In Video Coding, the Rate Distortion Optimization (RDO) is the key technique to choose the most efficient coded representation of raw video. Specifically, encoder selects an optimal combination of coding parameters from a fixed and discrete candidate set in the rate-distortion sense. As this process is computation intensive essentially, its practicality can be limited especially for real-time applications. Thus, it is worthwhile to reduce the complexity while still preserve its accuracy. To achieve this goal, we propose an efficient and low-complexity model to estimate the rate and distortion information. A CG level content-adaptive rate model is proposed to ensure the bit rate estimation is accurate and stable against the change of coding parameters and video content. For distortion modeling, an efficient quantization-free estimator is proposed. Extensive experimental results demonstrate that our method significantly reduces in average 34.6% of encoder complexity than existing works with marginal RD performance loss.