Stockfish Development Versions are build automatically if there are changes on the master branch in the git repository (https://github.com/official-stockfish/Stockfish). Use it at your own risk.
They are compiled with gcc 11.2/mingw 10 on Ubuntu 22.04.
You can leave a comment.

Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Gahtan Nahdi
Date: Mon Mar 11 10:08:40 2024 +0100
Timestamp: 1710148120

Simplify opponentWorsening condition

Passed non-reg STC:
https://tests.stockfishchess.org/tests/view/65ea18650ec64f0526c4033a
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 226624 W: 58601 L: 58589 D: 109434 Elo +0.02
Ptnml(0-2): 1030, 27193, 56819, 27275, 995

Passed non-reg LTC:
https://tests.stockfishchess.org/tests/view/65eb7a220ec64f0526c4161a
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 243882 W: 61462 L: 61469 D: 120951 Elo -0.01
Ptnml(0-2): 197, 27559, 66419, 27586, 180

closes https://github.com/official-stockfish/Stockfish/pull/5102

Bench: 1601012
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Muzhen Gaming
Date: Mon Mar 11 10:04:37 2024 +0100
Timestamp: 1710147877

VVLTC search tune

Result of 32k games of tuning at 60+0.6 8-thread. Link to the tuning
attempt:
https://tests.stockfishchess.org/tests/view/65def7b04b19edc854ebdec8

Passed VVLTC first SPRT:
https://tests.stockfishchess.org/tests/view/65e51b53416ecd92c162ab7f
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 37570 W: 9613 L: 9342 D: 18615 Elo +2.51
Ptnml(0-2): 2, 3454, 11601, 3727, 1

Passed VVLTC second SPRT:
https://tests.stockfishchess.org/tests/view/65e87d1c0ec64f0526c3eb39
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 123158 W: 31463 L: 31006 D: 60689 Elo +1.29
Ptnml(0-2): 5, 11589, 37935, 12044, 6

Note: The small net and psqt-only thresholds have been moved to
evaluate.h. The reasoning is that these values are used in both
`evaluate.cpp` and `evaluate_nnue.cpp`, and thus unifying their usage
avoids inconsistencies during testing, where one occurrence is changed
without the other (this happened during the search tune SPRT).

closes https://github.com/official-stockfish/Stockfish/pull/5101

Bench: 1741218
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Disservin
Date: Mon Mar 11 09:02:13 2024 +0100
Timestamp: 1710144133

Assorted cleanups

- fix naming convention for `workingDirectory`
- use type alias for `EvalFiles` everywhere
- move `ponderMode` into `LimitsType`
- move limits parsing into standalone static function

closes https://github.com/official-stockfish/Stockfish/pull/5098

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Robert Nurnberg @ elitebook
Date: Thu Mar 7 21:10:33 2024 +0100
Timestamp: 1709842233

Fix wrong constant usage in go mate

Fixes an oversight in https://github.com/official-stockfish/Stockfish/pull/5094

In theory, master could stop search when run with `go mate 247` and return a TB loss (not a mate score). Also fixes the spelling of opponenWorsening.

closes https://github.com/official-stockfish/Stockfish/pull/5096

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Muzhen Gaming
Date: Thu Mar 7 20:08:00 2024 +0100
Timestamp: 1709838480

VLTC time management tune

Result of 35k games of SPSA tuning at 180+1.8. Tuning attempt can be
found here:
https://tests.stockfishchess.org/tests/view/65e40599f2ef6c733362b03b

Passed VLTC 180+1.8:
https://tests.stockfishchess.org/tests/view/65e5a6f5416ecd92c162b5d4
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 31950 W: 8225 L: 7949 D: 15776 Elo +3.00
Ptnml(0-2): 3, 3195, 9309, 3459, 9

