Background: Cervical cancer shows a growing incidence and medical cost in recent years that has increased severe financial pressure on patients and medical insurance institutions. This study aimed to investigate the medical economic characteristics of cervical cancer patients with different payment modes within a Grade A tertiary hospital to provide evidence and suggestions for inpatient cost control and to verify the application of Gamma model in medical cost analysis. Methods: The basic and cost information of cervical cancer cases within a Grade A tertiary hospital in the year 2011–2016 were collected. The Gamma model was adopted to analyze the differences in each cost item between medical insured patient and uninsured patients. Meanwhile, the marginal means of different cost items were calculated to estimate the influence of payment modes toward different medical cost items among cervical cancer patients in the study. Results: A total of 1321 inpatients with cervical cancer between the 2011 and 2016 were collected through the medical records system. Of the 1321 cases, 65.9% accounted for medical insured patients and 34.1% were uninsured patients. The total inpatient medical expenditure of insured patients was RMB 29,509.1 Yuan and uninsured patients was RMB 22,114.3 Yuan, respectively. Payment modes, therapeutic options as well as the recurrence and metastasis of tumor toward the inpatient medical expenditures between the two groups were statistically significant. To the specifics, drug costs accounted for 37.7% and 33.8% of the total, surgery costs accounted for 21.5% and 25.5%, treatment costs accounted for 18.7% and 16.4%, whereas the costs of imaging and laboratory examinations accounted for 16.4% and 15.2% for the insured patient and uninsured patients, respectively. As the effects of covariates were controlled, the total hospitalization costs, drug costs, treatment costs as well as imaging and laboratory examination costs showed statistical significance. The total hospitalization costs, drug costs, treatment costs as well as imaging and laboratory examination costs of insured patient were 1.33, 1.42, 1.52, and 1.44 times of uninsured patients. Conclusions: The analysis of different payment modes toward the medical economic characteristics based on Gamma model is basically rational. Medical payment modes are having certain influence toward the hospitalization expenses of cervical cancer patients in an extent, as drug costs, treatment costs, and examination costs appear to be the main causes.