#LeelaChessZero #CCC11 #smartypantschess Leela plays a nice Austrian attack and a timely g4!? To crack open black's defences. Hardware Backend; Newest (2018+) NVidia GPUs: GTX 16xx, RTX 20xx, RTX 30xx and so on: CUDA: Newer (2014-2018) NVidia GPUs: GTX 7xx, GTX 8xx, GTX 9xx, GTX 10xx.
There is no single 'best net' for Leela but there a few worth recommending for various purposes. The most important consideration in choosing a net is picking the right size for your hardware and time controls (TC). In general, if you have a weak GPU (or no GPU at all) and you want to only spend milliseconds per move, then you want a smaller net that evaluates positions more quickly, i.e. higher NPS (nodes per second). On the other hand, if you have an RTX card (or several) and you want to run an analysis on a single move for hours at a time, then the quality of the evaluation is more important than the speed and a larger (but slower) net is probably going to work best.
Size versus Recommended Purpose
- Add the engine into the chess GUI. Now it's time to add the Lc0 into the chess GUI of your choice. How exactly it's done, depends on the GUI, but usually there is 'Add Engine' somewhere in settings. You can give any name to the entry, and as select the file lc0.exe that you unpacked as a binary/command.
- Leelenstein is playing the best chess ever! Using great bias, I selected only LS wins. Check out the games below! Game 18: B12, Caro-Kann Event 'CCC10 Finals (10 3)'.
Leelenstein V3 Chess
- <10b: Recommended for sparring vs humans
- 10b: Recommended for running on CPU
- 20b: Recommended for running on non-RTX cards or TC on the order of seconds (with RTX)
- 24b: Recommended for TC > 1 minute per move with an RTX card
- >24b: Recommended for long analysis or when speed isn't a major factor
Network List
Leelenstein Chess Engine
For nets of the same size, the first net listed is likely the strongest.
| Size | Name | Source for Download | Notes |
|---|---|---|---|
| 5b x 48f | Good Gyal 5 | GitHub: dkappe Bad Gyal | Other sizes also here |
| 9b x 112f | ID11258-112x9-se | GitHub: dkappe Distilled Networks | Other sizes also here |
| 10b x 128f | Latest T59 | lczero.org run 2 networks 591226. | A previous test run |
| 10b x 128f | Little Demon 2 | data.lczero.org repository (LD2) | JH nets also here |
| 16b x 192f | J20-460 | GitHub: jhorthos Leela Training | Trained on T40 data |
| 20b x 256f | Leelenstein 14.2 | Patreon: jjosh | Early Access |
| 20b x 256f | SV-20b-t40-1541 | Sergio-V repository | Trained on T40 data |
| 20b x 256f | Leelenstein 14.0 | 14.0 Post | No account required |
| 20b x 256f | T40: #42850 | lczero.org run 1 networks | Last T40 net |
| 24b x 320f | Latest T60 | lczero.org run 1 networks | Current main run |
| 24b x 320f | J13B.2-136 | GitHub: jhorthos Leela Training | 'Terminator 2' Net |
| 30b x 384f | 384x30-t60-3010, 384x30-t60-3044 | Sergio-V repository | Trained on T60 data |
| 30b x 384f | SV-30b-t40-1705 | Sergio-V repository | Trained on T40 data |
Note: The Sergio-V nets are also available on data.lczero.org in some cases.
'This is all too complicated. Just tell me what net to use!'
If you don't care about squeezing out the very best performance for a particular situation and want a general-purpose net, pick a medium size 20b net, which should do reasonably well (if not optimal) under most common conditions.
Leelenstein Chess Engine Download For Android
As in the table above, the top-recommended 20b net is 256x20-t40-1541.pb.gz from Sergio Vieri's repository.
Leelenstein Chess Engine
Adobe cs4 serial number. If this page hasn't been updated recently, check the Discord channels for a recommendation. Be sure to specify your hardware and use case so the helpful regulars know what to recommend.
