Edit on wiki

Lc0 options

Lc0 options

Flag UCI option Description
–help, -h Show help and exit.
–weights, -w WeightsFile Path from which to load network weights.Setting it to <autodiscover> makes it search in ./ and ./weights/ subdirectories for the latest (by file date) file which looks like weights.Default value: <autodiscover>
–backend, -b Backend Neural network computational backend to use.Default value: cudnn Allowed values: cudnn, cudnn-fp16, opencl, blas, check, random, roundrobin, multiplexing, demux
–backend-opts, -o BackendOptions Parameters of neural network backend. Exact parameters differ per backend.
–threads, -t Threads Number of (CPU) worker threads to use.Default value: 2 Minimum value: 1 Maximum value: 128
–nncache NNCacheSize Number of positions to store in a memory cache. A large cache can speed up searching, but takes memory.Default value: 200000 Minimum value: 0 Maximum value: 999999999

Search options

Flag UCI option Description
–minibatch-size MinibatchSize How many positions the engine tries to batch together for parallel NN computation. Larger batches may reduce strength a bit, especially with a small number of playouts.Default value: 256 Minimum value: 1 Maximum value: 1024
–max-prefetch MaxPrefetch When the engine cannot gather a large enough batch for immediate use, try to prefetch up to X positions which are likely to be useful soon, and put them into cache.Default value: 32 Minimum value: 0 Maximum value: 1024
–cpuct CPuct cpuct_init constant from “UCT search” algorithm. Higher values promote more exploration/wider search, lower values promote more confidence/deeper search.Default value: 3.00 Minimum value: 0.00 Maximum value: 100.00
–cpuct-base CPuctBase cpuct_base constant from “UCT search” algorithm. Lower value means higher growth of Cpuct as number of node visits grows.Default value: 19652.00 Minimum value: 1.00 Maximum value: 1000000000.00
–cpuct-factor CPuctFactor Multiplier for the cpuct growth formula.Default value: 2.00 Minimum value: 0.00 Maximum value: 1000.00
–temperature Temperature Tau value from softmax formula for the first move. If equal to 0, the engine picks the best move to make. Larger values increase randomness while making the move.Default value: 0.00 Minimum value: 0.00 Maximum value: 100.00
–tempdecay-moves TempDecayMoves Reduce temperature for every move from the game start to this number of moves, decreasing linearly from initial temperature to 0. A value of 0 disables tempdecay.Default value: 0 Minimum value: 0 Maximum value: 100
–temp-cutoff-move TempCutoffMove Move number, starting from which endgame temperature is used rather than initial temperature. Setting it to 0 disables cutoff.Default value: 0 Minimum value: 0 Maximum value: 1000
–temp-endgame TempEndgame Temperature used during endgame (starting from cutoff move). Endgame temperature doesn’t decay.Default value: 0.00 Minimum value: 0.00 Maximum value: 100.00
–temp-value-cutoff TempValueCutoff When move is selected using temperature, bad moves (with win probability less than X than the best move) are not considered at all.Default value: 100.00 Minimum value: 0.00 Maximum value: 100.00
–temp-visit-offset TempVisitOffset Reduces visits by this value when picking a move with a temperature. When the offset is less than number of visits for a particular move, that move is not picked at all.Default value: 0.00 Minimum value: -1.00 Maximum value: 1000.00
–noise, -n DirichletNoise Add Dirichlet noise to root node prior probabilities. This allows the engine to discover new ideas during training by exploring moves which are known to be bad. Not normally used during play.Default value: false
–verbose-move-stats VerboseMoveStats Display Q, V, N, U and P values of every move candidate after each move.Default value: false
–smart-pruning-factor SmartPruningFactor Do not spend time on the moves which cannot become bestmove given the remaining time to search. When no other move can overtake the current best, the search stops, saving the time. Values greater than 1 stop less promising moves from being considered even earlier. Values less than 1 causes hopeless moves to still have some attention. When set to 0, smart pruning is deactivated.Default value: 1.33 Minimum value: 0.00 Maximum value: 10.00
–fpu-strategy FpuStrategy How is an eval of unvisited node determined. “reduction” subtracts --fpu-reduction value from the parent eval. “absolute” sets eval of unvisited nodes to the value specified in --fpu-value.Default value: reduction Allowed values: reduction, absolute
–fpu-reduction FpuReduction “First Play Urgency” reduction (used when FPU strategy is “reduction”). Normally when a move has no visits, it’s eval is assumed to be equal to parent’s eval. With non-zero FPU reduction, eval of unvisited move is decreased by that value, discouraging visits of unvisited moves, and saving those visits for (hopefully) more promising moves.Default value: 1.20 Minimum value: -100.00 Maximum value: 100.00
–fpu-value FpuValue “First Play Urgency” value. When FPU strategy is “absolute”, value of unvisited node is assumed to be equal to this value, and does not depend on parent eval.Default value: -1.00 Minimum value: -1.00 Maximum value: 1.00
–cache-history-length CacheHistoryLength Length of history, in half-moves, to include into the cache key. When this value is less than history that NN uses to eval a position, it’s possble that the search will use eval of the same position with different history taken from cache.Default value: 0 Minimum value: 0 Maximum value: 7
–policy-softmax-temp PolicyTemperature Policy softmax temperature. Higher values make priors of move candidates closer to each other, widening the search.Default value: 2.20 Minimum value: 0.10 Maximum value: 10.00
–max-collision-events MaxCollisionEvents Allowed node collision events, per batch.Default value: 32 Minimum value: 1 Maximum value: 1024
–max-collision-visits MaxCollisionVisits Total allowed node collision visits, per batch.Default value: 9999 Minimum value: 1 Maximum value: 1000000
–out-of-order-eval OutOfOrderEval During the gathering of a batch for NN to eval, if position happens to be in the cache or is terminal, evaluate it right away without sending the batch to the NN. When off, this may only happen with the very first node of a batch; when on, this can happen with any node.Default value: true
–syzygy-fast-play SyzygyFastPlay With DTZ tablebase files, only allow the network pick from winning moves that have shortest DTZ to play faster (but not necessarily optimally).Default value: true
–multipv MultiPV Number of game play lines (principal variations) to show in UCI info output.Default value: 1 Minimum value: 1 Maximum value: 500
–score-type ScoreType What to display as score. Either centipawns (the UCI default), win percentage or Q (the actual internal score) multiplied by 100.Default value: centipawn Allowed values: centipawn, win_percentage, Q
–history-fill HistoryFill Neural network uses 7 previous board positions in addition to the current one. During the first moves of the game such historical positions don’t exist, but they can be synthesized. This parameter defines when to synthesize them (always, never, or only at non-standard fen position).Default value: fen_only Allowed values: no, fen_only, always
–kldgain-average-interval KLDGainAverageInterval Used to decide how frequently to evaluate the average KLDGainPerNode to check the MinimumKLDGainPerNode, if specified.Default value: 100 Minimum value: 1 Maximum value: 10000000
–minimum-kldgain-per-node MinimumKLDGainPerNode If greater than 0 search will abort unless the last KLDGainAverageInterval nodes have an average gain per node of at least this much.Default value: 0.00 Minimum value: 0.00 Maximum value: 1.00