Passed VLTC 240+2.4:
https://tests.stockfishchess.org/tests/view/65e714de0ec64f0526c3d1f1
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 65108 W: 16558 L: 16202 D: 32348 Elo +1.90
Ptnml(0-2): 7, 6366, 19449, 6728, 4

closes https://github.com/official-stockfish/Stockfish/pull/5095

Bench: 1714391
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Shahin M. Shahin
Date: Thu Mar 7 19:58:33 2024 +0100
Timestamp: 1709837913

Fix `go mate x` in multithreading

Fixes two issues with master for go mate x:

- when running go mate x in losing positions, master always goes to the
maximal depth, arguably against what the UCI protocol demands

- when running go mate x in winning positions with multiple
threads, master may return non-mate scores from the search (this issue
is present in stockfish since at least sf16) The issues are fixed by
(a) also checking if score is mate -x and by (b) only letting
mainthread stop the search for go mate x commands, and by not looking
for a best thread but using mainthread as per the default. Related:
niklasf/python-chess#1070

More diagnostics can be found here peregrineshahin#6 (comment)

closes https://github.com/official-stockfish/Stockfish/pull/5094

No functional change

Co-Authored-By: Robert Nürnberg <28635489+>
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Michael Chaly
Date: Thu Mar 7 19:56:30 2024 +0100
Timestamp: 1709837790

Introduce double extensions for PV nodes

Our double/triple extensions were allowed only for non-pv nodes. This
patch allows them to be done for PV nodes, with some stricter
conditions.

Passed STC:
https://tests.stockfishchess.org/tests/view/65d657ec1d8e83c78bfddab8
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 339424 W: 88097 L: 87318 D: 164009 Elo +0.80
Ptnml(0-2): 1573, 39935, 85729, 41090, 1385

Passed LTC:
https://tests.stockfishchess.org/tests/view/65dd63824b19edc854ebc433
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 459564 W: 115812 L: 114614 D: 229138 Elo +0.91
Ptnml(0-2): 248, 51441, 125173, 52705, 215

closes https://github.com/official-stockfish/Stockfish/pull/5093

Bench: 1714391
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: rn5f107s2
Date: Thu Mar 7 19:55:51 2024 +0100
Timestamp: 1709837751

Reduce futility_margin if opponents last move was bad

This reduces the futiltiy_margin if our opponents last move was bad by
around ~1/3 when not improving and ~1/2.7 when improving, the idea being
to retroactively futility prune moves that were played, but turned out
to be bad. A bad move is being defined as their staticEval before their
move being lower as our staticEval now is. If the depth is 2 and we are
improving the opponent worsening flag is not set, in order to not risk
having a too low futility_margin, due to the fact that when these
conditions are met the futility_margin already drops quite low.

Passed STC:
https://tests.stockfishchess.org/tests/live_elo/65e3977bf2ef6c733362aae3
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 122432 W: 31884 L: 31436 D: 59112 Elo +1.27
Ptnml(0-2): 467, 14404, 31035, 14834, 476

Passed LTC:
https://tests.stockfishchess.org/tests/live_elo/65e47f40f2ef6c733362b6d2
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 421692 W: 106572 L: 105452 D: 209668 Elo +0.92
Ptnml(0-2): 216, 47217, 114865, 48327, 221

closes https://github.com/official-stockfish/Stockfish/pull/5092

Bench: 1565939
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Linmiao Xu
Date: Thu Mar 7 19:53:48 2024 +0100
Timestamp: 1709837628

