The user tested the Embedding Gemma 2 model (≈330 MB at Q8 precision) to search for text inside images by measuring cosine similarity between the image embedding and refined text query embeddings. The demonstration shows how similarity changes as the query is refined, highlighting both the effectiveness and quirks of the method. They intend to run further tests and share example query images if there is interest.