Sexual and gender minorities (SGM) experience disproportionately high rates of mental and physical health challenges driven largely by stigma and discrimination embedded within social and structural systems. Intersectional stigma, where multiple stigmatized identities intersect, offers a useful lens, but is difficult to study quantitatively because individuals vary widely in both the number and types of stigmas they report, requiring large, diverse samples to identify meaningful patterns. Although intersectional experiences are often idiosyncratic, people who share identities may also share intersecting stigma profiles (e.g., gender and sexual-orientation stigma). However, many large-scale studies have collapsed cisgender sexual minorities (CSM) and gender-diverse sexual minorities (GDSM) into a single category, potentially obscuring subgroup-specific mechanisms and limiting intervention precision. To assess whether shared, group-level stigma configurations exist and whether they differ between CSM and GDSM, we used psychometric network analysis on 20,682 sexual minority participants from the All of Us Research Program (1,816 GDSM; 18,866 CSM), modeling 11 stigma domains (e.g., gender, race, sexual orientation, and appearance). Gender- and sexual-orientation-based stigma was the most frequently reported stigma, especially among the GDSM; however, network centrality analyses indicated that racialized and cultural domains (race, ancestry, religion) were structurally the most influential across groups. The network comparison test results showed a significant difference in the configuration of stigma profiles between GDSM and CSM participants (M = 1.32, p < 0.001), whereas global network strength did not differ (S = 3.22, p = 0.973). This indicates that there are different organizational patterns of intersectional stigma, despite their similar overall interconnectedness. These findings suggest that experiences of intersectional stigma among SGMs is organized by broader systems of racialized and cultural marginalization and that disaggregating sexual minorities by gender identity can reveal distinct network structures relevant for targeted clinical and public-health interventions.