Update default main net to nn-1ceb1ade0001.nnue

Created by retraining the previous main net `nn-b1a57edbea57.nnue` with:
- some of the same options as before:
- ranger21, more WDL skipping, 15% more loss when Q is too high
- removal of the huge 514G pre-interleaved binpack
- removal of SF-generated dfrc data (dfrc99-16tb7p-filt-v2.min.binpack)
- interleaving many binpacks at training time
- training with some bestmove capture positions where SEE < 0
- increased usage of torch.compile to speed up training by up to 40%

```yaml
experiment-name: 2560--S10-dfrc0-to-dec2023-skip-more-wdl-15p-more-loss-high-q-see-ge0-sk28
nnue-pytorch-branch: linrock/nnue-pytorch/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more
start-from-engine-test-net: True

early-fen-skipping: 28
training-dataset:
# similar, not the exact same as:
# https://github.com/official-stockfish/Stockfish/pull/4635
- /data/S5-5af/leela96.v2.min.binpack
- /data/S5-5af/test60-2021-11-12-novdec-12tb7p.v6-dd.min.binpack
- /data/S5-5af/test77-2021-12-dec-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test78-2022-01-to-05-jantomay-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test78-2022-06-to-09-juntosep-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test79-2022-04-apr-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test79-2022-05-may-16tb7p.v6-dd.min.binpack

- /data/S5-5af/test80-2022-06-jun-16tb7p.v6-dd.min.unmin.binpack
- /data/S5-5af/test80-2022-07-jul-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test80-2022-08-aug-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test80-2022-09-sep-16tb7p.v6-dd.min.unmin.binpack
- /data/S5-5af/test80-2022-10-oct-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test80-2022-11-nov-16tb7p.v6-dd.min.binpack

- /data/S5-5af/test80-2023-01-jan-16tb7p.v6-sk20.min.binpack
- /data/S5-5af/test80-2023-02-feb-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test80-2023-03-mar-2tb7p.min.unmin.binpack
- /data/S5-5af/test80-2023-04-apr-2tb7p.binpack
- /data/S5-5af/test80-2023-05-may-2tb7p.min.dd.binpack

# https://github.com/official-stockfish/Stockfish/pull/4782
- /data/S6-1ee1aba5ed/test80-2023-06-jun-2tb7p.binpack
- /data/S6-1ee1aba5ed/test80-2023-07-jul-2tb7p.min.binpack

# https://github.com/official-stockfish/Stockfish/pull/4972
- /data/S8-baff1edbea57/test80-2023-08-aug-2tb7p.v6.min.binpack
- /data/S8-baff1edbea57/test80-2023-09-sep-2tb7p.binpack
- /data/S8-baff1edbea57/test80-2023-10-oct-2tb7p.binpack

# https://github.com/official-stockfish/Stockfish/pull/5056
- /data/S9-b1a57edbea57/test80-2023-11-nov-2tb7p.binpack
- /data/S9-b1a57edbea57/test80-2023-12-dec-2tb7p.binpack

num-epochs: 800
lr: 4.375e-4
gamma: 0.995
start-lambda: 1.0
end-lambda: 0.7
```

This particular net was reached at epoch 759. Use of more torch.compile decorators
in nnue-pytorch model.py than in the previous main net training run sped up training
by up to 40% on Tesla gpus when using recent pytorch compiled with cuda 12:
https://github.com/linrock/nnue-tools/blob/7fb9831/Dockerfile

Skipping positions with bestmove captures where static exchange evaluation is >= 0
is based on the implementation from Sopel's NNUE training & experimentation log:
https://docs.google.com/document/d/1gTlrr02qSNKiXNZ_SuO4-RjK4MXBiFlLE6jvNqqMkAY
Experiment 293 - only skip captures with see>=0

Positions with bestmove captures where score == 0 are always skipped for
compatibility with minimized binpacks, since the original minimizer sets
scores to 0 for slight improvements in compression.

The trainer branch used was:
https://github.com/linrock/nnue-pytorch/tree/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more

Binpacks were renamed to be sorted chronologically by default when sorted by name.
The binpack data are otherwise the same as binpacks with similar names in the prior
naming convention.

