Satellite XCO₂ retrievals could improve the estimates of surface carbon fluxes, but it remains unknow on what scales these estimates are robust. Here, we use the time-dependent Bayesian synthesis top-down method and prior net ecosystem exchanges (NEEs) from 12 terrestrial biosphere models (TBMs) to infer the monthly carbon fluxes of 51 land regions with constraints by GOSAT XCO₂ retrievals. We find that the uncertainty (standard deviation of 12 TBMs) reduction rates (URR) decrease significantly at decreasing spatial scales. On the continental-scale, the mean URR is about 60%, and the annual and seasonal cycle estimates of NEE are rather robust. The evaluation shows that the posterior CO₂ concentrations are significantly improved at the continental scale. Our study suggests that the GOSAT XCO₂ can only promise a robust continental-scale NEE estimate, and improving the XCO₂ accuracy is an effective way to achieve robust estimates on smaller scales under current spatial coverage.