Author: Ian

The FIDE player list is a combination of the three ratings lists (standard, rapid, and blitz) but is very big and includes lots of players who are registered but have no rating. After running a Python script to keep only the players rated 2000 or above, I can provide a much smaller list that might also be more useful. In the MediaFire directory for 2025-01, you can find it in XML, CSV, JSON, XLSX, ODS, and TXT.

https://www.mediafire.com/folder/kpyvsijjhsiiw/2025-01

This is a Python file which has been converted to EXE — along with the original Python script, if you’re not on Windows — which takes as its only argument a path to a PGN. If not specified, it will prompt you for it during runtime. This program provides information on a PGN — namely the number of players, the number of games, the number of events, and the highest and lowest Elo. It will also prompt you to ask whether or not you want a text file list of players, and if you want a text file list of sites/events.

https://www.mediafire.com/file/g9snnwefprj8btp/PGN-Info.zip/file

This is a combination of the Chesscom Elite db (which covers 2020-12 to 2024-12) and the Lichess Elite db (which covers 2013-01 to 2024-12).

Covers 2014-12 to 2024-12. Every game has players rated at least 2500, the games are between 20-150 moves, and they end in checkmate. Doubles, bullet games and non-standard games have been removed. Openings, plycount and evaluations have been added in.

1,829,705 games:
https://www.mediafire.com/file/nev27dqeqjnqtbg/online-superelite-240109.zip/file

Author(s): Marco Zerbinati (ITA)
Release Date: 2025-01-08
Language(s): C++
Repo Owner: Zerbinati
Repo URL: https://github.com/Zerbinati/HypnoS-plus

HypnoS ++ is a free and strong UCI chess engine derived from Stockfish that analyzes chess positions and computes the optimal moves. HypnoS ++ does not include a graphical user interface (GUI).

https://github.com/Zerbinati/HypnoS-plus/releases/download/H1.0/windows.builds.7z
https://github.com/Zerbinati/HypnoS-plus/archive/refs/tags/H1.0.zip

Stockfish 17 source:
https://github.com/official-stockfish/Stockfish/archive/refs/tags/sf_17.zip

Author(s): Liam McGuire (USA), Eduardo Cáceres (ESP)
Release Date: 2025-01-08
Language(s): C#
Repo Owner: liamt19
Repo URL: https://github.com/liamt19/Lizard

Has a more complex network and a few search tweaks/additions. For the sake of my sanity (and because .NET can’t/doesn’t autovectorize NNUE code), this requires at least AVX2 to be performant, but will still function without it.

A Note On Bindings

This release includes C++ code from Horsie to make NNUE evaluation faster. This code is only used if your processor supports AVX2.

The Windows and Linux releases here already have it compiled and embedded as a .dll/.so within it. For technical reasons this embedded file will automatically extract itself into a file called HorsieBindings.dll/HorsieBindings.so which Lizard will try to use when it launches.

You will see “Loaded Horsie bindings!” if they are successfully loaded, or “Running without Horsie bindings” if they aren’t. The bindings aren’t required, but they do make Lizard significantly faster.

Picking A Binary

Use a …-512 binary if your processor has Avx512.
AOT binaries aren’t being included here because they are strictly slower.

https://github.com/liamt19/Lizard/releases/download/v11.2/Lizard-11_2-arm64
https://github.com/liamt19/Lizard/releases/download/v11.2/Lizard-11_2-linux
https://github.com/liamt19/Lizard/releases/download/v11.2/Lizard-11_2-linux_512
https://github.com/liamt19/Lizard/releases/download/v11.2/Lizard-11_2-win-512.exe
https://github.com/liamt19/Lizard/releases/download/v11.2/Lizard-11_2-win.exe
https://github.com/liamt19/Lizard/archive/refs/tags/v11.2.zip

 

Author(s): Marco Zerbinati (ITA)
Release Date: 2025-01-06
Language(s): C++
Repo Owner: Zerbinati
Repo URL: https://github.com/Zerbinati/JudaS-Plus

