Higher spatial and angular resolution is essential in diffusion MRI to resolve fiber and structural ambiguities. However, quantitative measures are confounded by low SNR, particularly at high b-values, compensation of which leads to longer acquisition times. In this study, the fundamental question asked is: Can denoising aid the stability of the measurement in the presence of increasing noise? Model based denoising was used to explore accelerated sampling by evaluating bias developed in qualitative and quantitative end points. Experimental results highlight superior performance, compared to ground truth, in noise and bias reduction in metrics along with structure preservation.