None of them of course. But the point is that even smaller open-source "LLMs" (more specifically transformer architectures) you can run anywhere yourself outperform these "traditional" pipelines with less compute. I would say that its not well defined what exactly "traditional" even means here though, since I wouldn't really even describe CNN/BiLSTMs as "traditional", in my mind that would be SpaCy <2.0 and NLTK (linear models SVMs/TF-IDF, Word2Vec/Glove/fastText/etc. etc.), LLMs are at least 2 generations ahead of those since there was the whole "deep learning" craze inbetween.
