Domain randomisation is a very popular methodfor visual sim-to-real transfer in robotics, due to its simplicityand ability to achieve transfer without any real-world imagesat all. Nonetheless, a number of design choices must be madeto achieve optimal transfer. In this paper, we perform acomprehensive benchmarking study on these different choices,with two key experiments evaluated on a real-world object poseestimation task. First, we study the rendering quality, and findthat a small number of high-quality images is superior to alarge number of low-quality images. Second, we study the typeof randomisation, and find that both distractors and texturesare important for generalisation to novel environment