> if LLMs are used as compressors, how well is that expected to work

Quite well. This project[1], by Fabrice Bellard of ffmpeg fame, is quite old in AI years and uses an ancient LLM, but still beats xz by a solid margin.

[1]: https://bellard.org/ts_zip/

Makes me wonder if compression ratio can be used as a measure for intelligence. Any benchmarks using it?

> Any benchmarks using it?

A challenge as I understand it is reproducibility.

Normal LLM runtimes aren't typically fully reproducible even with same random seeds for distribution sampling, due to floating-point numbers, batching and such.

Though averaging over many runs could alleviate that I suppose.

While it would measure some aspects of intelligence, I'd argue it fails to capture other, more creative aspects.

Extremely well, aside from speed.

> aside from speed.

And energy consumption.

I wonder if, on an information theoretical level, compression radiates heat, and decompression absorbs it?