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Reasoning

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Normalized score across public games (0–100)

Showing top 6 of 217 benchmarked reasoning variants (updates when chart loads)

Scale: relative 0-100

  1. 91.8
    Claude Opus 5.5
  2. 90.7
    GPT-6 Astra
  3. 87.3
    GPT-6.1 Sol
  4. 86.2
    Claude Fable 5.1
  5. 83.5
    Claude Sonnet 5.5
  6. 83.4
    Claude Opus 5.5

Detailed leaderboard

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 the current models.

Score is the normalized 0–100 result across public games. Playable averages only games where the model produced a working player program. 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, and the rating-evidence and match-evidence index are rough heuristics of match volume, not confidence levels; a zero rating-evidence index is a clipped endpoint, not certainty. 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 reasoning variants do not receive an official rank. Under-covered means evidence is sparse. Capped draws reached the shared move limit 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.

Reasoning Variants leaderboard for DuelLab GameBench 2
Rank Model Reasoning Score Playable W / D / L Opponents played Best Cost / player Codegen By game
1Claude Opus 5.5XHigh91.891.83444 / 75 / 12799%100 × 2$1.9975%25%0%n 8
2GPT-6 AstraXHigh90.790.74490 / 128 / 21299%100$1.30100%0%0%n 8
3GPT-6.1 SolXHigh87.387.33334 / 101 / 21199%100 × 2$0.27100%0%0%n 8
4Claude Fable 5.1XHigh86.286.26118 / 165 / 35699%95.8$5.0282%18%0%n 11
5Claude Sonnet 5.5XHigh83.583.53196 / 283 / 16399%100$0.5588%12%0%n 8
6Claude Opus 5.5Medium83.483.43764 / 114 / 21698%95.7$0.3389%11%0%n 9
7Pareto 26.10 PreviewProvider78.278.23000 / 127 / 29393%92.7$0.03100%0%0%n 8
8GPT-6 AstraMedium75.775.74084 / 390 / 37699%96.1$0.41100%0%0%n 8
9GPT-6.1 SolMedium73.173.13074 / 205 / 36399%92.7$0.0888%12%0%n 8
10Claude Opus 5XHigh71.971.95839 / 410 / 90499%93.3$1.38100%0%0%n 13
11Claude Fable 5.1Medium69.169.13868 / 371 / 59599%88.3$1.1588%12%0%n 8
12GPT-6 SolXHigh68.568.52820 / 222 / 60099%90.0$0.21100%0%0%n 8
13Claude Fable 5.1Low68.368.33885 / 458 / 49898%82.4$0.79100%0%0%n 8
14GPT-6 AstraLow67.267.23730 / 651 / 47599%90.5$0.24100%0%0%n 8
15Grok 4.7XHigh66.268.42597 / 137 / 46098%82.4$0.7875%13%12%n 8
16Grok 4.7Medium65.067.22568 / 184 / 43699%89.5$0.4088%0%12%n 8
17GPT-5.6 SolXHigh62.262.24149 / 399 / 88499%78.5$0.8088%12%0%n 8
18GLM-5.3Max62.164.22254 / 334 / 34091%80.7$0.5588%0%12%n 8
19Claude Opus 5.5Low58.958.92789 / 680 / 62498%82.6$0.12100%0%0%n 9
20GPT-6.1 SolLow58.958.92544 / 525 / 57399%89.5$0.05100%0%0%n 8
21Muse WonderXHigh58.858.82488 / 424 / 49292%82.4$0.49100%0%0%n 8
22GPT-6 SolMedium58.058.02454 / 596 / 59399%89.0$0.0888%12%0%n 8
23Claude Fable 5XHigh56.856.83181 / 680 / 103299%76.9$1.47100%0%0%n 8
24Claude Haiku 5.5XHigh55.957.81982 / 356 / 62091%81.5$0.0588%0%12%n 8
25Claude Opus 5Medium55.855.85572 / 1095 / 137799%76.3$0.45100%0%0%n 14
26MiMo-V2.6-ProEnabled54.754.72257 / 341 / 80092%80.0$0.06100%0%0%n 8
27GPT-5.4XHigh53.855.73130 / 750 / 104098%87.7$1.5288%0%12%n 8
28Claude Opus 4.8XHigh53.255.02602 / 562 / 86499%74.1$0.9375%13%12%n 8
29GLM-5.3High52.752.73018 / 834 / 110899%84.7$0.1675%25%0%n 8
30Claude Opus 5None51.851.84951 / 1609 / 164999%79.9$0.29100%0%0%n 14
31Qwen3.8 Max 0902XHigh51.651.62125 / 586 / 67992%82.1$0.4088%12%0%n 8
32Grok 4.6Medium51.151.12894 / 956 / 100999%70.5$0.1375%25%0%n 8
33Ox AlphaMax50.850.88985 / 1836 / 429796%62.7$0.0088%12%0%n 25
