With the rapid evolution in the automation of serial electron microscopy in life sciences, the acquisition of terabyte-sized datasets is becoming increasingly common. High resolution serial block-face imaging (SBEM) of biological tissues offers the opportunity to segment and reconstruct nanoscale structures to reveal spatial features previously inaccessible with simple, single section, two-dimensional images, with a particular focus on glial cells, whose reconstruction efforts in literature are still limited, compared to neurons. Here, we imaged a 750000 cubic micron volume of the somatosensory cortex from a juvenile P14 rat, with 20 nm accuracy. We recognized a total of 186 cells using their nuclei, and classified them as neuronal or glial based on features of the soma and the processes. We reconstructed for the first time 4 almost complete astrocytes and neurons, 4 complete microglia and 4 complete pericytes, including their intracellular mitochondria, 186 nuclei and 213 myelinated axons. We then performed quantitative analysis on the three-dimensional models. Out of the data that we generated, we observed that neurons have larger nuclei, which correlated with their lesser density, and that astrocytes and pericytes have a higher surface to volume ratio, compared to other cell types. All reconstructed morphologies represent an important resource for computational neuroscientists, as morphological quantitative information can be inferred, to tune simulations that take into account the spatial compartmentalization of the different cell types.