The developers made trained weights of MatSciBERT publicly accessible, enabling accelerated materials discovery and information extraction from materials science texts. A recent study introduced a larger GPT version, named MatGPT , based on a larger scientific corpus than MatSciBERT. In their study the group claim that the MatGPT model embeddings outperform MatSciBERT and achieve an improved band gap prediction based on the Materials Project combined with graph neural networks (GNN).