The article considers the prospect of combining two methodologies of mathematical modeling. The first methodology, based on computational models of general economic equilibrium (CGE models), has been used for modeling the development of economic policies for nearly half a century. These models have self-sufficient methodological bases as well as a solid mathematical apparatus for predicting and solving problems of analysis, forecasting and planning. The second methodology is based on a dynamic model of input-output balance (IUM). The main purpose of the study has been to identify the positive aspects of combining the two models. The CGE models are based on such provisions of neoclassical economic theory as comparative statics, Samuelson's correspondence principle, and the assumption of economic stability. If the growing economies are stable, then it is possible to ensure the objectivity of CGE modeling in terms of the degree of economic growth calculated from the dynamic model of input-output balance. The article highlights the importance of mutual integration of both the general economic equilibrium (CGE models) modeling and dynamic models of input-output balance in solving a multitude of problems. Indeed, CGE models provide flexibility in representing the agents of the modern economy; those models are easily modified and can determine how much the current economic situation differs from equilibrium in all markets. At the same time, dynamic models of input-output balance, written in the form of a system of algebraic and differential equations, open up opportunities for investigating the problems of sustainability and economic growth. We have established that the best results can be obtained through mutual integration of both the general economic equilibrium (CGE) models whose properties can control economic growth with dynamic models of input-output balance. The CGE-IUM complex should not only allow to determine the state of economic equilibrium more reasonably but should help generate the signals for managing the economy that ensure its transition to the so-called cone of main economic growth trajectories and maintaining the corresponding macroeconomic proportions. In this case, the probabilistic nature of the prediction can be divided into qualitatively different trajectories of economic dynamics of macrosystems. We have made an attempt to discuss the issues of mathematical modeling in economics without using mathematical formulas. This is acceptable for a study that only poses a problem for research. The ultimate goal of our project is developing a new class of models of economic systems.