Increasing worldwide energy demand and diminishing supplies of fossil fuels have necessitated the development and increasing use of new sustainable energy sources, as well as more parsimonious energy use. In the context of agriculture, research has focused predominantly on the production of bio-energy, while only a limited number of studies have investigated the energy use and possible energy saving in conventional agricultural production. In response to this lack in empirical research this study aims (i) to measure the farm-level energy and cost efficiency of conventional agricultural (wheat) production, (ii) to identify the potential for energy saving in conventional agriculture and quantify its shadow cost, (iii) to identify production technologies and managerial practices that reduce total energy use. We adjusted the method by Coelli, Lauwers, Van Huylenbroeck (2007) introducing analogy between cost and nutrient minimization to measure energy use reduction potential and its costs. The analysis was carried out on survey data for 95 farms for production year 2007/08. Energy coefficients for individual non-renewable inputs were derived from the PLANETE methodology (Méthode Pour L'Analyse EnergéTique de l'Exploitation) developed by SOLAGRO. We applied data envelopment analysis to estimate energy and cost optima and efficiencies, and truncated regression to identify statistically significant determinants of energy efficiency. We found significant differences in energy consumption per unit of wheat production among Czech farms - best producers consume 46% less energy per unit of production than average producers, however, from that ca. 30% is due to variation in production conditions. Marked share of energy inefficiency (over 50% of potential energy savings) originates in technical efficiency, which offers simultaneous cost savings. Producing wheat in energy optimum would increase costs by 9% when compared to cost optimum. The largest potential of energy savings was found in fuel, and fertilizers and other chemicals. Regression analysis implies that use of more fuel-efficient machinery or machinery with other energy-saving technical parameters (e.g., higher utility weight) and optimizing material transport could increase energy efficiency, while some commonly applied technological practices (such as conventional soil preparation) have a negative energy efficiency effects.