31 Best Chess Engines of 2024 | Based On Their Ratings

A chess engine analyzes thousands of outcomes before making an efficient move. It’s an intricate software program that blends brute-force calculation, positional evaluation, pattern recognition, and sometimes neural networks to make decisions in a game of chess. 

The number of possible moves makes chess one of the most complex games 

If you construct a complete tree of all possible moves in a chessboard, you will get a total of 10¹²⁰ moves. That’s an extremely large number.

To put this into perspective, there have been only 10²⁶ nanoseconds since the Big Bang and about 10⁷⁵ atoms in the entire universe. These numbers are dwarfed by the number of possible moves in chess, making it one of the most complex board games.

Chess Engines Outperform human decision-making

Since the hardware and software programming techniques are improving year by year, chess engines are becoming more intelligent. Modern engines are more selective and have a better positional understanding.

Every year, engines like Stockfish and Komodo further push the boundaries of chess, advancing opening theory, tactical analysis, and endgame play. Innovations like neural networks and sophisticated evaluation functions have become commonplace, allowing chess engines to outperform human decision-making. 

Selection Criteria 

There are literally hundreds of ‘rating lists’ that measure the relative strength of chess engines based on how many moves they make per minute. Not only do these lists rank chess engines from superior to inferior, but they also furnish margin of error values for the assigned ratings.

Among these rating lists, the most famous are CCRL (Computer Chess Rating Lists) and CEGT (Chess Engines Grand Tournament). With both of these ratings in consideration, we introduce the most advanced Chess Engines, exemplifying the supremacy of machines over human players.

Note: Since CCRL and CEGT rating lists change continuously, the ranking can differ from time to time.

31. Hannibal

CCRL Rating: 3146
CEGT Rating: 3085

Hannibal is a Universal Chess Interface (UCI) engine that builds upon concepts from prior engines, namely Twisted Logic and LearningLemming. It utilizes the alpha-beta technique along with various chess-specific strategies and employs a selective search approach.

In addition to its extensive endgame expertise, Hannibal demonstrates a strong grasp of material imbalances. It also understands the fortresses and trapped pieces and can sacrifice material to gain an edge in king attacks.

Moreover, Hannibal’s time management is tuned for the Fischer time controls.

30. Critter

CCRL Rating: 3149
CEGT Rating: 3089

Critter is the UCI-compliant chess engine available for Windows, Mac, Android, and Linux. You can use it for private purposes only.

It was initially written in Delphi but later converted to C++ using Bitboard technology. This was done to enhance its performance on 64-bit processors.

This chess engine features null move pruning, forward pruning, principal variation search, parallel search with up to 8 threads, and blockage detection in the endgames.

29. Suger XPro

CCRL Rating: 3533

SugaR engine is derived from Stockfish and supports up to 128 cores. Like other popular engines such as Stockfish, SugaR is not a complete chess program. It requires a compatible GUI, such as XBoard with Arena, PolyGlot, Shredder, Sigma Chess, and Chess Partner.

Since the engine is distributed under the General Public License, you are allowed to modify and sell it.

28. asmFish

CCRL Rating: 3506

asmFish is a Stockfish engine port written in x86 assembly language. It uses BMI2 and AVX2 instructions optionally. It is assembled with FASM for Linux and Windows platforms.

asmFish is built with some structural optimization techniques, such as the elimination of piece lists. The critical functions in this engine do not adhere to the x86-64 ABI with respect to register usage and calling conventions. 

Nevertheless, the engine is NUMA (non-uniform memory access) aware and supports parallel search and large pages.

27. Chiron

CCRL Rating: 3245
CEGT Rating: 3130

Chiron is the commercial chess engine that supports both Universal Chess Interface and Chess Engine Communication Protocol, as well as several endgame tablebase and bitbase formats.

It applies a parallel search on multiprocessor architectures and implements pawn blockage detection that not only detects blockages in pawn endgame but also identifies other pieces on the board.

The latest version has been tuned deeply, especially in the context of passing pawns and mobility. Several advanced search enhancements have also been introduced, such as Lazy symmetric multiprocessing, forward pruning, and NUMA awareness

26. Equinox

CCRL Rating: 3164
CEGT Rating: 3112

Equinox is a symmetric multiprocessing chess engine primarily developed by Giancarlo Delli Colli. It is inspired by popular open-source engines like Stockfish, Crafty, and Ippolit.

Equinox is active in several private engine tournaments, including the Italian Open Chess Software Cups and Thoresen Chess Engine Competition.

25. GullChess

CCRL Rating: 3261
CEGT Rating: 3183

GullChess is an open-source chess engine that applies magic bitboards to determine sliding piece attacks. It is mostly written in C++ and contains only one source file.

