We describe here raaSAFT, a Python code that enables the setup and running of coarse-grained molecular dynamics simulations in a systematic and efficient manner. The code is built on top of the popular HOOMD-blue code, and as such harnesses the computational power of GPUs. The methodology makes use of the SAFT-γ Mie force field, so the resulting coarse grained pair potentials are both closely linked to and consistent with the macroscopic thermodynamic properties of the simulated fluid. In raaSAFT both homonuclear and heteronuclear models are implemented for a wide range of compounds spanning from linear alkanes, to more complicated fluids such as water and alcohols, all the way up to nonionic surfactants and models of asphaltenes and resins. Adding new compounds as well as new features is made straightforward by the modularity of the code. To demonstrate the ease-of-use of raaSAFT, we give a detailed walkthrough of how to simulate liquid–liquid equilibrium of a hydrocarbon with water. We describe in detail how both homonuclear and heteronuclear compounds are implemented. To demonstrate the performance and versatility of raaSAFT, we simulate a large polymer-solvent mixture with 300 polystyrene molecules dissolved in 42 700 molecules of heptane, reproducing the experimentally observed temperature-dependent solubility of polystyrene. For this case we obtain a speedup of more than three orders of magnitude as compared to atomistically-detailed simulations.