Recently, existing generative models have been adapted to discover previously unknown stoichiometries, molecules , and solid crystals , with the latter still in their nascent stages of development. Work done in generating new crystals have either had restricted stoichiometry or structures. In contrast to molecules, generative modelling of inorganic solid-state materials has been challenging because of the lack of invertible representation and limited availability of datasets. Attempts have been made to overcome these obstacles. Some models have alleviated these problems and presented a general framework for the generation of crystals. Nevertheless, we believe they lack in creating a model, which can be generalized to the vast variety of compositions possible out of the periodic table and scalable to generate the inorganic materials with complex chemistries.