producer string | tool string | url string | method_url string | benchmark_url string | engine string | measured timestamp[s] | metric string | tiles_tracked list | spawns string | notes string | fixed_depth_runs list | adaptive_run dict | headline dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
LK Forge | 2048 AI Solver | https://lkforge.com/games/2048/ | https://lkforge.com/games/2048/blog-how-the-ai-solver-works.html | https://lkforge.com/blog/2048-expectimax-depth-benchmark/ | expectimax search with a corner-snake heuristic, probability-threshold pruning and a transposition table (pruning/table approach follows nneonneo's canonical 2048-ai); the exact shipped engine (public/games/2048/solver-core.js), self-played headlessly | 2026-09-23T00:00:00 | self-play reach-rate per tile, mean and median score, and mean milliseconds per move, by fixed search depth | [
1024,
2048,
4096,
8192
] | standard 90% '2' / 10% '4' tile spawns | reach_*_pct is the share of games that reached that tile at least once. Depths 5 and 6 use 100 and 30 games (vs 300 for depths 1-4 and adaptive) because each move is far slower, so their percentages carry wider error bars. Tile spawns use a seeded PRNG; the search samples empty cells with the same randomness the shippe... | [
{
"depth": 1,
"games": 300,
"reach_1024_pct": 3,
"reach_2048_pct": 0,
"reach_4096_pct": 0,
"reach_8192_pct": 0,
"mean_score": 4366,
"median_score": 3636,
"ms_per_move": 0.002
},
{
"depth": 2,
"games": 300,
"reach_1024_pct": 4,
"reach_2048_pct": 0,
"reach_4... | {
"description": "the shipped default: search depth 3 when the board is empty, rising to depth 5 when it is nearly full",
"games": 300,
"reach_1024_pct": 99,
"reach_2048_pct": 94,
"reach_4096_pct": 70.3,
"reach_8192_pct": 9,
"mean_score": 62529,
"median_score": 60644,
"ms_per_move": 1.844
} | {
"reach_2048_depth_1_or_2_pct": 0,
"reach_2048_depth_3_pct": 66.3,
"reach_2048_depth_5_pct": 97,
"adaptive_reach_2048_pct": 94,
"adaptive_reach_8192_pct": 9,
"cost_multiplier_depth_3_to_6": 83,
"summary": "Below a 3-ply lookahead the solver never reaches 2048. Depth 3 is the threshold (66%); quality clim... |
2048 Solver Benchmark — Expectimax Depth Sweep
How well the LK Forge 2048 Solver plays as a function of search depth. The shipped engine is an expectimax search with a corner-snake heuristic, plus probability-threshold pruning and a transposition table (the pruning/table approach follows nneonneo's canonical 2048-ai). Self-played headlessly at fixed depths 1–6 plus the shipped adaptive setting.
- How the solver works: https://lkforge.com/games/2048/blog-how-the-ai-solver-works.html
- Full write-up: https://lkforge.com/blog/2048-expectimax-depth-benchmark/
- Try it: https://lkforge.com/games/2048/
- Producer: LK Forge — client-side AI games, solvers, and tools.
Headline numbers
- Below a 3-ply lookahead the solver never reaches 2048 — 0% of games at depth 1 and depth 2.
- Depth 3 is the threshold: reach-2048 jumps to 66%, and the mean score jumps six-fold (from ~4,400 to ~29,600) for that one extra ply.
- Quality climbs to 97% reach at depth 5, but a depth-6 move costs about 83× more compute than depth 3 for a shrinking gain.
- The shipped adaptive engine reaches 2048 in 94% of 300 games (depth 3 on an empty board, up to depth 5 when it is nearly full), pushes to 4096 in 70%, and breaks 8192 in 9%, at 1.8 ms/move. A separate 250-game run of the same engine measured 92.8% reach-2048 — corroborating within sampling error.
Files
data/2048-benchmark.json— per-depth reach-rates (1024/2048/4096/8192), mean/median score, and mean ms/move for fixed depths 1–6, plus the adaptive run and a headline summary.
Method
- Engine: the exact shipped engine (
public/games/2048/solver-core.js), self-played headlessly — the numbers describe the search the game actually runs. - Reach-rate = share of games that reached that tile at least once.
- Spawns: standard 90% "2" / 10% "4" tile spawns.
- Samples: depths 1–4 and adaptive are 300 games each; depth 5 is 100 games, depth 6 is 30 games (each move there is far slower), so those percentages carry wider error bars.
- Tile spawns use a seeded PRNG so the run is re-runnable; the search samples empty cells with the same randomness the shipped engine uses, so reach-rate is a stable distribution, not a single fixed value.
- Timing is mean milliseconds per move on one laptop. Measured 23 September 2026 (reworked engine).
Reproduce
node scripts/benchmark-2048-depth.mjs
# or: GAMES=300,300,300,300,100,30 DEPTHS=1,2,3,4,5,6 node scripts/benchmark-2048-depth.mjs
Citation
LK Forge (2026). 2048 Solver Benchmark — Expectimax Depth Sweep. https://lkforge.com/blog/2048-expectimax-depth-benchmark/
Everything runs client-side, no login, no tracking.
- Downloads last month
- -