JudaS ++ is a free and strong UCI chess engine derived from Stockfish that analyzes chess positions and computes the optimal moves. JudaS ++ does not include a graphical user interface (GUI).

https://github.com/Zerbinati/JudaS-Plus/releases/download/J2.0/windows.builds.7z
https://github.com/Zerbinati/JudaS-Plus/archive/refs/tags/J2.0.zip

Stockfish 17 source:
https://github.com/official-stockfish/Stockfish/archive/refs/tags/sf_17.zip

Author(s): Thorsten Greiner (GER)
Release Date: 2025-01-07
Language(s): C++
Repo Owner: thgreiner
Repo URL: https://github.com/thgreiner/amy

What’s Changed

Full Changelog: v0.9.5…v0.9.6

https://github.com/thgreiner/amy/releases/download/v0.9.6/amy-0.9.6.tar.gz
https://github.com/thgreiner/amy/archive/refs/tags/v0.9.6.zip

Eubos chess is a multi-threaded Java chess engine. Eubos uses a standard alpha-beta negascout algorithm with transposition hashing and quiescence search extension. It uses lazy move generation and lazy evaluation.

The evaluation function takes account of the following factors

  • material balance
  • piece mobility
  • pawn structure
  • king safety
  • tactical threats

It knows about draws by 3-fold repetition and insufficient material.

https://github.com/cjbolt/EubosChess/releases/download/v3.8/Eubos.bat
https://github.com/cjbolt/EubosChess/releases/download/v3.8/Eubos.jar
https://github.com/cjbolt/EubosChess/archive/refs/tags/v3.8.zip

Author(s): Colin Jenkins (GBR)
Release Date: 2025-01-06
Language(s): JavaScript
Repo Owner: op12no2
Repo URL: https://github.com/op12no2/lozza

Lozza was primarily created for use in browsers, but can also be used with traditional chess UIs via Node.js and on pretty-much any platform (see below). Note however that Lozza is relatively slow compared to compiled engines of a similar design, which also makes her relatively weak.

This is a Lozza 4 re-release.

The original Lozza 4 release caused problems for some users. For those that ran it successfully, results (e.g. CCRL Blitz) can stand because no peformative changes have been made. However, please replace with this re-release anyway; thanks.

Please use a recent version of Node if possible (they are always improving performance). The latest stable version is 22.

https://nodejs.org

Changes

Train generation 3 net.
Use ADJACENT, not DIST.
Simplify QS and don’t go into QS if in check.
Scale eval by 1.9. Scale UCI cp by 1.9.
Add perspective (currently unused).
Use the Mersene Twister from cwtch for randoms.
Move futility alpha test to move loop.
Use hash move in QS.
Optmise deferral of accumulator update a bit more.
Fix some web stuff. Add improving indicator (failed to get it to gain so far).
Prune QS with quickSee(). Only count nodes that iterate moves.
Put eval in TT before search.
Optimise castling a bit.
Simplify search recursion.
Allow successive NMP and beta pruning.
Bigger net 768x128x1 srelu.
Make sure all UE updates (e.g. castling) are a single accumulator loops.
Defer UE to after legal check (doh!) and don’t check pre-determined legal moves.
Minor tweaks for datagen + net command.

https://github.com/op12no2/lozza/releases/download/4/lozza4.zip
https://github.com/op12no2/lozza/archive/refs/tags/4.zip

Release Date: 2025-01-01
Repo Owner: rubenkku
Repo URL: https://github.com/rubenkku/PGN-Book-Creator

Changes in this release:

  • Fixed a bug where some moves were not being saved correctly in the BIN book.
  • Fixed an issue with pawn promotions: now, when promoting a pawn, a menu opens allowing you to choose the promotion piece.
  • Improved the speed of pasting a PGN game.
  • Fixed an issue when importing all moves “to current position” in the BIN editor.
  • Resolved a bug where multiple “add move” windows could be opened simultaneously, now only one window can open at a time.
  • Enhanced the UCI protocol by using “startpos” instead of “fen” for sending the position.

https://github.com/rubenkku/PGN-Book-Creator/releases/download/3.1/PGN.Book.Creator.3.1.exe
https://github.com/rubenkku/PGN-Book-Creator/archive/refs/tags/3.1.zip

Author(s): Peter Österlund
Release Date: 2025-01-05
Language(s): C++
Repo Owner: peterosterlund2
Repo URL: https://github.com/peterosterlund2/texel

Neural network improvements:

  • Speed up matrix multiplication for AVX-512.
  • New network based on new training data.
  • Use 4 “heads” (all NN layers except the first) for evaluation. The active head depends on the number of pieces on the board.
  • Increase NN layer 1 output size from 256 to 384.

