Static is much cheaper, uses the same probabilities for the entire data block (e.g. 30 kB), probabilities are stored in the header - practically all Huffman and tANS compressors (however, there are considered exceptions: https://en.wikipedia.org/wiki/Adaptive_Huffman_coding ).
I know that's what adaptive coding means, I thought that was impossible with rANS. All the descriptions of rANS I could find (back when I looked at it) described it terms of a static model, and I ran into problems trying to generalize it to an adaptive one.
Thanks for the resources.