The Metastability metric measures the proportion of 20 sampled structures have an energy within 0.1 eV/atom of the ground truth structure's energy, based on MACE-MP which is a pre-trained machine learning force-field from the energies and trajectories of geometry optimisation in Materials Project. This counting occurs only when the sampled structures share the same composition as the ground truth structures, and it is done without performing geometric optimization to allow for more efficient evaluation. This metric indicates how many of the generated structures are energetically close to the ground truth, suggesting their potential stability before further optimization. Both text encoders, baseline BERT and Crystal CLIP, perform similarly in this regard, and about 19-25 % of the sampled structures exhibit energetically favourable configurations without further optimization, demonstrating the models' effectiveness in generating stable structures directly from the initial sampling.