Low-carbon economy constitutes a critical pathway to achieving China’s dual carbon goals and a core driver of high-quality economic development, integrating environmental sustainability with long-term economic growth momentum. As a major energy province and a key national comprehensive energy security base, Shaanxi Province bears unshirkable political responsibilities for ensuring stable energy supply—its abundant fossil energy reserves and strategic geographical location make it an indispensable pillar of national energy security, while also imposing the arduous task of reconciling energy production with low-carbon transition. Based on panel data of 10 prefecture-level cities in Shaanxi from 2011 to 2022, this study constructs a comprehensive evaluation index system for low-carbon economic development, incorporating 33 basic indicators across six interconnected dimensions: energy structure, low-carbon industry, low-carbon innovation, low-carbon society, lowcarbon environment, and economic development. The entropy weight method is adopted for objective evaluation, as it quantifies indicator weights based on information entropy without subjective biases, ensuring the reliability of the low-carbon development level measurement. On this basis, three quantitative methods are employed to explore regional characteristics: the Dagum Gini coefficient and its decomposition method to identify sources of regional disparities; kernel density estimation to visualize the dynamic evolution of development level distributions; and two classic spatial convergence models to test long-term trends in regional disparity. Finally, the Quadratic Assignment Procedure (QAP) is utilized to examine the intrinsic mechanisms of regional differences, leveraging its advantage in addressing spatial dependence in cross-sectional data. The empirical findings are as follows first, from 2011 to 2022, the low-carbon economic development level of Shaanxi Province as a whole, its three major regions, and all 10 prefecture-level cities exhibited a steady upward trend. This progress is attributed to the implementation of national low-carbon strategies, regional industrial structure optimization, and increased investment in energy conservation and environmental protection. Notably, however, unbalanced development persisted across regions and cities, stemming from disparities in resource endowments, industrial bases, technological capabilities, and policy implementation effects. Secondly, the overall regional disparity in Shaanxi’s low-carbon economic development showed a gradual expanding trend. Decomposition results of the Dagum Gini coefficient indicate that inter-regional disparity is the primary source of overall imbalance, as divergent development conditions and resource allocation across regions lead to heterogeneous growth trajectories. Among these, the gap between Guanzhong and Southern Shaanxi is particularly prominent, reflecting significant differences in economic foundation, technological innovation capacity, and industrial transformation speed between the two regions. Thirdly, regarding convergence characteristics: σ -convergence is absent in Shaanxi as a whole, Guanzhong, and Northern Shaanxi, meaning the relative gap in low-carbon development among cities in these regions did not narrowover time. In contrast, Southern Shaanxi exhibits significant σ-convergence, driven by coordinated development policies and ecological protection efforts that reduce intra-regional disparities. Furthermore, Shaanxi Province, Guanzhong, and Southern Shaanxi all demonstrate absolute β-convergence, indicating lagging cities have faster low-carbon development growth rates and the potential to catch up with leading cities over time. Guanzhong’s convergence speed is significantly faster than that of Southern Shaanxi, primarily due to its advantages in talent aggregation, technological spillover, and industrial agglomeration, which accelerate the diffusion of low-carbon technologies and models. Fourth, QAP analysis results reveal that except for low-carbon industry, development disparities in the other five dimensions exert a significant positive impact on low-carbon economic development gaps. Among these factors, low-carbon innovation has the strongest effect, underscoring that the uneven distribution of innovation resources is the key driver of regional disparities.