Many mixed reality applications are b ased on the real-time compression and streaming of three-dimensional (3D) mod els. Thus, they demand very high- bandwidth and ultra-low latency from network specifications. The next-generation wireless networks will employ promising technologies to sig nificantly improve the communication data rates. However, due to implementation complexity and thus increased en ergy consumption of these technologies, a trade-off between the quality-of-use r-experience (QoE) and the hardware spec ifications is necessary. To overcome these limitations low- resolution quantizers have been of inte rest, which provide a trade-off between quality and complexity. In this p aper, we propose a complexity-aware perceptual coding scheme that minimizes the reconstruction losses of the 3D models. Ex tensive simulations assuming different 3D models show that the proposed scheme achieves plausible reconstruction output offering significantly higher energy efficiency gains, as com pared to a context unaware coding approaches.