Bigeye tuna () is one of the most valuable tropical tuna species targeted by most longline fisheries. stock assessments have always been the focus for regional tuna fishery management organizations worldwide. Based on the catch from 1950 to 2016 and Catch Per Unit Effort (CPUE) from 1955 to 2016, the stock of the Indian Ocean bigeye tuna was assessed by the Bayesian state space surplus production model in an open environment, JABBA (Just Another Bayesian Biomass Assessment), and the implications on the effects of fishing boat and CPUE data scale was explored. The results showed that the stock assessment was sensitive to different CPUE, and the scenario using CPUE considering vessel effect from 1979 to 2016 was revealed to perform best with the lowest Root-Mean-Squared-Error (RMSE) and Deviance Information Criterion (DIC), and selected to be the base case. The median estimate for bigeye tuna biomass in 2016 was 812 kt, and the Maximum Sustainable Yield (MSY) was estimated to be 163 kt, which was much higher than the catch (86.81 kt) in 2016, indicating that the stock was not overfished, with 81% in the green zone of the Kobe plot. The biomass of bigeye tuna would be higher than the biomass that can produce the maximum sustainable yield () in the next 10-year projection when the total permissible catch was set to 69.45-104.17 kt (80%-120% of catch in 2016). There were some retrospective errors in the stock assessment results, with underestimated fishing rate and overestimated biomass. Therefore, the stock assessments should be improved by updating the model structure, CPUE standardization, and setting for prior distribution of model parameters.