Training data can be found at:
https://robotmoon.com/nnue-training-data/

Passed STC:
https://tests.stockfishchess.org/tests/view/65e3ddd1f2ef6c733362ae5c
LLR: 2.92 (-2.94,2.94) <0.00,2.00>
Total: 149792 W: 39153 L: 38661 D: 71978 Elo +1.14
Ptnml(0-2): 675, 17586, 37905, 18032, 698

Passed LTC:
https://tests.stockfishchess.org/tests/view/65e4d91c416ecd92c162a69b
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 64416 W: 16517 L: 16135 D: 31764 Elo +2.06
Ptnml(0-2): 38, 7218, 17313, 7602, 37

closes https://github.com/official-stockfish/Stockfish/pull/5090

Bench: 1373183
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: FauziAkram
Date: Thu Mar 7 19:53:48 2024 +0100
Timestamp: 1709837628

Update elo estimates

Tests used to change the elo worth of some functions:

https://tests.stockfishchess.org/tests/view/65c3f69dc865510db0283eef
https://tests.stockfishchess.org/tests/view/65c3f935c865510db0283f2a
https://tests.stockfishchess.org/tests/view/65d1489f1d8e83c78bfd7dbf
https://tests.stockfishchess.org/tests/view/65ce9d361d8e83c78bfd4951
https://tests.stockfishchess.org/tests/view/65cfcd901d8e83c78bfd6184

closes https://github.com/official-stockfish/Stockfish/pull/5089

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: FauziAkram
Date: Thu Mar 7 19:49:01 2024 +0100
Timestamp: 1709837341

Simplify Time Management

Instead of having a formula for using extra time with larger increments.
Simply set it to 1 when the increment is lower than 0.5s and to 1.1 when
the increment is higher.

The values can later on be further improved.

Passed STC:
https://tests.stockfishchess.org/tests/view/65d25d3c1d8e83c78bfd9293
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 27488 W: 7077 L: 6848 D: 13563 Elo +2.89
Ptnml(0-2): 96, 3041, 7267, 3218, 122

Passed LTC:
https://tests.stockfishchess.org/tests/view/65d2a72c1d8e83c78bfd97fa
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 137568 W: 34612 L: 34512 D: 68444 Elo +0.25
Ptnml(0-2): 60, 14672, 39221, 14770, 61

Passed VLTC:
https://tests.stockfishchess.org/tests/view/65d7d7d39b2da0226a5a205b
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 139650 W: 35229 L: 35134 D: 69287 Elo +0.24
Ptnml(0-2): 33, 14227, 41218, 14306, 41

Passed also the TCEC TC style suggested by vondele:
https://tests.stockfishchess.org/tests/view/65e4ca73416ecd92c162a57d
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 134150 W: 34278 L: 34163 D: 65709 Elo +0.30
Ptnml(0-2): 561, 15727, 34444, 15722, 621

closes https://github.com/official-stockfish/Stockfish/pull/5076

Bench: 1553115
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Gahtan Nahdi
Date: Sun Mar 3 15:45:13 2024 +0100
Timestamp: 1709477113

Simplify extension when ttMove is assumed to fail high over current beta

Simplify extension value to -3 when ttMove is assumed to fail high over current beta.

Passed non-reg STC:
https://tests.stockfishchess.org/tests/view/65d66ed81d8e83c78bfddcba
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 235136 W: 60711 L: 60708 D: 113717 Elo +0.00
Ptnml(0-2): 969, 27904, 59874, 27797, 1024

Passed non-reg LTC:
https://tests.stockfishchess.org/tests/view/65da2994944f2a78d4733107
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 662850 W: 166161 L: 166602 D: 330087 Elo -0.23
Ptnml(0-2): 394, 74895, 181274, 74482, 380

closes https://github.com/official-stockfish/Stockfish/pull/5088

Bench: 1553115
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Gahtan Nahdi
Date: Sun Mar 3 15:42:17 2024 +0100
Timestamp: 1709476937

Simplify IIR

Simplified depth reduction for PV nodes without a ttMove to 3.