Engine options

Flag UCI option Description
–slowmover Slowmover Budgeted time for a move is multiplied by this value, causing the engine to spend more time (if value is greater than 1) or less time (if the value is less than 1).Default value: 1.00 Minimum value: 0.00 Maximum value: 100.00
–move-overhead MoveOverheadMs Amount of time, in milliseconds, that the engine subtracts from it’s total available time (to compensate for slow connection, interprocess communication, etc).Default value: 200 Minimum value: 0 Maximum value: 100000000
–time-midpoint-move TimeMidpointMove The move where the time budgeting algorithm guesses half of all games to be completed by. Half of the time allocated for the first move is allocated at approximately this move.Default value: 51.50 Minimum value: 1.00 Maximum value: 100.00
–time-steepness TimeSteepness “Steepness” of the function the time budgeting algorithm uses to consider when games are completed. Lower values leave more time for the endgame, higher values use more time for each move before the midpoint.Default value: 7.00 Minimum value: 1.00 Maximum value: 100.00
–syzygy-paths, -s SyzygyPath List of Syzygy tablebase directories, list entries separated by system separator (";” for Windows, “:” for Linux).
–ponder Ponder This option is ignored. Here to please chess GUIs.Default value: true
–immediate-time-use ImmediateTimeUse Fraction of time saved by smart pruning, which is added to the budget to the next move rather than to the entire game. When 1, all saved time is added to the next move’s budget; when 0, saved time is distributed among all future moves.Default value: 1.00 Minimum value: 0.00 Maximum value: 1.00
–ramlimit-mb RamLimitMb Maximum memory usage for the engine, in megabytes. The estimation is very rough, and can be off by a lot. For example, multiple visits to a terminal node counted several times, and the estimation assumes that all positions have 30 possible moves. When set to 0, no RAM limit is enforced.Default value: 0 Minimum value: 0 Maximum value: 100000000
–config, -c ConfigFile Path to a configuration file. The format of the file is one command line parameter per line, e.g.:--weights=/path/to/weightsDefault value: lc0.config
–logfile, -l LogFile Write log to that file. Special value <stderr> to output the log to the console.

Selfplay options

Flag UCI option Description
–share-trees ShareTrees When on, game tree is shared for two players; when off, each side has a separate tree.Default value: true
–games Games Number of games to play.Default value: -1 Minimum value: -1 Maximum value: 999999
–parallelism Parallelism Number of games to play in parallel.Default value: 8 Minimum value: 1 Maximum value: 256
–playouts Playouts Number of playouts per move to search.Default value: -1 Minimum value: -1 Maximum value: 999999999
–visits Visits Number of visits per move to search.Default value: -1 Minimum value: -1 Maximum value: 999999999
–movetime MoveTime Time per move, in milliseconds.Default value: -1 Minimum value: -1 Maximum value: 999999999
–training Training Enables writing training data. The training data is stored into a temporary subdirectory that the engine creates.Default value: false
–verbose-thinking VerboseThinking Show verbose thinking messages.Default value: false
–resign-playthrough ResignPlaythrough The percentage of games which ignore resign.Default value: 0.00 Minimum value: 0.00 Maximum value: 100.00
–reuse-tree ReuseTree Reuse the search tree between moves.Default value: false
–resign-wdlstyle ResignWDLStyle If set, resign percentage applies to any output state being above 100% minus the percentage instead of winrate being below.Default value: false
–resign-percentage ResignPercentage Resign when win percentage drops below specified value.Default value: 0.00 Minimum value: 0.00 Maximum value: 100.00
–resign-earliest-move ResignEarliestMove Earliest move that resign is allowed.Default value: 0 Minimum value: 0 Maximum value: 1000
–interactive Run in interactive mode with UCI-like interface.Default value: false

Benchmark options

Flag UCI option Description
–nodes Number of nodes to run as a benchmark.Default value: -1 Minimum value: -1 Maximum value: 999999999
–movetime Benchmark time allocation, in milliseconds.Default value: 10000 Minimum value: -1 Maximum value: 999999999
–fen Benchmark initial position FEN.Default value: rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1
Last Updated: 2019-12-08