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Correct me if I'm wrong but I think that a few years old version of Stockfish running on a modern MacBook Air with 1 min per move is unbeatable if the game starts from the initial position.

Even if the opponent is the latest Stockfish with 1000x more time per move, it will always be a draw.

I asked about this a few years ago in a Stockfish Discord and the above claim is what someone implied, if I remember correctly.

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This sounds plausible. But otherwise, there are "tournaments" like the TCEC which is for bots only and the way it works is, the bots are adjusted to play a specific opening and they're on their own after the Nth move.

Stockfish has been dominant for a long time. And a later version of Stockfish would outperform an earlier version given the same time control.


I believe this is not the case. The first reason is the optimization of the Transposition Table in stockfish. https://github.com/official-stockfish/Stockfish/blob/master/...

Basically this optimization means that stockfish will sometimes take a bad read from a cache (so it will take an evaluation of the position from cache which was calculated for a different position). It's fairly random when this will trigger a bad play, but if you brute force vs any deterministic setup you will find it eventually.

But even withtout it - you can just implement a kind of a brute-force heap of positions using stockfish's own eval and you can find wins from almost any position even on fairly high playout count.

I got as far as 32M from different even starting positions, but I spent compute to find as many games as possible rather than as deep as possible.

Example game: https://lichess.org/XVUjezMr#134

the collection of the games I found (vibecoded gui) https://kuboble.com/chess_ideas/


The post literally says

> against Stockfish 18, this new release brings an Elo gain of up to 44 points, and wins more than three times as many game pairs as it loses.


I'm talking about games that start from the initial position.

A faster engine is still very useful in practice, for example for position evaluations in game review.

Not that an engine evaluation will always be helpful (the line in question making a position strong or weak might be effectively unplayable/impossible to find by a human), but it’s useful for studying nevertheless.




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