Oh, my bad, yeah. When I was writing the comment, I flipped the direction of advantage for longer time controls (longer time controls are actually better for humans in odds matches of course), but this way I agree it's unclear a priori whether 200 elo drop would be enough to account for longer time controls.

Thanks for this update! I find that an odd prediction by the IM because Awonder is around 2670 FIDE and Joel is around 2470 FIDE, 200 elo is huge.

Hissha from the Lc0 server reports 19 wins, 3 draws, and 2 losses against Lenderman (currently ~2500 FIDE) at 15+10 from a knight odds match 2 months ago -- with the caveat that Lenderman started playing too fast after 10 games. I haven't run the numbers but suspect this would be enough to go even against a 2750, if not Magnus?

I was surprised too. I think it's an exciting development :)

At rapid time controls, it seems like we could maybe go even against Magnus with knight odds? If not Magnus, perhaps other high-rated GMs.

There was a match with the most recently updated LeelaKnightOdds and GM Alex Lenderman but I don't recall the score exactly. EDIT: which was 19-3-2 win draw loss.

This is something lc and gwern discussed in the comments here, but now we have clear evidence this is only true for Nash solvers (all typical engines like SF, Lc0, etc.). LeelaQueenOdds, which trained exploitatively against a model of top human players (FM+), is around 2k to 2.9k lichess elo depending on the time controls, so it completely trounces 1.6k elo players (especially 1.2k elo players as another commenter has suggested the author actually is). See: https://marcogio9.github.io/LeelaQueenOdds-Leaderboard/

Nash solvers are far too conservative and expect perfect play out of their opponents, hence give up most meaningful attacking chances in odds games. Exploitative models like LQO instead assume their opponents play like strong humans (good but imperfect) and do extremely well, despite a completely crushing material disadvantage. As some have noted, this is possible even with chess being a super sterile/simple environment relative to real life.

I speculate that the experiment from this post only yielded the results it did because Nash is a poor solution concept when one side is hopelessly disadvantaged under optimal play from both sides, and queen odds fall deep into that category.

See video from 7 minutes. Try it yourself https://lichess.org/@/LeelaQueenOdds :)