How well can LLMs solve chess puzzles? (github.com)

submitted 7 months ago by httpjames@sh.itjust.works to c/technology@lemmy.world

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Each LLM is given the same 1000 chess puzzles to solve. See puzzles.csv. Benchmarked on Mar 25, 2024.

Model	Solved	Solved %	Illegal Moves	Illegal Moves %	Adjusted Elo
gpt-4-turbo-preview	229	22.9%	163	16.3%	1144
gpt-4	195	19.5%	183	18.3%	1047
claude-3-opus-20240229	72	7.2%	464	46.4%	521
claude-3-haiku-20240307	38	3.8%	590	59.0%	363
claude-3-sonnet-20240229	23	2.3%	663	66.3%	286
gpt-3.5-turbo	23	2.3%	683	68.3%	269
claude-instant-1.2	10	1.0%	707	66.3%	245
mistral-large-latest	4	0.4%	813	81.3%	149
mixtral-8x7b	9	0.9%	832	83.2%	136
gemini-1.5-pro-latest*	FAIL	-	-	-	-

Published by the CEO of Kagi!

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[-] sudoreboot@slrpnk.net 11 points 7 months ago

Not well, apparently.

[-] conciselyverbose@sh.itjust.works 8 points 7 months ago* (last edited 7 months ago)

I wonder how many of the ones they "solved" were just because they'd seen it discussed somewhere in the data set, considering the puzzles are apparently from a public resource.

[-] sudoreboot@slrpnk.net 10 points 7 months ago

Yeah, I don't know why anyone knowledgeable would expect them to be good at chess. LLMs don't generalise, reason or spot patterns, so unless they read a chess book where the problems came from...

[-] Carrolade@lemmy.world 5 points 7 months ago

Likely close to 100%. If you read the (rather good) article, a little further down they test whether the LLM can play an extremely simplistic "Connect 4" game they devise, as a way of narrowing down on specifically reasoning capabilities.

It cannot.

Chess puzzles, in particular, are frequently shared and discussed in online chess spaces, so the LLM will have a significant amount of material to work with when it tries to predict the best response to give to the prompt.

this post was submitted on 25 Mar 2024

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