How well are single-cell properties reproduced by the present-day neuronal models? Recently, several labs have approached this question by assessing the quality of the models with respect to spike timing prediction or characteristic features of the voltage trace. So far, every modeler used his own preferred performance measure on his own data set. The ‘Quantitative Single-Neuron Modeling Competition’ offers a coherent framework to compare neuronal models with four different experiments on layer V pyramidal neurons of the somatosensory cortex under somatic and dendritic stimulation. Specific performance measures are used on these four experiments to quantify specific performances of neuronal models under somatic and dendritic stimulation, e. g.: spike timing, inter-spike intervals, or subthreshold waveform. Expert and novice modelers have been invited to submit their prediction of neuronal behavior in any or all of these four different experimental setups. Here we present the results of this competition. Along with submissions from other labs, we show the performance of a stochastic Poisson neuron model and the adaptive Exponential Integrate-and-Fire model. The results are valuable for network modelers interested in finding the best trade-off between biological relevance and simplicity.