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.　©　2017　IEEE.