Among the English Channel fishery, the importance of cuttlefish stock has increased, following the cephalopods global landings and market trend. The stock is currently managed at regional scale but not by European regulations, although it is a shared species targeted by French and British fishing fleets at several stages of its life-cycle and across much of its distributional range. An assessment of this stock was conducted in June 2014 by fitting a two-stage biomass model on a 22 years’ time-series (1992-2013). We present the last update of cuttlefish stock assessment using the same model on years 1992-2014. As the outputs of the model are sensitive to a fix growth parameter, we explore possibilities to improve the model. The use of a Bayesian framework is particularly adapted for decision making, allowing the propagation of uncertainty in the model and the use of prior knowledge on some parameter distributions. Therefore, we implemented the two-stage biomass model into a Bayesian framework and compared the results with the outputs of the initial fit. We found similar trends of biomass estimates for both models. The Bayesian model outputs showed a smaller range of variation than the initial fit. These results are only a first step toward an improvement of the two-stage biomass model currently used for cuttlefish stock assessment in the English Channel. The Bayesian model could indeed be improved and particular attention should be paid to the growth parameter g because of the high sensitivity of model outputs to its value. We discuss future directions of this work.