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• Developing novel multi-level benchmarks. • Identifying benchmarks for electricity and thermal energy for office buildings. • Presentation a base for short/long-term energy efficiency plans. • Analyzing energy efficiency and consumption in details. • Creating a dataset, including building and energy information. Energy benchmarking is an accurate tool to measure, monitor, and reduce end-use energy consumption in the building sector using comparison scenarios. Various studies have applied Bottom-Up energy consumption assessment to compare the energy performance of a group of buildings with a benchmark. The Bottom-Up method mostly relies on simulating an ideal building to develop a benchmark. However, this study has developed a Top-Down energy benchmarking methodology based on the actual energy consumption within a cluster of governmental office buildings. The method presents multi-level benchmarks to provide a detailed policy for improving the energy efficiency of buildings in the short or long-term. In an exploratory study, 26 office buildings in a cold climate region were investigated to identify the multi-level benchmarks. Four general benchmark levels were developed, including the 'Best Practice, 'Good Practice', 'Benchmark', and 'Poor Practice'. In addition, 15 energy efficiency classes were also introduced and applied as a base for developing the 'Energy Performance Certificate' method. The results indicate that the benchmark values for electricity and natural gas are 40 and 252 kWh/m2/yr, respectively, while the total energy benchmark is 292 kWh/m2/yr. According to the benchmarking results, 69% of the case studies were inefficient, 23% were labeled 'C', and no cases were labeled 'A' or 'B'. The multi-level benchmarking system can provide quick and clear guidance for building designers, operators, and government regulation/enforcement agencies; thus, it can apply at local, regional, and international levels. These benchmark levels establish reference points for measuring and rewarding good performance, on the other hand, it recognizes poor-performance buildings and prioritizes them for energy efficiency improvement. The method can be replicated in various climates and urban scales. [ABSTRACT FROM AUTHOR]