Gull Engine features generic function templates in recursive search routines, as well as several other functions for move generation (excluding ‘hash move’ and ‘side to move’).

24. Schooner

CCRL Rating: 3246
CEGT Rating: 3177

Schooner uses alpha-beta search, late move reductions (LMR), principle search window (PVS), and single hash entry. It supports a subset of Universal Chess Interface to automatically play games without hogging a lot of resources.

Its performance has been improved significantly in recent years: a simpler evaluation inspired by Xiphos, staged move generation, and tons of testing and tuning are responsible for those improvements.

23. Xiphos

CCRL Rating: 3324
CEGT Rating: 3265

Xiphos is an open-source chess engine written in C and distributed under GNU General Public License. It’s a UCI-compliant engine that utilizes bitboards with ERLEF mapping.

Xiphos uses sliding piece attacks, which are evaluated by either PEXT bitboards (for BMI2) or magic bitboards. If you want to try, you can run this engine on Windows, macOS, and Linux.

22. Deep Shredder

CCRL Rating: 3266
CEGT Rating: 3213

Shredder is a commercial chess engine developed in 1993. It has won more than 20 titles, including the World Microcomputer Chess Championship (1996, 2000), the World Computer Chess Championship (1999, 2003), the World Chess Software Championship (2010), and the World Computer Speed Chess Championship (5 times).

Deep Shredder is the multiprocessor version of Shredder. It comes with a graphical user interface developed by Millennium Chess System, which supports Universal Chess Interface and is compatible with other UCI engines available for Mac OS, Windows, and Linux.

21. Booot

WCCC 2011, Booot vs. Alex Morozov 

CCRL Rating: 3326
CEGT Rating: 3396

Booot is an open-source chess engine written in Delphi 6. It determines sliding piece attacks with rotated bitboards. It is packed with lazy SMP and a fully redesigned evaluation function.

The engine applies PVS with all basic search enhancements like late move reductions, null move pruning, and internal iterative deepening. The latest version supports multiprocessor architecture and has several assembly variants for 32 and 64-bit.

20. Andscacs

CCRL Rating: 3250
CEGT Rating: 3200

First published in 2014, Andscacs soon became one of the world’s best chess engines. It uses a magic bitboard to speed up the attack calculations. It applies a principal variation search with a transposition table inside an iterative framework.

Andscacs employs static exchange evaluation and a threaded parallel search. Additionally, it attempts a hash move during a quiescence search.

In order to make the engine more powerful and efficient (or minimize the standard deviation of static evaluation), developers optimized 200 evaluation features with 750,000 positions. 

19. Caissa

CCRL Rating: 3464
CEGT Rating: 3445

Caissa is a relatively new chess engine developed from scratch in C++. It is optimized for conventional chess, Fischer Random Chess (FRC), and Double Fischer Random Chess (DFRC). 

The engine follows a UCI protocol, which makes it compatible with various chess GUIs. It employs a neural network for evaluating positions. This neural network is trained using self-play games generated by Caïssa’s custom trainer. 

It uses the Negamax search algorithm along with alpha-beta pruning — a common and efficient technique to explore and evaluate positions during the search. 

Moreover, Caissa supports Syzygy and Gaviota endgame tablebases, which help in endgame play and ensure optimal decisions in positions with fewer pieces. 

18. Ethereal

CCRL Rating: 3483
CEGT Rating: 3517

Ethereal is greatly influenced by numerous chess engine projects like Stockfish, Crafty, MadChess, TSCP, and Fruit. It’s a UCI-compliant chess engine based on the alpha-betta framework.

The commercial version of Ethereal incorporates two Neural Network Universal Evaluations (NNUEs) for assessment, one designed for standard chess and another specifically trained for Chess960.

The NNUE implementation, based on Stockfish NNUE, illustrates how developers can significantly boost their engines’ playing strength with minimal effort.

17. Koivisto

CCRL Rating: 3466
CEGT Rating: 3516

Written in C++, Koivisto is a strong chess engine that features lazy SMP, iterative deepening, and principal variation search. It’s important to note that Koivisto is not a standalone program and requires a UCI-compatible graphical user interface to function.

The bitboard engine offers automated evaluation tuning by logistic regression, either using stochastic gradient descent or an adaptive gradient algorithm. You can find binaries for Windows and Linux on GitHub.

16. Fizbo

CCRL Rating: 3257
CEGT Rating: 3220

Fizbo is a Chess Engine Communication Protocol, first released in 2014. This engine is founded on the bitboard approach and leverages the population count instruction. As of now, it is compatible with the Windows operating system and requires a CPU with pop-count instructions.