Passed STC non-reg:
https://tests.stockfishchess.org/tests/view/65d1a90a1d8e83c78bfd855a
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 363168 W: 93648 L: 93791 D: 175729 Elo -0.14
Ptnml(0-2): 1557, 43692, 91221, 43565, 1549

Passed LTC non-reg:
https://tests.stockfishchess.org/tests/view/65d5612d1d8e83c78bfdc8e2
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 58818 W: 14946 L: 14761 D: 29111 Elo +1.09
Ptnml(0-2): 36, 6595, 15962, 6780, 36

closes https://github.com/official-stockfish/Stockfish/pull/5062

Bench: 1505827
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: mstembera
Date: Sun Mar 3 15:29:58 2024 +0100
Timestamp: 1709476198

Only evaluate the PSQT part of the small net for large evals.

Thanks to Viren6 for suggesting to set complexity to 0.

STC https://tests.stockfishchess.org/tests/view/65d7d6709b2da0226a5a203f
LLR: 2.92 (-2.94,2.94) <0.00,2.00>
Total: 328384 W: 85316 L: 84554 D: 158514 Elo +0.81
Ptnml(0-2): 1414, 39076, 82486, 39766, 1450

LTC https://tests.stockfishchess.org/tests/view/65dce6d290f639b028a54d2e
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 165162 W: 41918 L: 41330 D: 81914 Elo +1.24
Ptnml(0-2): 102, 18332, 45124, 18922, 101

closes https://github.com/official-stockfish/Stockfish/pull/5083

bench: 1504003
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Disservin
Date: Sun Mar 3 15:21:57 2024 +0100
Timestamp: 1709475717

Document TT code more

Slight refactor of the TT code with the goal to make it easier to understand / tweak.

Passed Non-Regression STC:
https://tests.stockfishchess.org/tests/view/65d51e401d8e83c78bfdc427
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 56416 W: 14750 L: 14550 D: 27116 Elo +1.23
Ptnml(0-2): 227, 6386, 14796, 6558, 241

closes https://github.com/official-stockfish/Stockfish/pull/5061

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Gahtan Nahdi
Date: Sun Mar 3 15:18:13 2024 +0100
Timestamp: 1709475493

Join conditions for move sorting heuristics

closes https://github.com/official-stockfish/Stockfish/pull/5078

No functional change.
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Disservin
Date: Sun Mar 3 15:09:46 2024 +0100
Timestamp: 1709474986

Update Actions to Node20

ensure our CI continues to run after Node16 is obsolote on github.

closes https://github.com/official-stockfish/Stockfish/pull/5074

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Disservin
Date: Sun Mar 3 15:07:32 2024 +0100
Timestamp: 1709474852

Make binaries executable again in CI

closes https://github.com/official-stockfish/Stockfish/pull/5072

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Disservin
Date: Sun Mar 3 15:01:29 2024 +0100
Timestamp: 1709474489

Restore development

closes https://github.com/official-stockfish/Stockfish/pull/5073

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Disservin
Date: Sat Feb 24 18:15:04 2024 +0100
Timestamp: 1708794904

Stockfish 16.1

Official release version of Stockfish 16.1

Bench: 1303971

---

Stockfish 16.1

Today, we have the pleasure to announce Stockfish 16.1. As always, you can
freely download it at https://stockfishchess.org/download and use it in the GUI
of your choice[1].

Don't forget to join our Discord server[2] to get in touch with the community of
developers and users of the project!

*Quality of chess play*

In our testing against its predecessor, Stockfish 16.1 shows a notable
improvement in performance, with an Elo gain of up to 27 points and winning over
2 times more game pairs[3] than it loses.

*Update highlights*

*Improved evaluation*

- Updated neural network architecture: The neural network architecture has
undergone two updates and is currently in its 8th version[4].
- Removal of handcrafted evaluation (HCE): This release marks the removal of the
traditional handcrafted evaluation and the transition to a fully neural
network-based approach[5].
- Dual NNUE: For the first time, Stockfish includes a secondary neural
network[6], used to quickly evaluate positions that are easily decided.

