RLLTE is a reinforcement learning research library that implements modern RL algorithms including PPO, Phasic Policy Gradient, and DrQ-v2. It provides intrinsic reward modules for exploration and benchmarks on environments like DeepMind Control Suite, ProcGen, and PyBullet. The library offers GPU and NPU acceleration for training and supports algorithm decoupling for modular experimentation.