our model, we evaluated the production of ethanol by Synechocystis sp. PCC6803, which enabled us to estimate quantitatively how its productivity depends on the environmental conditions. The genome-scale metabolic model provides useful information for the evaluation of the metabolic capabilities, and prediction of the metabolic characteristics, of Synechocystis sp. PCC6803.