*UCI Options removed*

`Use NNUE` and `UCI_AnalyseMode`[7] have been removed as they no longer had any
effect. `SlowMover`[8] has also been removed in favor of `Move Overhead`.

*More binaries*

We now offer 13 new binaries. These new binaries include `avx512`, `vnni256`,
`vnni512`, `m1-apple-silicon`, and `armv8-dotprod`, which take advantage of
specific CPU instructions for improved performance.
For most users, using `sse41-popcnt` (formerly `modern`), `avx2`, or `bmi2`
should be enough, but if your CPU supports these new instructions, feel free to
try them!

*Development changes*

- Updated testing book: This new book[9], now derived exclusively from the open
Lichess database[10], is 10 times larger than its predecessor, and has been
used to test potential improvements to Stockfish over the past few months.
- Consolidation of repositories: Aiming to simplify access to our resources, we
have moved most Stockfish-related repositories into the official Stockfish
organization[11] on GitHub.
- Growing maintainer team: We welcome Disservin[12] to the team of maintainers
of the project! This extra pair of hands will ensure the lasting success of
Stockfish.

*Thank you*

The Stockfish project builds on a thriving community of enthusiasts (thanks
everybody!) who contribute their expertise, time, and resources to build a free
and open-source chess engine that is robust, widely available, and very strong.

We would like to express our gratitude for the 10k stars[13] that light up our
GitHub project! Thank you for your support and encouragement – your recognition
means a lot to us.

We invite our chess fans to join the Fishtest testing framework[14], and
programmers to contribute to the project either directly to Stockfish[15] (C++),
to Fishtest[16] (HTML, CSS, JavaScript, and Python), to our trainer
nnue-pytorch[17] (C++ and Python), or to our website[18] (HTML, CSS/SCSS, and
JavaScript).

The Stockfish team

[1] https://github.com/official-stockfish/Stockfish/wiki/Download-and-usage#download-a-chess-gui
[2] https://discord.gg/GWDRS3kU6R
[3] https://tests.stockfishchess.org/tests/view/65d666051d8e83c78bfddbd8
[4] https://github.com/official-stockfish/nnue-pytorch/blob/master/docs/nnue.md#sfnnv8-architecture
[5] https://github.com/official-stockfish/Stockfish/commit/af110e0
[6] https://github.com/official-stockfish/Stockfish/commit/584d9ef
[7] https://github.com/official-stockfish/Stockfish/commit/c53d2ec
[8] https://github.com/official-stockfish/Stockfish/commit/536d692
[9] https://github.com/official-stockfish/books/commit/426eca4
[10] https://database.lichess.org/
[11] https://github.com/official-stockfish/
[12] https://github.com/Disservin
[13] https://github.com/official-stockfish/Stockfish/stargazers
[14] https://github.com/official-stockfish/fishtest/wiki/Running-the-worker
[15] https://github.com/official-stockfish/Stockfish
[16] https://github.com/official-stockfish/fishtest
[17] https://github.com/official-stockfish/nnue-pytorch
[18] https://github.com/official-stockfish/stockfish-web
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Robert Nurnberg @ elitebook
Date: Sat Feb 24 17:59:41 2024 +0100
Timestamp: 1708793981

Update the WDL model

Based on 130M positions from 2.1M games.

```
Look recursively in directory pgns for games from SPRT tests using books
matching "UHO_4060_v..epd|UHO_Lichess_4852_v1.epd" for SF revisions
between 8e75548f2a10969c1c9211056999efbcebe63f9a (from 2024-02-17
17:11:46 +0100) and HEAD (from 2024-02-17 17:13:07 +0100). Based on
127920843 positions from 2109240 games, NormalizeToPawnValue should
change from 345 to 356.
```

The patch only affects the UCI-reported cp and wdl values.

closes https://github.com/official-stockfish/Stockfish/pull/5070

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Disservin
Date: Sat Feb 24 17:58:44 2024 +0100
Timestamp: 1708793924

Update Top CPU Contributors

closes https://github.com/official-stockfish/Stockfish/pull/5069

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Disservin
Date: Sat Feb 24 17:57:49 2024 +0100
Timestamp: 1708793869

Expose EvalFileSmall option for small net

Since https://github.com/official-stockfish/fishtest/pull/1870 has been merged
it's time for this update.