Besides iterative deepening, Fizbo performs parallel searches using an enhanced PV splitting algorithm. Moreover, it utilizes a transposition table with 8-byte entries in the quiescence search.

15. Igel 

CCRL Rating: 3482
CEGT Rating: 3458

Igel is a UCI-compliant, open-source chess engine written in C and C++. It primarily utilizes Neural Network Evaluation (NNUE) as its main evaluation function. It relies on Dietrich Kappe’s NiNu network file, which is a neural network-based evaluation system. 

Developers have introduced their own class of neural networks, known as Igel Generation Network (IGN). These networks have specific rules for data generation and training. 

Developers offer transparency by making the source data of the network available for validation and external training, promoting a fair and open approach to network development and use in chess tournaments.

14. Fire

CCRL Rating: 3412
CEGT Rating: 3368

Fire is a free chess engine that was previously open-source but later transitioned into a closed Windows executable. It is specifically designed for new Intel processors. Originally, it was known as Firebird but had to be renamed to “Fire” due to trademark naming conflicts.

The Fire engine features magic bitboards, Syzygy tablebases, configurable hash, and multiPV. You can configure it with over 70 Universal Chess Interface options and apply SMP parallel search.

13. Revenge

CCRL Rating: 3467
CEGT Rating: 3343

The Revenge chess engine, originally named Pedone and under development since 2013, is compatible with both Windows and Linux. It’s important to note that its console program requires a graphical user interface (GUI) to function effectively.

The inclusion of a larger neural network in this chess engine significantly enhances its performance across all game phases, particularly in the endgame. It has higher depth for history pruning, improved history move ordering, enhanced reduction formula, and advanced speed optimization in search.

12. Minic

CCRL Rating: 3440
CEGT Rating: 3374

Minic is an open-source written in C++ and licensed under the GPL v3.0. While it has no GUI, it is compatible with both the Chess Engine Communication Protocol (CECP) and the Universal Chess Interface (UCI) protocol.

This allows users to integrate it with their preferred chess software, such as Cutechess, Arena, Banksia, and Winboard/Xboard. 

The latest version of the engine has detached its dependency on the Stockfish NNUE (Noisy Neural Network Updates Estimation) and implemented its own NNUE system. This adoption of NNUE allows Minic to easily change the neural network architecture and apply engine-independent PyTorch training code.

The latest engine introduced support for a new NNUE variant called “Seer-like NNUE Narcotized Nightshift.” This new NNUE variant appears to have significantly improved Minic’s playing strength, with a reported gain of nearly 90 Elo points compared to the previous NNUE version called “Nefarious Nucleus.”

11. Seer 

CCRL Rating: 3446
CEGT Rating: 3483

Seer is a strong UCI-compliant chess engine that stands out for its reliance on a neural network-based evaluation system. It employs a neural network for position evaluation, with a specific focus on estimating Win-Draw-Loss (WDL) probabilities.

It features a custom implementation of Noisy Neural Network Updates Estimation (NNUE). This custom NNUE system uses 32-bit float weights and has both training code (for learning from data) and inference code (for evaluation during chess games).

The engine utilizes Principal Variation Search (PVS) within an iterative deepening framework and employs a lockless shared transposition table based on Zobrist hashing to store previously evaluated positions. 

It also incorporates history pruning, history extensions, static null move pruning, futility pruning, and late move reductions. These techniques help to improve the efficiency of the search and evaluation process.

More recently, Seer has extended its support to ARM NEON through sse2neon, making it compatible with a broader range of devices, including Android devices.

10. Chess System Tal 

CCRL Rating: 3486
CEGT Rating: 3484

Chess System Tal (CSTal) is a commercial chess program developed in the mid-1990s as the successor to the Complete Chess System. Over the years, it has evolved into a unique and entertaining chess engine with specific characteristics and playing styles.

It is famous for its distinctive playing style, which emphasizes strong human-like play with a particular focus on aggressive king attacks and speculative sacrifices. 

In 2023, developers released Chess System Tal 2.00, marking a significant development in the engine’s evolution. This version is UCI-compliant, which makes it more accessible to various chess graphical user interfaces. 

Chess System Tal 2.00 comes in two variations: 

• One version is designed for Elo strength, meaning it is engineered to perform at specific rating levels, offering a competitive challenge to players of varying skill levels.
• The other version is tailored to emulate the legendary style of Mikhail Tal. This version is focused on replicating the daring and attacking style for which Tal was renowned.

