Chinchilla is a $70$-billion-parameter language model that inherits the architecture and compute budget of Gopher but trains on a significantly larger dataset of $1.4$ trillion tokens. It outperforms Gopher by placing greater emphasis on the number of training tokens rather than the sheer number of model parameters.