5k Fixed Games showed no problems.
https://tests.stockfishchess.org/tests/view/65d9cc274c0e22b904f574d7

closes https://github.com/official-stockfish/Stockfish/pull/5068

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: cj5716
Date: Sat Feb 17 17:13:07 2024 +0100
Timestamp: 1708186387

Simplify PV node reduction

Reduce less on PV nodes even with an upperbound TT entry.

Passed STC:
https://tests.stockfishchess.org/tests/view/65cb3a861d8e83c78bfd0497
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 118752 W: 30441 L: 30307 D: 58004 Elo +0.39
Ptnml(0-2): 476, 14179, 29921, 14335, 465

Passed LTC:
https://tests.stockfishchess.org/tests/view/65cd3b951d8e83c78bfd2b0d
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 155058 W: 38549 L: 38464 D: 78045 Elo +0.19
Ptnml(0-2): 85, 17521, 42219, 17632, 72

closes https://github.com/official-stockfish/Stockfish/pull/5057

Bench: 1303971
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Linmiao Xu
Date: Sat Feb 17 17:11:46 2024 +0100
Timestamp: 1708186306

Update default main net to nn-b1a57edbea57.nnue

Created by retraining the previous main net `nn-baff1edbea57.nnue` with:
- some of the same options as before: ranger21, more WDL skipping
- the addition of T80 nov+dec 2023 data
- increasing loss by 15% when prediction is too high, up from 10%
- use of torch.compile to speed up training by over 25%

```yaml
experiment-name: 2560--S9-514G-T80-augtodec2023-more-wdl-skip-15p-more-loss-high-q-sk28

training-dataset:
# https://github.com/official-stockfish/Stockfish/pull/4782
- /data/S6-514G-1ee1aba5ed.binpack
- /data/test80-aug2023-2tb7p.v6.min.binpack
- /data/test80-sep2023-2tb7p.binpack
- /data/test80-oct2023-2tb7p.binpack
- /data/test80-nov2023-2tb7p.binpack
- /data/test80-dec2023-2tb7p.binpack
early-fen-skipping: 28

start-from-engine-test-net: True
nnue-pytorch-branch: linrock/nnue-pytorch/r21-more-wdl-skip-15p-more-loss-high-q-torch-compile

num-epochs: 1000
lr: 4.375e-4
gamma: 0.995
start-lambda: 1.0
end-lambda: 0.7
```

Epoch 819 trained with the above config led to this PR. Use of torch.compile
decorators in nnue-pytorch model.py was found to speed up training by at least
25% on Ampere gpus when using recent pytorch compiled with cuda 12:
https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch

See recent main net PRs for more info on
- ranger21 and more WDL skipping: https://github.com/official-stockfish/Stockfish/pull/4942
- increasing loss when Q is too high: https://github.com/official-stockfish/Stockfish/pull/4972

Training data can be found at:
https://robotmoon.com/nnue-training-data/

Passed STC:
https://tests.stockfishchess.org/tests/view/65cd76151d8e83c78bfd2f52
LLR: 2.98 (-2.94,2.94) <0.00,2.00>
Total: 78336 W: 20504 L: 20115 D: 37717 Elo +1.73
Ptnml(0-2): 317, 9225, 19721, 9562, 343

Passed LTC:
https://tests.stockfishchess.org/tests/view/65ce5be61d8e83c78bfd43e9
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 41016 W: 10492 L: 10159 D: 20365 Elo +2.82
Ptnml(0-2): 22, 4533, 11071, 4854, 28

closes https://github.com/official-stockfish/Stockfish/pull/5056

Bench: 1351997
see source

< prev page next page >