Various computational approaches have been developed for estimating the relative abundance of different cell types in the tumour microenvironment (TME) using bulk tumour RNA data. However, a comprehensive comparison across diverse data sets that objectively evaluates the performance of these approaches has not been conducted. Here we benchmarked seven widely used tools and gene sets and introduce ConsensusTME, a method that integrates gene sets from all the other methods for relative TME cell estimation of 18 cell types. We collected a comprehensive benchmark dataset consisting of pan-cancer data (DNA-derived purity, leukocyte methylation, and H&E-derived lymphocyte counts) and cell-specific benchmark data sets (peripheral blood cells and tumour tissues). Although none of the methods outperformed others in every benchmark, ConsensusTME ranked top three in all cancer-related benchmarks and was the best performing tool overall. We provide a web resource to interactively explore the benchmark results and an objective evaluation to help researchers select the most robust and accurate method to further investigate the role of the TME in cancer (www.consensusTME.org).