There is no single 'best net' for Leela but there a few worth recommending for various purposes.
There is no single 'best net' for Leela but there a few worth recommending for various purposes. The most important consideration in choosing a net is picking the right size for your hardware and time controls (TC). In general, if you have a weak GPU (or no GPU at all) and you want to only spend milliseconds per move, then you want a smaller net that evaluates positions more quickly, i.e. higher NPS (nodes per second). On the other hand, if you have an RTX card (or several) and you want to run an analysis on a single move for hours at a time, then the quality of the evaluation is more important than the speed and a larger (but slower) net is probably going to work best.
Size versus Recommended Purpose
- Add the engine into the chess GUI. Now it's time to add the Lc0 into the chess GUI of your choice. How exactly it's done, depends on the GUI, but usually there is 'Add Engine' somewhere in settings. You can give any name to the entry, and as select the file lc0.exe that you unpacked as a binary/command.
- Leelenstein is playing the best chess ever! Using great bias, I selected only LS wins. Check out the games below! Game 18: B12, Caro-Kann Event 'CCC10 Finals (10 3)'.
Leelenstein V3 Chess
- <10b: Recommended for sparring vs humans
- 10b: Recommended for running on CPU
- 20b: Recommended for running on non-RTX cards or TC on the order of seconds (with RTX)
- 24b: Recommended for TC > 1 minute per move with an RTX card
- >24b: Recommended for long analysis or when speed isn't a major factor
Network List
Leelenstein Chess Engine
For nets of the same size, the first net listed is likely the strongest.
| Size | Name | Source for Download | Notes |
|---|---|---|---|
| 5b x 48f | Good Gyal 5 | GitHub: dkappe Bad Gyal | Other sizes also here |
| 9b x 112f | ID11258-112x9-se | GitHub: dkappe Distilled Networks | Other sizes also here |
| 10b x 128f | Latest T59 | lczero.org run 2 networks 591226. | A previous test run |
| 10b x 128f | Little Demon 2 | data.lczero.org repository (LD2) | JH nets also here |
| 16b x 192f | J20-460 | GitHub: jhorthos Leela Training | Trained on T40 data |
| 20b x 256f | Leelenstein 14.2 | Patreon: jjosh | Early Access |
| 20b x 256f | SV-20b-t40-1541 | Sergio-V repository | Trained on T40 data |
| 20b x 256f | Leelenstein 14.0 | 14.0 Post | No account required |
| 20b x 256f | T40: #42850 | lczero.org run 1 networks | Last T40 net |
| 24b x 320f | Latest T60 | lczero.org run 1 networks | Current main run |
| 24b x 320f | J13B.2-136 | GitHub: jhorthos Leela Training | 'Terminator 2' Net |
| 30b x 384f | 384x30-t60-3010, 384x30-t60-3044 | Sergio-V repository | Trained on T60 data |
| 30b x 384f | SV-30b-t40-1705 | Sergio-V repository | Trained on T40 data |
Note: The Sergio-V nets are also available on data.lczero.org in some cases.
'This is all too complicated. Just tell me what net to use!'
If you don't care about squeezing out the very best performance for a particular situation and want a general-purpose net, pick a medium size 20b net, which should do reasonably well (if not optimal) under most common conditions.
Leelenstein Chess Engine Download For Android
As in the table above, the top-recommended 20b net is 256x20-t40-1541.pb.gz from Sergio Vieri's repository.
Leelenstein Chess Engine
Adobe cs4 serial number. If this page hasn't been updated recently, check the Discord channels for a recommendation. Be sure to specify your hardware and use case so the helpful regulars know what to recommend.
There is no single 'best net' for Leela but there a few worth recommending for various purposes.
The most important consideration in choosing a net is picking the right size for your hardware and time controls. In general, if you have a weak GPU or no GPU and want to only spend milliseconds per move, then you want a smaller net that evaluates positions more quickly, i.e. higher NPS (nodes per second). On the other hand, if you have an RTX card(s) and you want to run analysis from a position hours at a time, then the quality of the evaluation is more important than the speed, and a larger (but slower) net is probably going to work best. Matthew hussey videos.
