Biological characteristics of pregnant women during early pregnancy make them susceptible to both poor sleep quality and metal/metalloid exposure. However, the effects of metal(loid) exposure on sleep quality in pregnant women remain unknown and unexplored. We aimed to examine the relationship between exposure to a mixture of metal(loid)s and pregnant women's sleep quality during early pregnancy. We recruited 493 pregnant women in the first trimester from prenatal clinics in Jinan, Shandong Province, China, and collected their spot urine samples. All urine specimens were assessed for eight metal(loid)s: arsenic (As), cadmium (Cd), iron (Fe), zinc (Zn), molybdenum (Mo), lead (Pb), selenium (Se), and mercury (Hg). We used the Pittsburgh Sleep Quality Index (PSQI) to assess sleep quality. Linear regression, logistic regression, generalized additive models (GAMs), quantile g-computation, and Bayesian kernel machine regression (BKMR) were applied to investigate the relationships between metal(loid) exposure and sleep quality. The results from single metal(loid) models, quantile g-computation models, and BKMR models consistently suggested that Fe was positively related to women's sleep quality. Moreover, in the quantile g-computation models, As was the most critical contributor to the negative effects of the metal(loid) mixture on sleep quality. In addition, we found significant As by Fe interaction for scores of PSQI and habitual sleep efficiency, Pb by Fe interaction for PSQI and sleep latency, and Hg by Fe interaction for PSQI, suggesting the interactive effects of As and Fe, Pb and Fe, Hg and Fe on sleep quality and specific sleep components. Our study provided the first-hand evidence of the effects of metal(loid) exposure on pregnant women's sleep quality. The underlying mechanisms need to be explored in the future.