EfficientTDMPC, a sample-efficient model-based reinforcement learning method, improves on the TD-MPC family of algorithms by introducing an ensemble of dynamics models and an uncertainty penalty to reduce estimation errors. This enables EfficientTDMPC to achieve state-of-the-art sample efficiency on several benchmarks, including HumanoidBench-Hard and DMC hard.