Mass spectrometry is the state-of-the-art methodology for capturing the breadth and depth of the immunopeptidome across HLA allotypes and cell types. The majority of studies in the immunopeptidomics field are discovery-driven and data-dependent tandem mass spectrometry acquisition is commonly used, as it generates high quality references of peptide fingerprints. However, DDA suffers from the stochastic selection of abundant ions that leads to lower sensitivity and reproducibility. In contrast, in data-independent acquisition, the fragmentation and acquisition of all fragment ions from a predefined list of precursor isolation windows yields a comprehensive map for a given sample. Because often the amount of HLA peptides eluted from biological samples, is typically not sufficient for acquiring both meaningful DDA data necessary for generating comprehensive spectral libraries and DIA MS measurements, the implementation of DIA in the immunopeptidomics translational research domain has remained limited. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy by matching DIA data against libraries with growing complexity - from sample-specific libraries to libraries combining from two to forty different immunopeptidomics samples. Matching DIA immunopeptidomics data against complex pan-HLA spectral library resulted in a two-fold increase in peptide identification compared with sample-specific library and in a three-fold increase compared with DDA measurements, yet with no detrimental effect on the specificity. We concluded that a comprehensive pan-HLA library for DIA approach is highly advantageous for the clinical Immunopeptidomics where low amount of biological sample is available for immunopeptidomics.