Size versus Recommended Purpose
- 30b: Recommended for multi-GPU (RTX), long analysis, or when speed isn't a major factor
- 24b: Recommended for TC > 1 minute per move with an RTX card
- 20b: Recommended for running on non-RTX cards or TC on the order of seconds (with RTX)
- 10b: Recommended for running on CPU
- <10b: Recommended for sparring vs humans
Network Lists
In each section, the nets are listed (roughly) in descending order of strength. (Some may be too close to tell apart).
30 blocks x 384 filters:
| Name | Source for Download | Notes |
|---|---|---|
| Latest J94 net | GitHub: jhorthos Leela Training | Based on Sergio-V networks, trained on T60 data |
| Latest 30b SV net | Sergio-V repository | Trained on T60 data |
| SV-3972+jio-20k | data.lczero.org direct download | Submitted for TCEC 18 Superfinal |
| 384x30-t60-3010 | Sergio-V repository | Won CCC13 and TCEC 17 |
| 384x30-t40-1705 | Sergio-V repository | Trained on T40 data |
24 blocks x 320 filters:
| Name | Source for Download | Notes |
|---|---|---|
| Latest T60 | lczero.org run 1 networks | Current main run |
| J13B.2-136 | GitHub: jhorthos Leela Training | 'Terminator 2' Net |
20 blocks x 256 filters:
| Name | Source for Download | Notes |
|---|---|---|
| Leelenstein 15.0 | Patreon: jjosh | Early Access (Patrons only) |
| Leelenstein 14.3 | 14.3 Post | No account required, to be used with LC0 v0.24.1 |
| Leelenstein 14.0 | 14.0 Post | No account required |
| SV-20b-t40-1541 | Sergio-V repository | Trained on T40 data |
| 42850 | training.lczero.org direct download | Last T40 net |
10 blocks x 128 filters:
Leelenstein Chess Engines
| Name | Source for Download | Notes |
|---|---|---|
| Latest 10b SV net | Sergio-V repository | Trained on T60 data |
| 703810 | training.lczero.org direct download | Last T70 net (not to be confused with T72) |
| 591226 | training.lczero.org direct download | Last T59 net |
| Little Demon 2 | data.lczero.org repository (LD2) | JH nets also here |
Asorted sizes:
| Size | Name | Source for Download | Notes |
|---|---|---|---|
| 19b x 256f | T71.5-FR960-Armageddon-Chess | lczero.org run 3 networks | Trained from scratch on Fischer Random Armageddon Chess |
| 16b x 192f | J64-210 | GitHub: jhorthos Leela Training | Trained on T60 data |
| 16b x 192f | J20-460 | GitHub: jhorthos Leela Training | Trained on T40 data |
| 9b x 112f | ID11258-112x9-se | GitHub: dkappe Distilled Networks | Other sizes also here |
| 5b x 48f | Good Gyal 5 | GitHub: dkappe Bad Gyal | Other sizes also here |
| 2b x 16f | Tiny Gyal | GitHub: dkappe Bad Gyal | Other sizes also here |
Note: The Sergio-V nets are also available on data.lczero.org in some cases.
'This is all too complicated. Just tell me what net to use!'
If you don't care about squeezing out the very best performance for a particular situation and want a general-purpose net, pick a medium size 20b net, which should do reasonably well (if not optimally) under most common conditions.
The strongest 20b nets are the Leelenstein ones listed above but these aren't trained purely on Lc0 data. The best 20b net trained only on Lc0 data is 256x20-t40-1541.pb.gz from Sergio Vieri's repository. Deivamagal sujatha real name.
If this page hasn't been updated recently, check the Discord channels for a recommendation. Be sure to specify your hardware and use case so the helpful regulars know what to recommend.
