![]() More importantly, also for standard chess this release progressed and will win two times more game pairs than it loses against Stockfish 15. As a result, Elo gains are largest for FRC, reaching up to 50 Elo for doubly randomized FRC (DFRC). With this release, version 5 of the NNUE neural net architecture has been introduced, and the training data has been extended to include Fischer random chess (FRC) positions. ![]() Today, we have the pleasure to announce Stockfish 15.1.Īs usual, downloads will be freely available at /download Elo gain and competition results ![]() We invite all chess enthusiasts to join the Fishtest testing framework and contribute to the project. Together, this dedicated community works towards the common goal of developing a powerful, freely accessible, and open-source chess engine. The success of the Stockfish project relies on the vibrant community of passionate enthusiasts (we appreciate each and every one of you!) who generously contribute their knowledge, time, and resources. Finally, binaries of our latest development version are now provided continuously as pre-releases on GitHub making it easier for enthusiasts to download the latest and strongest version of the program, we thank Roman Korba for having provided a similar service for a long time. It is worth noting that the evaluation system remains consistent with Stockfish 15.1, maintaining the choice that 100cp means a 50% chance of winning the game against an equal opponent. Furthermore, the UCI_Elo option, to reduce its strength, has been calibrated. Additionally, Stockfish now includes a clear and consistent forced tablebase win score, displaying a value of 200 minus the number of plies required to reach a tablebase win. Stockfish now comes with documentation, found in the wiki folder when downloading it or on GitHub. Additionally, the Fishtest framework has been improved and is now able to run the tests needed to validate new ideas with 10000s of CPU cores. The search has undergone more optimization, leading to improved performance, particularly in longer analyses. The ongoing utilization of Leela’s data combined with a novel inference approach exploiting sparsity, and network compression ensure a speedy evaluation and modest binary sizes while allowing for more weights and higher accuracy. This updated version of Stockfish introduces several enhancements, including an upgraded neural net architecture (SFNNv6), improved implementation, and refined parameterization. Leela Chess Zero was the challenger in most finals, putting top-engine chess now firmly in the hands of teams embracing free and open-source software. In major chess engine tournaments, Stockfish reliably tops the rankings winning the TCEC season 24 Superfinal, Swiss, Fischer Random, and Double Random Chess tournaments and the CCC 19 Bullet, 20 Blitz, and 20 Rapid competitions. In self-play against Stockfish 15, this new release gains up to 50 Elo and wins up to 12 times more game pairs than it loses. Stockfish continues to demonstrate its ability to discover superior moves with remarkable speed. Note: There is a distortion in the Elo ratings for Stockfish 3 and Stockfish 4 due to 7 time forfeits (all by Stockfish 3 when playing Stockfish 4) that have not been replayed yet.A new major release of Stockfish is now available at /download Quality of chess play Total number of games: 159600 (games available upon request) Openings: 50 positions 2 moves deep (a subset of the openings used in round 2 of TCEC)Īdjudication: 450 cp for 4 moves draw after 120 moves if score < 50 cp for 4 moves Each version played each other 100 times (50 openings/reversed colors). For each month, I downloaded the last development version available on the 22nd day (the chosen day due to SF 2.3.1 being dated 2). ![]() For my measurement, I have used the generic Linux 64bit compiles available at . I have tried to measure the change in Elo for Stockfish, using Stockfish 2.3.1 (which I believe was the original "master" or reference version) as the reference. In addition, the successful ideas that have come out of Fishtest have had a definite effect on development of other computer chess engines. With contributions from over 900 developers and testers, who have supplied ideas for over 15,000 tests and given over 600 years of CPU time, Fishtest has led to the dramatic increase in strength of Stockfish. In conjunction with the use of GitHub, the development of Stockfish became a truly open and public project. In the first quarter of 2013, Gary Linscott created the distributed testing framework known as "Fishtest".
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