Setting view
Intensive filter
AI-written players, ranked by match results. This view combines each model's scores across the public games. Each attempt whose player program could not be generated counts as 0.
- Updated
- 2026-10-26
- Models
- 71
- Public games
- 8
Rankings
Models
Model leaderboard
One row per evaluated model; Best is the highest 0–100 game score across that model's evaluated games in this reasoning-setting view. Models appear once this reasoning setting has match history, or at 0 when every one of its generation attempts failed.
How to read
We ask each AI model to write a player program for every game. DuelLab runs those programs against each other. Higher scores mean stronger results against a fixed reference field of player programs.
Score is the 0–100 result across public games: expected points against the fixed reference field. Working-program strength averages only games where the model produced a working player program, leaving failed generation attempts out. Codegen shows the share that worked first try / worked after repair or resend / failed. Players counts the player programs behind a row, while Best is its highest single-game score. W / D / L shows rated wins, draws, and losses. More matches with existing programs do not add independent generation evidence. Where shown, the reasoning spread tells how much results vary across settings. Opponents played, hidden until you turn it on under Columns, shows how far the row's player programs are through the full round-robin of their games.
Partial 3/3 is an official Overall rank whose evidence is incomplete in another way, so compare it with care. Models with results for fewer than three reasoning settings get no Overall rank. Provisional rows do not receive an official rank. Capped draws reached the shared move cap and still count as draws. Filters can change the visible order, but the Official or Base column keeps the published rank. Cost / player is an estimate; select a value for its source and pricing details.
Columns
Choose the optional columns shown in this table.
Models
Not yet ranked (7)
These entries have scores so far but do not yet meet the rules for an official rank, so they are kept out of the leaderboard above.
- 5Some games cannot be scored A game's only generation attempts failed because of our test harness or the provider, not the model, and cannot currently be repeated. The score averages the other games.
- 1Every program failed None of the setting's generation attempts produced a working player program, so it scores 0.
- 1Too many programs failed Too few of its player programs compiled and ran to qualify for a rank.
Show all 7 entriesHide entries
| Model | Reasoning | Score so far | Why not ranked yet |
|---|---|---|---|
 Claude Haiku 5.5 | — | 74.9 | Some games cannot be scored |
 Muse Spark Open | — | 63.6 | Some games cannot be scored |
 Mercury 3 | — | 59.6 | Some games cannot be scored |
 MiMo-V2.5 | — | 35.9 | Some games cannot be scored |
 Nex N2.5 Pro | — | 20.6 | Some games cannot be scored |
 Solar Mini 4 | — | 13.8 | Too many programs failed |
 Granite 4.2 8B | — | 0.0 | Every program failed |
Scoring method
How this is scored
Each model is asked to create a program that can play every benchmark game.
The generated programs compete head-to-head, with both players receiving comparable opportunities.
Wins, draws, and losses produce a B1 (Bradley–Terry) rating for each program, which becomes a 0–100 score for each game: 100 × its expected points against the fixed reference field.
The main score is the mean across games. Every generation attempt counts: a game combines its working programs' scores with a 0 for each attempt whose player program could not be generated, and a reasoning setting where every attempt failed scores 0. A program rejected only for being too slow, or lost to a fault of the test machine, does not play and does not count. The share of working programs is shown on its own (Codegen).
Every row uses the reasoning setting selected for this view.
Detailed tables provide match records, match counts, and other context for careful comparison.