Amorphous materials have been known to be intrinsically brittle under tensile stress. This is especially true in silicon-based and metallic-based glasses. In particular, for the latter, they quite often show promising mechanical properties superior to their crystalline counterparts. However, lacking tensile ductility strongly prohibits them from servicing the societies. Although with decades of immense research efforts, we are still waiting for a sophisticated solution. To march in this direction, in this work, we are dedicated to finding a practical method by smart fractal nano-architecture design through advanced computational modeling. This mainly aims to circumvent the intrinsic strain localization at the nano-scale to avoid catastrophic failure. By distributing the external strain to numerous self-confined nano-branches, we successfully achieve astonishing and tunable tensile ductility. This strategy proves to be very effective for different classes of amorphous materials. We found that the tensile properties of the nano-architectured glasses depend on both the constituent elements and the nanostructure. This demonstrates our flexible capability to design desired mechanical properties for a specific material at any spatial length scale. The current findings will inspire experimental realization by cutting-edge 3D-printing techniques and call for optimal design by top-notch graph neural network deep learning algorithms. This work also proposes a new ’structure’-property relationship to efficiently bridge experimental fabrication and computational design.