>What happens when you ask those same frontier models to write a chess-playing program?
they shit out a carbon copy of https://github.com/official-stockfish/stockfish that they have in their training data. Still doesn't make Fable good at playing chess.
In Why I'm still bearish on LLMs after Navier-Stokesofficial-stockfish
Stockfish
C++2016–2026
official-stockfish / Stockfish
Stockfish
A free and strong UCI chess engine
39Distinct people
45Mentions
1Explicit recommenders
17.4KGitHub stars
What to know before exploring
What it is
A free and strong UCI chess engine
GitHub
Where it is used
No documented product use was verified in the last source check.
What people are saying
I recommend anyone who's interested in this topic, or in data structures and optimisation, to pick apart Stockfish' transposition table implementation[0,1]. It's essentially a…
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Also in these discussions
- leelachesszero/lc0 · linked in 2 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year45 dated mentions
Observed mentions: 2016-11-12 18:05:22 UTC to 2026-09-16 15:28:55 UTC.
* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2016 | 2016-01-01 00:00:00 UTC | 2017-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2017 | 2017-01-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 3 | 0 | 3 |
| 2018 | 2018-01-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 5 | 1 | 4 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 10 | 1 | 9 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 6 | 0 | 6 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 3 | 2 | 1 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2026 (partial) | 2026-01-01 00:00:00 UTC | 2027-01-01 00:00:00 UTC | 6 | 1 | 5 |
From the project README
An excerpt from the repository, fetched Nov 13, 2026.
Read the project’s introduction
Stockfish
A free and strong UCI chess engine.
Explore Stockfish docs »
Report bug
·
Open a discussion
·
Discord
·
Blog
Overview
Stockfish is a free and strong UCI chess engine derived from
Glaurung 2.1 that analyzes chess positions and computes the optimal moves.
Stockfish does not include a graphical user interface (GUI) that is required
to display a chessboard and to make it easy to input moves. These GUIs are
developed independently from Stockfish and are available online. Read the
documentation for your GUI of choice for information about how to use
Stockfish with it.
See also the Stockfish documentation for further usage help.
Files
This distribution of Stockfish consists of the following files:
README.md, the file you are currently reading.
Copying.txt, a text file containing the GNU General Public
License version 3.
AUTHORS, a text file with the list of authors for the project.
src, a subdirectory containing the full source code, including a
Makefile that can be used to compile Stockfish on Unix-like systems.
a file with the .nnue extension, storing the neural network for the NNUE
evaluation. Binary distributions will have this file embedded.
Contributing
See Contributing Guide.
Donating hardware
Improving Stockfish requires a massive amount of testing. You can donate your
hardware resources by installing the Fishtest Worker and viewing
the current tests on Fishtest.
Improving the code
In the chessprogramming wiki, many techniques used in
Stockfish are explained with a lot of background information.
The section on Stockfish describes many features
and techniques used by Stockfish. However, it is generic rather than
focused on Stockfish's precise implementation.
The engine testing is done on Fishtest.
If you want to help improve Stockfish, please read this guideline
first, where the basics of Stockfish development are explained.
Discussions about Stockfish take place these days mainly in the Stockfish
Discord server. This is also the best place to ask questions
about the codebase and how to improve it.
Compiling Stockfish
Stockfish has support for 32 or 64-bit CPUs, certain hardware instructions,
big-endian machines such as Power PC, and other platforms.
On Unix-like systems, it should be easy to compile Stockfish directly from the
source code with the included Makefile in the folder src. In general, it is
recommended to run make help to see a list of make targets with corresponding
descriptions. An example suitable for most Intel and AMD chips:
cd src
make -j profile-build
Detailed compilation instructions for all platforms can be found in our
documentation. Our wiki also has information about
the UCI commands supported by Stockfish.
Terms of use
Stockfish is free and distributed under the
GNU General Public License version 3 (GPL v3). Essentially,
this means you are free to do almost exactly what you want with the program,
including distributing it among your friends, making it available for download
from your website, selling it (either by itself or as part of some bigger
software package), or using it as the starting point for a software project of
your own.
The only real limitation is that whenever you distribute Stockfish in some way,
you MUST always include the license and the full source code (or a pointer to
where the source code can be found) to generate the exact binary you are
distributing. If you make any changes to the source code, these changes must
also be made available under GPL v3.
Acknowledgements
Stockfish uses neural networks trained on data provided by the Leela Chess Zero
project, which is made available under the Open Database License (ODbL).
Read the full README on GitHubWhat Hacker News says
45 sourcesI 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.
