In recent years, single cell proteomics became one of the hottest topics within the field of proteomics. The potential ability to map the proteomic fingerprint to transcriptomic data would master the understanding of how gene expression translates into actual phenotypes and cellular functions. In contrast to nucleic acid sequencing, in vitro amplification of proteins is impossible to date and no single cell proteomic workflow has been established as gold standard yet. Lots of advances in microfluidic sample preparation, multi-dimensional sample separation, sophisticated data acquisition strategies and intelligent data analysis algorithms already brought major improvements to successfully analyze such tiny sample amounts with steadily boosted performance. However, among the broad variation of published approaches, its commonly accepted, that highest possible sensitivity, robustness and throughput are still the most urgent needs for the field. While many labs have focused on multiplexing to achieve these goals, label-free single cell proteomics is a highly promising strategy as well whenever high dynamic range and unbiased accurate quantification are needed. We here focus on recent advances of label-free single-cell mass spectrometry workflows and try to guide our readers to choose the best method or method combinations for their specific application. We further highlight which techniques are most propitious in the future and which applications but also limitations we foresee for the field.