The engine is made available to the public in the form of a public executable, which means users can run the program, but the underlying source code is not publicly disclosed. This approach allows users to enjoy the chess engine’s features while preserving the proprietary nature of the source code. 

9. RofChade

CCRL Rating: 3477
CEGT Rating: 3494

RofChade is a UCI-compliant chess engine written in C++. It has undergone several significant developments to enhance its playing strength.

Initially, RofChade used a tapered evaluation system that distinguished between middlegame and endgame material. l. It also utilized asymmetrical piece-square tables and featured a sophisticated parallel search algorithm. 

A notable evolution in the engine is its adoption of a neural network-based evaluation system. Its current network architecture is called HALFKA — it plays a central role in evaluating positions and guiding RofChade’s move choices.

The network has been trained with a substantial dataset of positions, including approximately 2.8 billion generated by RofChade. Among these positions, around 600 million are specific to Fischer Random Chess (FRC).

The implementation of this network is inspired by Cfish, and its training base is linked to Stockfish. This indicates that RofChade benefits from the experience and techniques used by Stockfish in training neural networks.

8. Berserk

CCRL Rating: 3489
CEGT Rating: 3529

Berserk is a UCI-compliant open-source chess engine written in the C programming language. It supports two board representations: Bitboards and Magic Bitboards.

The latest version brings significant improvements in its search algorithms, time management, and evaluation capabilities. It has its own network architecture, which features NNUE evaluation, reverse futility pruning, delta pruning, quiescence search, and singular extensions.

7. Slow Chess

CCRL Rating: 3457
CEGT Rating: 3528

Slow Chess is a chess engine written in C++ and inline assembly that adheres to WinBoard and UCI standards. Unlike other chess engines, it has its own graphical user interface.

It includes an Analyze mode, allowing it to recommend the best move for any position and generate multi-variation moves. Players benefit from features like text transcript copy-pasting, position setup, move redo options, time-limit configuration, and the ability to adjust the difficulty level by specifying the number of ply or nodes.

6. RubiChess 

CCRL Rating: 3491
CEGT Rating: 3495

RubiChess is an open-source chess engine distributed under the GNU General Public License (GPL). It has undergone significant development and improvements over the years, making it a competitive and capable chess-playing program.

It initially used rotated bitboards and subsequently implemented magic bitboards to determine sliding piece attacks. This transition to bitboards likely contributed to a significant performance boost, as magic bitboards are known to be approximately 24% faster in determining sliding piece attacks compared to other methods. 

It later introduced a neural network-based evaluation system to further enhance its playing strength. 

RubiChess is recognized in various chess rankings and participates in many chess tournaments, demonstrating its capabilities and competitiveness within the chess community.

5. Houdini

CCRL Rating: 3380
CEGT Rating: 3414

Houdini is renowned for its distinct positional style, remarkable defensive capabilities, resilience in challenging positions, and its capacity to secure draws.

To date, Houdini has emerged victorious in three seasons of the Top Chess Engine Championship.

Its latest version is available in two variations: Standard and Pro. In contrast to the previous version, which could utilize a maximum of 8 processor cores, the Pro version supports an impressive 128 cores and 128 GB of RAM.

Moreover, the chess engine is NUMA-aware and can effectively utilize Nailmov endgame table bases.

4. Leela Chess Zero

CCRL Rating: 3368
CEGT Rating: 3549

Inspired by Deepmind’s research about AlphaZero and AlphaGo Zero, Leela Chess Zero relies on a self-taught neural network to make smart moves. The network learns through deep learning techniques by playing against itself millions of times.

Instead of using conventional AlphaBeta search with handcrafted evaluation functions, it utilizes a type of Monte Carlo Tree Search (MCTS) referred to as PUCT.

To unlock its full potential,, you must run the chess engine on a CUDA-supported GPU.

3. Fat Fritz 2

CCRL Rating: 3559
CEGT Rating: 3551

Introduced in 2021, Fat Fritz 2 is built on NNUE technology and Stockfish 12, featuring a doubled network size. Unlike its predecessor, it efficiently runs on a CPU and doesn’t require any expensive graphic cards for game playing.

Fat Fritz 2 combines the best of both worlds — a large new neural network trained by Albert Silver with the original Fat Fritz and the precision of Stockfish’s alpha-beta search. 

2. Komodo

CCRL Rating: 3524
CEGT Rating: 3602

Komodo was derived from an older search engine, Doch, as a major rewrite and a port of Komodo to C++11. Since it relies on evaluation (instead of depth), it has a quite different positional style.

The engine supports up to 64 cores, Syzygy endgame tablebase, and Fischer random chess. Kodomo lets you save the engine’s analysis of a position so you can check it later and resume analysis. You can also control how the engine makes long-term sacrifices of pawn structure for dynamic play.

