There is a way to do this same compression by utilizing the raw probability distributions that the LLM produces as output. Fabrice Bellard has some experiments with doing this with transformers: https://bellard.org/nncp/

The idea is that if you can produce an accurate probably distribution over the next bit/byte/token, then you can compress things with an entropy compressor (huffman encoding, range encoding, asymmetric numeral systems, etc). This comment is too small of a space to explain fully how they work, but it suffices to say that pretty much every good compression algorithm models probability distributions in some way.