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did they stick with the image-based compaction (when vision is supported i guess)? It boggled my mind: "snapcompact, which archives older history into dense images for a vision-capable model"

great idea. Currently working on updating benches on frontiers models, so far on glm-5.3 it's already showed great results. Can I have a link to oh-my-pi to make sure will sure use right one for it?

Well it's beating Claude while using GLM-5.3 in solving the UNSEEN issues from real github PRs on our benches.

Yes, readme maybe sloppy, I'm using it daily along with claude and can say it works much better, but still personal opinion

You will never know if you not try, sloppy readme cannot say the product is bad IMO, but its your choice.

Thank for feedback. I will definitely will look and work on readme. But advise what exactly sloppy – would be much more valuable

Our benchmarks shows that it best solver. Solves more than Claude on Opus while using glm 5.3, but still benching new models with most recent version.

The point here it has flexibilty in config, supervisors, automatic learning and also utilizeing jev-like models to gain maximum of efficiency while keeping solving rate intact

I highly recommend just using `mise` with the cargo backend[0]. I use mise to manage all the harnesses I try.

[0] https://mise.jdx.dev/dev-tools/backends/cargo.html

I would vote against package managers. It just doesn't make sense to try to support them across Linux distributions.

If it's really static rust then either make it one binary. If that's not reasonable then make the release relocatable to run from any path. Also it should be simple and easy to run out of the source repo.

Thanks for suggestion! Will do. Can I know which distribution are you using? Feel free to leave feedback after you try. Cheers

I like yours too! Perfect fit