Read the rest
Example game: https://lichess.org/XVUjezMr#134
the collection of the games I found (vibecoded gui)
https://kuboble.com/chess_ideas/
In old-school chess AIs, zugzwang is also of interest because it can break null-move pruning[0], which is a way to prune the search tree. "Null move" just means "skip your turn", and the assumption that skipping your turn is always worse than the optimal move. But in zugzwang positions, that assumption is wrong, so you have to avoid doing null-move pruning.
Stockfish's heuristic for "risk of zugzwang" is basically "only kings and pawns left over", alongside logic for "is null-move pruning even useful right now" [1]:
// Step 9. Null move search with verification search
if (cutNode && ss->staticEval >= beta - 16 * depth - 53 * improving + 378 && !excludedMove
&& pos.non_pawn_material(us) && ss->ply >= nmpMinPly && !is_loss(beta))
{
[0]: https://en.wikipedia.org/wiki/Null-move_heuristic
[1]: https://github.com/official-
Read the rest
Stockfish removes classical evaluation functions in favor of NNUE only (2023)
2 points · Open discussion> but I still think the developers of both engines banter over who is really producing the True WDL numbers for a given position
In fact, stockfish's WDL is very rudimentary: it is a function of the centipawn evaluation of the position and the value of the remaining material.
See https://github.com/official-stockfish/Stockfish/blob/a6d055d...
In What Is a Centipawn Advantage?It found a small but nice little optimization in Stockfish: https://github.com/official-stockfish/Stockfish/pull/6613
Previous models including Claude Opus 4.6 have generally produced a lot of noise/things that the compiler already reliably optimizes out.
In Gemini 3 Deep ThinkStockfish has got rid of old handwritten evaluation now.
https://github.com/official-stockfish/Stockfish/pull/4674
Its evaluation now purely relies on NNUE neural network.
So it's an good exmaple of the better lesson. More compute evently won against handwritten evaluation.
Stockfish developers thought old evaluation would help neural network so they kept the code for a few years, then it turned out that NNUE neural network didn't need any input of human chess knowledge.
In “The Bitter Lesson” is wrong. Well sort of(2016)
The comments on this fast range reduction are interesting, I recommend reading them (they're much longer than the post itself). Some highlights:
Versions of this exist as early as 1997, in CMU's Common Lisp implementation. Their GitLab is not loading quicky on my computer, but the commit is supposed to be from December by Douglas Crosher (https://lemire.me/blog/2016/06/27/a-fast-alternative-to-the-...).
The "Further reading" section (and comments) include implementations of the trick in the wild. Stockfish, the chess engine, used this optimization to reduce memory for storing precomputations of moves in their transposition tables (https://github.com/official-stockfish/Stockfish/commit/2198c...). The commit switches from using bitwise AND (&) and power-of-2 table sizes to using the modulo hash trick, which allows for full use of RAM
Read the rest
(even if it's not an exact power of 2). It's also used in Hashtron's modular hash: https://github.com/neurlang/classifier/blob/master/hash/hash..., a straightforward application of the optimization to avoid using modulo.
A GitHub gist with more information: https://github.com/sipa/writeups/tree/main/uniform-range-ext.... It walks through a couple of intuitive explanations on why this technique maintains maximum uniformity in the output distribution, as opposed to the proof in the post.
My point is that if the computer never flags it will have an inherent advantage in low time controls. If not, why not just test it in hyperbullet games? Games where humans flag in a drawn or winning position need to be excluded, otherwise it’s unclear what this is even measuring.
And limited depth games would not have been difficult to run. You can run a limited search Stockfish on a laptop using the UCI protocol: https://github.com/official-stockfish/Stockfish/wiki/UCI-%26...
In Grandmaster-level chess without searchI was wondering on how Stockfish encodes the destination and origin square in 5 bits each. I think they don't, at least the code on github uses 6 bits each, which actually gives you 64 possible values, so works out fine:
https://github.com/official-stockfish/Stockfish/blob/master/...
Thats 16 bits.
Thank you for sending me down that (small) rabbit hole!
In The rarest move in chess [video]The Stockfish program can be set to play at strength level 0-20. Estimates of the levels' Elo is provided here: https://github.com/official-stockfish/Stockfish/commit/a08b8...
In Manipulating Chess-GPT's World ModelNo, they removed the code in Stockfish 16, released June 30, 2023 but it wasn't used for much or made much difference before then, after they introduced the neural net.
https://github.com/official-stockfish/Stockfish/commit/af110...
In Advancements in machine learning for machine learningStop bringing meaningless opinions like “software should not crash”
1 points · Open discussionIncrease MAX_MOVES to prevent buffer overflow and stack corruption
4 points · Open discussionIt's milliseconds (well except for 0, which stockfish considers an edge case)
See: http://wbec-ridderkerk.nl/html/UCIProtocol.html , https://github.com/official-stockfish/Stockfish/issues/3720
That said I don't think a strong chess engine alone would be enough to pass this puzzle.
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