Effective stem cell therapies and disease modeling depend on understanding epigenetic factors of aging. Accurately modeling age-dependent phenotypes such as aortic, and smooth muscle cell stiffening, requires cell models that reflect donor age. Improved knowledge of how donor aging influences stem cell-derived smooth muscle cells is essential for precise disease modeling and creating targeted therapeutics. We hypothesize that traits of vascular aging are retained in human induced pluripotent stem cells (iPSCs) and manifest in differentiated smooth muscle cells (SMCs). We aim to compare iPSC stiffness and gene expression between young (under 40, n=5 lines) and old (over 60, n=4 lines) donors, and examine age-dependent differences in their iPSC-SMCs. We measured cell stiffness using atomic force microscopy (AFM), and analyzed bulk and single-cell RNA gene expression in iPSCs and iPSC-SMCs of neuroectoderm (NE) or paraxial mesoderm (PM) lineages, respectively. AFM revealed no significant age-related differences in iPSC colony stiffness. Bulk RNA expression showed high similarity (>94% Pearson correlation) between young and old donor iPSCs, with principal component analysis indicating low variability and no clear age separation. Single-cell stiffness measurements found old NE-SMCs significantly stiffer than young ones (p=0.032), with no marked difference in PM-SMCs between ages. Old and young NE-SMCs were stiffer than their respective PM-SMC counterparts (old, p=0.006; young, p=0.007). UMAP analysis of single-cell RNA expression displayed distinct groupings for old and young NE-SMCs, but not for PM-SMCs. Cluster analysis revealed three clusters predominantly of old NE-SMCs and one of young NE-SMCs. Our study reveals age-related stiffening in NE lineage iPSC-SMCs, but not in PM lineage or iPSCs, indicating that iPSCs preserve certain donor age-related traits that manifest as lineage-specific phenotypes in SMCs post-differentiation. RNA sequencing showed similar expression patterns in young and old iPSCs, but age-specific differences in NE-SMCs. The integration of AFM and RNA expression data sheds light on the emergence of age-dependent phenotypes in differentiated, sensitive cell types, which are not present in immature cells.