WordLlama is a fast, lightweight NLP toolkit that operates on token embeddings from LLMs. It provides CPU-optimized functionality for fuzzy deduplication, semantic similarity computation, document ranking, clustering, and text splitting. The toolkit supports model2vec static embeddings and achieves competitive results on the MTEB benchmark.