<p>Metabolomics has matured into a powerful approach for probing metabolism, offering readouts that closely reflect cellular and organismal function in health and disease. Here we highlight two rapidly advancing frontiers: single-cell metabolomics and population-scale metabolomics. Single-cell metabolomics resolves the metabolic states of individual cells, uncovering cell-to-cell heterogeneity and spatial organization within tissues. Population-scale profiling profiles metabolites across large cohorts, enabling the discovery of markers of disease, environmental exposures and genetic variation. Although these approaches operate at different scales, they face shared challenges—including metabolite identification, quantification and multimodal data integration—and offer common advantages, such as the ability to capture non-genetic influences on phenotype and to scale to high throughput. We propose that continued advances in scalability will bring these domains together, enabling the construction of comprehensive metabolic atlases that chart cellular and interindividual variation and provide training data for foundation models of metabolism. By integrating cellular and population-level insights, single-cell and population-scale metabolomics promise to advance our understanding of metabolism across biology, medicine and pharmacology.</p>