## Overview
-[](https://travis-ci.org/official-stockfish/Stockfish)
+[](https://github.com/official-stockfish/Stockfish/actions)
[](https://ci.appveyor.com/project/mcostalba/stockfish/branch/master)
[Stockfish](https://stockfishchess.org) is a free, powerful UCI chess engine
to be used comfortably. Read the documentation for your GUI of choice for information
about how to use Stockfish with it.
-The Stockfish engine features two evaluation functions for chess, the classical
-evaluation based on handcrafted terms, and the NNUE evaluation based on efficiently
-updatable neural networks. The classical evaluation runs efficiently on almost all
-CPU architectures, while the NNUE evaluation benefits from the vector
-intrinsics available on most CPUs (sse2, avx2, neon, or similar).
-
+The Stockfish engine features two evaluation functions for chess.
+The efficiently updatable neural network (NNUE) based evaluation is the default and by far the strongest.
+The classical evaluation based on handcrafted terms remains available.
+The strongest network is integrated in the binary and downloaded automatically during the build process.
+The NNUE evaluation benefits from the vector intrinsics available on most CPUs (sse2, avx2, neon, or similar).
## Files
This distribution of Stockfish consists of the following files:
- * Readme.md, the file you are currently reading.
+ * [Readme.md](https://github.com/official-stockfish/Stockfish/blob/master/README.md), the file you are currently reading.
+
+ * [Copying.txt](https://github.com/official-stockfish/Stockfish/blob/master/Copying.txt), a text file containing the GNU General Public License version 3.
- * 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
+ * [AUTHORS](https://github.com/official-stockfish/Stockfish/blob/master/AUTHORS), a text file with the list of authors for the project
- * src, a subdirectory containing the full source code, including a Makefile
+ * [src](https://github.com/official-stockfish/Stockfish/tree/master/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
+ * a file with the .nnue extension, storing the neural network for the NNUE
evaluation. Binary distributions will have this file embedded.
## The UCI protocol and available options
-The Universal Chess Interface (UCI) is a standard protocol used to communicate with a chess engine,
-and is the recommended way to do so for typical graphical user interfaces (GUI) or chess tools.
+The Universal Chess Interface (UCI) is a standard protocol used to communicate with
+a chess engine, and is the recommended way to do so for typical graphical user interfaces
+(GUI) or chess tools. Stockfish implements the majority of its options as described
+in [the UCI protocol](https://www.shredderchess.com/download/div/uci.zip).
-Stockfish implements most commands as described in [the UCI protocol](https://www.shredderchess.com/download/div/uci.zip)
-
-For users, the following UCI options, which can typically be set via a GUI, are available in Stockfish:
+Developers can see the default values for UCI options available in Stockfish by typing
+`./stockfish uci` in a terminal, but the majority of users will typically see them and
+change them via a chess GUI. This is a list of available UCI options in Stockfish:
* #### Threads
The number of CPU threads used for searching a position. For best performance, set
Example: `C:\tablebases\wdl345;C:\tablebases\wdl6;D:\tablebases\dtz345;D:\tablebases\dtz6`
It is recommended to store .rtbw files on an SSD. There is no loss in storing
- the .rtbz files on a regular HD. It is recommended to verify all md5 checksums
+ the .rtbz files on a regular HDD. It is recommended to verify all md5 checksums
of the downloaded tablebase files (`md5sum -c checksum.md5`) as corruption will
lead to engine crashes.
Limit Syzygy tablebase probing to positions with at most this many pieces left
(including kings and pawns).
- * #### Contempt
- A positive value for contempt favors middle game positions and avoids draws,
- effective for the classical evaluation only.
-
- * #### Analysis Contempt
- By default, contempt is set to prefer the side to move. Set this option to "White"
- or "Black" to analyse with contempt for that side, or "Off" to disable contempt.
-
* #### Move Overhead
Assume a time delay of x ms due to network and GUI overheads. This is useful to
avoid losses on time in those cases.
For developers the following non-standard commands might be of interest, mainly useful for debugging:
+ * #### bench *ttSize threads limit fenFile limitType evalType*
+ Performs a standard benchmark using various options. The signature of a version (standard node
+ count) is obtained using all defaults. `bench` is currently `bench 16 1 13 default depth mixed`.
+
* #### compiler
Give information about the compiler and environment used for building a binary.
- * #### flip
- Flips the side to move.
-
- * #### bench ttSize threads limit fenFile limitType evalType
- Performs a standard benchmark using various options. The signature or standard node
- count is obtained using all defaults. `bench` is currently `bench 16 1 13 default depth mixed`.
-
* #### d
Display the current position, with ascii art and fen.
* #### eval
Return the evaluation of the current position.
+ * #### export_net [filename]
+ Exports the currently loaded network to a file.
+ If the currently loaded network is the embedded network and the filename
+ is not specified then the network is saved to the file matching the name
+ of the embedded network, as defined in evaluate.h.
+ If the currently loaded network is not the embedded network (some net set
+ through the UCI setoption) then the filename parameter is required and the
+ network is saved into that file.
+
+ * #### flip
+ Flips the side to move.
+
+
## A note on classical evaluation versus NNUE evaluation
Both approaches assign a value to a position that is used in alpha-beta (PVS) search
The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward.
It can be evaluated efficiently on CPUs, and exploits the fact that only parts
of the neural network need to be updated after a typical chess move.
-[The nodchip repository](https://github.com/nodchip/Stockfish) provides additional
-tools to train and develop the NNUE networks. On CPUs supporting modern vector instructions
+[The nodchip repository](https://github.com/nodchip/Stockfish) provided the first version of
+the needed tools to train and develop the NNUE networks. Today, more advanced training tools are available
+in [the nnue-pytorch repository](https://github.com/glinscott/nnue-pytorch/), while data generation tools
+are available in [a dedicated branch](https://github.com/official-stockfish/Stockfish/tree/tools).
+
+On CPUs supporting modern vector instructions
(avx2 and similar), the NNUE evaluation results in much stronger playing strength, even
if the nodes per second computed by the engine is somewhat lower (roughly 80% of nps
is typical).
that is guaranteed to be compatible with that binary.
2) to use the NNUE evaluation, the additional data file with neural network parameters
-needs to be available. Normally, this file is already embedded in the binary or it
+needs to be available. Normally, this file is already embedded in the binary or it
can be downloaded. The filename for the default (recommended) net can be found as the default
value of the `EvalFile` UCI option, with the format `nn-[SHA256 first 12 digits].nnue`
(for instance, `nn-c157e0a5755b.nnue`). This file can be downloaded from
If the engine is searching a position that is not in the tablebases (e.g.
a position with 8 pieces), it will access the tablebases during the search.
-If the engine reports a very large score (typically 153.xx), this means
+If the engine reports a very large score (typically 153.xx), this means
it has found a winning line into a tablebase position.
If the engine is given a position to search that is in the tablebases, it
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 full source code, or a pointer
+some way, you MUST always include the license, 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 the GPL.
+these changes must also be made available under the GPL v3.
For full details, read the copy of the GPL v3 found in the file named
-*Copying.txt*.
+[*Copying.txt*](https://github.com/official-stockfish/Stockfish/blob/master/Copying.txt).
projects / stockfish / blobdiff