Medium-large Dynamic Stochastic General Equilibrium models such as those used for forecasting and policy analysis by central banks take a substantial amount of time to estimate using standard approaches such as Random Walk Metropolis Hastings. Our new Sequential Monte Carlo sampler in DSGE.jl makes it possible to estimate DSGE models in parallel, reducing computational time, and “online,” that is efficiently including new data in the estimation as they become available.