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Neurodiverse diagnoses (NDs) have been largely conceptualised as distinct categories with clear-cut diagnostic boundaries. However, converging research evidence is showing that this conventional approach may inadequately capture the individual variation and overlaps that are commonly observed in population studies. This study extended emerging quantitative research frameworks for understanding diagnostic complexity, adopting a transdiagnostic dimensional approach toward characterising the cognitive and mental health dimensions associated with NDs. A cohort of 175 adults with suspected or previously diagnosed neurodiverse conditions was recruited using convenience sampling. Cognitive domains of executive function, language, attention, processing speed, and memory were assessed using the National Institute of Health (NIH) Cognition Toolbox©. A battery consisting of the Extended Strengths and Weaknesses Assessment of Normal Behavior (E-SWAN), Strengths and Difficulties Questionnaire (SDQ), and Emotion Regulation Skills Questionnaire (ERSQ) was administered to provide additional proxy measures of mental health. Cluster analyses revealed that the sample of neurodivergent adults was best represented by three data-driven clusters, none of which mapped coherently onto traditional diagnostic labels. In contrast, these transdiagnostic groups were best characterised by a combination of strengths and weaknesses along two multivariate dimensions: 1) cognitive flexibility and processing speed, and 2) language, memory, emotional wellbeing, and behavioral regulation. This study provides novel, data-driven evidence to support the emerging dimensional structure of NDs, and highlights several component processes which may contribute to the complexity associated with neurodiversity in adults. These findings may be used to inform future assessment and/or support strategies for neurodivergent adults, beyond those framed by strictly categorical approaches.