Abstract: In the context of the development of the digital economy, exploring the spatiotemporal pattern and convergence issues of digital economic development is of significant practical importance in promoting regional coordinated development. Based on panel data from 30 provinces in China from 2011 to 2021, the article used the entropy weight method to construct the comprehensive index of China's digital economy. It examined the regional unevenness and dynamic evolution patterns of China's digital economy using kernel density estimation, and tested the convergence characteristics of the digital economy using the coefficient of variation method and spatial econometric models. It is found that the development of China's digital economy exhibits a “core-periphery” structure with eastern coastal provinces as the core and central and western inland provinces as the periphery, showing clear characteristics of a “digital divide.” The main pattern of China's digital economic development consists of “H-H” agglomeration and “L-L” agglomeration, displaying a certain degree of polarization. Over time, this polarization has weakened, and the asymmetric structure is gradually easing. The econometric results reveal that the level of development of China's digital economy exhibits characteristics of δ-convergence, β-convergence, and club convergence, but with varying convergence speeds in different regions. Compared to the eastern region, the central and western regions show a significant “catch-up effect,” and the convergence speed demonstrates a “differentiation feature” among provinces. Therefore, it is recommended that the government follow a collaborative approach to understand the spatiotemporal evolution patterns of China's digital economy and optimize regional structures, aiming to achieve common development among regions.