The latent HIV reservoir is generated following HIV infection of activated effector CD4 T cells, which then transition to a memory phenotype. Here, we describe an ex vivo method, called QUECEL (quiescent effector cell latency), that mimics this process efficiently and allows production of large numbers of latently infected CD4 ⁺ T cells. Naïve CD4 ⁺ T cells were polarized into the four major T cell subsets (Th1, Th2, Th17, and Treg) and subsequently infected with a single-round reporter virus which expressed GFP/CD8a. The infected cells were purified and coerced into quiescence using a defined cocktail of cytokines, including tumor growth factor beta, interleukin-10 (IL-10), and IL-8, producing a homogeneous population of latently infected cells. Flow cytometry and transcriptome sequencing (RNA-Seq) demonstrated that the cells maintained the correct polarization phenotypes and had withdrawn from the cell cycle. Key pathways and gene sets enriched during transition from quiescence to reactivation include E2F targets, G ₂ M checkpoint, estrogen response late gene expression, and c-myc targets. Reactivation of HIV by latency-reversing agents (LRAs) closely mimics RNA induction profiles seen in cells from well-suppressed HIV patient samples using the envelope detection of in vitro transcription sequencing (EDITS) assay. Since homogeneous populations of latently infected cells can be recovered, the QUECEL model has an excellent signal-to-noise ratio and has been extremely consistent and reproducible in numerous experiments performed during the last 4 years. The ease, efficiency, and accuracy of the mimicking of physiological conditions make the QUECEL model a robust and reproducible tool to study the molecular mechanisms underlying HIV latency.IMPORTANCE Current primary cell models for HIV latency correlate poorly with the reactivation behavior of patient cells. We have developed a new model, called QUECEL, which generates a large and homogenous population of latently infected CD4 ⁺ memory cells. By purifying HIV-infected cells and inducing cell quiescence with a defined cocktail of cytokines, we have eliminated the largest problems with previous primary cell models of HIV latency: variable infection levels, ill-defined polarization states, and inefficient shutdown of cellular transcription. Latency reversal in the QUECEL model by a wide range of agents correlates strongly with RNA induction in patient samples. This scalable and highly reproducible model of HIV latency will permit detailed analysis of cellular mechanisms controlling HIV latency and reactivation.