Tablebases:

  • Measure thinking time more accurately. Useful when TB files are on mechanical disks.
  • Better handling of DTZ scores in search.
  • Avoid expensive (wrong side to move) DTZ probes in search.
  • Add UCI parameter to control required search depth for DTZ probes.
  • Measure time required to perform a TB probe instead of guessing. This avoids time losses in fast games when TB files are on mechanical disks.
  • Allow RTB WDL probes in some cases even if hmc > 0.
  • Change TB swindle depth from 16 to “15+minProbeDepth”, to avoid slowdown in late middlegame/early endgame when TB files are on mechanical disks.

Search:

  • Implement the counter move heuristic.
  • Implement multi-cut pruning based on singular search score.
  • Adjust singular extension search parameters.
  • Allow both extension and reduction in the same search node.
  • Remove no longer useful “recapture” and “going into pawn endgame” extensions.
  • Reduce aspiration window size.

Other:

  • Use multiple threads to initialize the transposition table.
  • Better handling of mate scores in the transposition table.
  • Fix handling of empty strings in UCI string options.

https://github.com/peterosterlund2/texel/releases/download/1.12/texel112.7z
https://github.com/peterosterlund2/texel/archive/refs/tags/1.12.zip

https://www.mediafire.com/file/g5wy1ycjcdz9i6u/LichessDownloader.zip/file

This script will prompt you for beginning and end year/month, then download everything you ask for, extract each one, and filter each one in pgn-extract according to certain criteria that can be changed.

This is what the file pgn-extract-command.txt looks like:

pgn-extract.exe {input} -t tags.txt -R roster.txt --xroster --minmoves 10 --maxmoves 150 --fixresulttags --fixtagstrings --nosetuptags -e --checkmate --plycount --evaluation -D -w9999 -o {output}

Anything from -t to -w can be changed. For instance, if you want to change the minimum and maximum moves — or to take one or both parameters out, here’s the place to do it. If you want to take out the requirement that a game end in checkmate, just take out the –checkmate option. The –evaluation option is what creates those evaluations for each move. The -w9999 is what makes each movelist one line. -D checks for doubles, -e specifies that you want ECO information and opening names. (Which is what eco.pgn is for.) If you want to change the contents of tags.txt, you’d either be changing the minimum Elo for either white or black, or the minimum time control — or taking any of those requirements out. The roster.txt file is a list of tag names, one per line, that define the order those tags go in. Specifying –xroster means that it will remove any tags *not* in the roster, as well as put them in the same order.

Because this script needs pgn-extract.exe to run, it’s necessary to keep the binary and all of its dependent files in the same directory as the script.

https://www.mediafire.com/file/hey6lzegqzzc76z/FilterPGNByElo.zip/file

This is a C program written by ChatGPT o1, at my direction. To be clear, I know nothing about coding, especially in a low-level language. The form that the command takes is:

FilterPGNByElo.exe <input_path> <output_path> <minimum_elo>

For example:

FilterPGNByElo.exe lichess_db_standard_rated_2016-11.pgn lichess-2016-11.pgn 2300

It should be run in the same directory as the executable, at least for the command to take the form above. If you wanted, you could have each path be a full path. If there are any spaces in the path, you should surround it with double quotes.

It should be noted that because this is written in C and optimized for speed, it runs bizarrely fast. It finishes a gigabyte in about two seconds. It should also be noted that for the same reasons, it’s just going to do it, and not check to make sure there’s enough room. So if you are filtering a very large PGN, make sure you have enough space and resources.