Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, such as Google’s T5 and Meta’s BART, consist of two distinct components: an encoder and a decoder. The encoder processes the input (e.g., a sentence or document) and transforms it into numeral values that represent the meaning and the relationships between words.