Although new generation many-body polarizable force field (PFFs) are more accurate in describing biomolecular interactions, they are computationally more challenging than traditional approaches. Therefore, to overcome these limitations, we provide here a novel general multi-level enhanced sampling strategy, that we apply to the PFF AMOEBA. To do so, we combine together the Tinker-HP massively parallel multi-GPUs platform to a highly scalable GaMD implementation (level 0 ) and to additional enhanced sampling techniques based on recent developments of the field. As a first speedup, we propose an extension of the GaMD formalism with a new GaMD mode enabling the use of flexible water models such as AMOEBA and fast multiple-time-step integrators (level 1 ). We then discuss the explicit coupling of such GaMD approach to Umbrella Sampling (US) and Adaptive Sampling (AS) 6 techniques (level 2 ). To demonstrate their applicability to PFF, these physics-based hybrid enhanced sampling strategies are then applied to the Potential of Mean Force (PMF) study of a large biological complex CD2-CD58 interacting via salt bridges with the AMOEBA force field. Finally, we combine all together within the Adaptive Sampling-US-GaMD method (ASUS-GaMD) scheme (level 3 ).