When do cheap embeddings beat protein language models? A theoretically-grounded hashing sketch for biological sequence classification

\textbf{Motivation:} Pre-trained protein language models (PLMs) such as ESM-2 have become the default representation for biological sequence tasks, but they are computationally heavy and require GPUs both for embedding and for fine-tuning. Whether they are actually necessary for sequence \emph{class