A reliable workhorse for turning text into dense vector representations. GTE Large handles semantic similarity tasks with solid contextual understanding, producing 1024-dimensional embeddings that capture meaning well across sentences and short paragraphs. It trades raw speed for richer representations compared to smaller siblings in the GTE family.