In 2020, Komodo Chess introduced Dragon Chess, which incorporates the utilization of efficiently updatable neural networks in its evaluation function. 

In certain tournaments, such as the Top Chess Engine Championship and the World Computer Chess Championship (WCCC), Dragon is referred to as “Komodo Dragon.” However, in events like the Chess.com Computer Chess Championship (CCC), it’s simply known as “Dragon.”

To date, Komodo has secured victory three times in the Top Chess Engine Championship.

Aside from Stockfish and Lc0, which chess engine have you used?

— Chessify (@ChessifyMe) October 3, 2023

1. Stockfish

CCRL Rating: 3546
CEGT Rating: 3612

Stockfish, an open-source UCI-compliant chess engine, has consistently claimed the top position in the majority of chess engine rating lists.

Written in C++, this engine boasts the capacity to leverage 1024 CPU threads on multiprocessor systems, and its transposition table can reach a maximum size of 32 terabytes.

Stockfish employs a sophisticated alpha–beta search method and utilizes bitboards. One of Stockfish’s standout features is its remarkable search depth (achieved through aggressive pruning and late move reductions). 

Stockfish 16 is here. Improved playing strength, and updated neural net architecture, improved table base win scores, and more: https://t.co/IQPyXBRNgC

— Stockfish Chess (@stockfishchess) June 30, 2023

It has also been popular on various platforms. On desktop computers, for example, it serves as the default chess engine included with the Internet Chess Club interface programs like Dasher and BlitzIn. On mobile devices, it is integrated with apps like Droidfish and SmallFish. 

Since 2020, Stockfish has secured victory in all major events within the Chess.com Computer Chess Championship (CCC and the Top Chess Engine Championship (TCEC).

Frequently Asked Questions

When was chess invented?

The early form of chess, called chaturaṅga, originated in India in the 7th century CE. From there, it spread to Persia and southern Europe. The game later evolved roughly into its current form by 1500 CE.

Who wrote the first chess-playing program for computers?

In 1948, Alan Turing and David Champernowne developed the first chess program named Turochamp. It could play an entire chess game against a human player by computing all moves and all potential opponent’s moves in response. However, its algorithm was too complicated to be executed by the early machines of the time.

In 1957, Alex Bernstein wrote a chess program for the IBM 704. It was the first full-fledged chess program to be run on a computer. The program did a 4-ply search in 8 minutes.

What’s the difference between chess engines and chess software?

While a chess engine is the computational brain that evaluates the moves and plays the game, chess software compasseses the engine along with a graphical user interface and additional functions to make the game more accessible and enjoyable.   

Chess Engine	Chess Software
Focuses on calculating moves and evaluating positions	Comprehensive package that includes engines and offer additional features
Typically do not have a user-friendly interface	Comes with GUI, allowing users to interact with the engine and access various chess functions
Primarily focused on calculations and analysis	Combines engines with user interfaces and database management tools
May lack training and learning features	Often includes training modules and tutorials to help players improve their skills

What are the names of open-source chess engines?

There are many open source chess engines that benefit from contributions from a global community of developers and chess enthusiasts. The most popular ones are

1. Stockfish 
2. Komodo
3. Leela Chess Zero
4. Fire
5. Crafty
6. Xiphos
7. Fruit
8. Sjeng
9. Phalanx
10. Arasan

Are chess computers unbeatable?

In 1996, Deep Blue became the first computer to beat a human in a formal chess game. This specially designed IBM supercomputer beat the Russian chess grandmaster Garry Kasparov in the first game of a six-game match.

However, over two decades have passed since that momentous event. Present-day computers have grown so immensely powerful that they have essentially become invincible.

Even a high-end general-purpose computer (running on a well-optimized algorithm) can analyze millions of possible moves and compare them against each other within seconds. No human mind can compete with such analytical powers.

What is AlphaZero?

Developed by AI research company Deepmind, AlphaZero is a computer program designed to master the games of shogi, go, and chess. It uses neural networks to evaluate a specific number of positions, which eliminates the need to look over millions of positions per second (like other conventional chess engines do).

More specifically, AlphaZero analyzes 80,000 positions per second in chess compared to 70 million for Stockfish. In 2017, AlphaZero defeated the then world’s strongest chess engine, Stockfish, in a one-sided 100-game match. The results were published in Science Journal.

Although AlphaZero isn’t available on any public platform, it has inspired many developers to create open-source network chess projects. AllieStein and Leela Chess Zero, for example, try to mimic AlphaZero’s learning method.

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