34GLM-5.3 FlashXMax50.050.02142 / 623 / 87498%71.8$0.06100%0%0%n 8
35Muse Spark 1.3XHigh49.349.32142 / 454 / 79092%74.1$0.2588%12%0%n 8
36GPT-5.5XHigh49.150.72352 / 836 / 82299%76.6$2.7488%0%12%n 8
37Qwen3.8 2.4T A95BXHigh48.548.52688 / 1111 / 113699%74.0$0.4375%25%0%n 8
38DeepSeek V4.1 FlashMax48.248.22097 / 740 / 80499%73.0$0.03100%0%0%n 8
39Gemini 3.1 Pro PreviewHigh48.148.12143 / 477 / 102299%70.5$0.3263%37%0%n 8
40GPT-5.6 SolMedium47.647.63148 / 816 / 153899%62.1$0.23100%0%0%n 8
41Claude Fable 5Medium47.447.42668 / 917 / 131599%78.4$0.52100%0%0%n 8
42Grok 4.6XHigh46.746.72576 / 1207 / 132899%71.4$0.2388%12%0%n 8
43GPT-6 SolNone46.446.42069 / 647 / 92499%65.3$0.04100%0%0%n 8
44Muse Spark 1.3Medium46.346.32778 / 781 / 144899%71.8$0.05100%0%0%n 8
45Hy4 PreviewHigh46.146.12452 / 1355 / 124599%70.8$0.1288%12%0%n 8
46Gemini 3.8 FlashHigh45.145.12734 / 753 / 150399%76.5$0.1488%12%0%n 8
47Gemini 3.6 FlashHigh45.048.44917 / 1595 / 237698%74.3$0.4850%25%25%n 16
48Ember-1Max44.944.92014 / 660 / 97699%64.2$0.3088%12%0%n 8
49Grok 4.5High44.644.63216 / 1073 / 173099%72.2$0.0775%25%0%n 8
50GLM-5.3 FlashHigh44.244.22455 / 1111 / 142999%71.2$0.0058100%0%0%n 8
51Gemini 3.5 FlashHigh43.943.92577 / 1020 / 150699%77.1$0.2763%37%0%n 8
52Muse WonderMedium43.743.71829 / 584 / 99392%76.2$0.2575%25%0%n 8
53GLM-5.3 FlashMax43.343.32431 / 947 / 158899%59.6$0.0188%12%0%n 8
54Grok 4.5Medium42.742.72366 / 1011 / 134999%68.0$0.0688%12%0%n 8
55Qwen3.8 27BXHigh42.745.82020 / 457 / 140198%64.6$0.2063%12%25%n 8
56Hy4 PreviewLow41.743.12199 / 725 / 157199%72.6$0.1475%13%12%n 8
57MiMo-V2.6-FlashEnabled41.741.71883 / 536 / 122098%71.2$0.0263%37%0%n 8
58Claude Fable 5Low41.341.32332 / 1214 / 146099%68.5$0.29100%0%0%n 8
59Gemini 3.8 FlashMedium41.241.22189 / 1432 / 142899%70.1$0.07100%0%0%n 8
60Qwen3.8 FlashEnabled41.041.02199 / 1575 / 131799%69.9$0.0463%37%0%n 8
61Mistral Large 4High40.640.61579 / 762 / 105592%70.6$0.1988%12%0%n 8
62GPT-6 LunaXHigh40.640.61762 / 544 / 133599%76.1$0.01100%0%0%n 8
63GPT-5.4Medium40.340.32291 / 1716 / 164199%100$0.28100%0%0%n 8
64Muse Spark 1.2XHigh40.340.31656 / 615 / 113792%65.0$0.14100%0%0%n 8
65Claude Haiku 5.5Medium39.939.91605 / 874 / 116799%61.5$0.01100%0%0%n 8
66Gemini 3.6 FlashMedium38.639.94785 / 2163 / 302099%73.3$0.2688%0%12%n 16
67Claude Sonnet 5XHigh38.638.62449 / 1172 / 191499%59.0$0.35100%0%0%n 8
68GPT-5.6 SolNone38.638.62657 / 1327 / 196499%62.8$0.13100%0%0%n 8
69Gemini 3.5 FlashMedium38.238.22128 / 1210 / 164599%65.1$0.2075%25%0%n 8
70Grok 4.7Low38.039.31427 / 611 / 116499%72.9$0.0875%13%12%n 8
71Muse WonderMinimal37.937.91533 / 947 / 110697%70.2$0.1288%12%0%n 8
72Gemini 3.8 FlashLow37.537.52065 / 1284 / 168999%66.1$0.03100%0%0%n 8
73DeepSeek V4 Pro 0813Max37.337.32171 / 1268 / 164999%67.1$0.1575%25%0%n 8
74GPT-5.6 LunaXHigh37.137.12200 / 1768 / 161299%72.4$0.03100%0%0%n 8
75Muse Spark 1.2Medium36.936.92250 / 1193 / 157999%68.7$0.05100%0%0%n 7
76Kimi K3Low36.836.82432 / 1616 / 225099%77.9$0.0888%12%0%n 8
77DeepSeek V4 ProHigh36.836.82193 / 1050 / 191099%64.0$0.0550%50%0%n 8
78DeepSeek V4.1 FlashHigh36.736.71408 / 1137 / 109799%68.0$0.0288%12%0%n 8
79GPT-5.6 TerraXHigh36.736.72025 / 1318 / 174799%70.4$0.3875%25%0%n 8
80Ember-1High36.336.31403 / 1067 / 117199%55.0$0.1475%25%0%n 8
81Qwen3.8 MaxXHigh36.137.22052 / 1315 / 182799%65.9$0.3589%0%11%n 9
82Claude Sonnet 5.5Medium35.835.81437 / 851 / 135899%68.3$0.0663%37%0%n 8
83GLM-5.3 FlashXHigh35.335.31446 / 802 / 139299%61.6$0.0363%37%0%n 8
84Claude Opus 4.5Medium35.235.22405 / 1527 / 222799%56.2$0.18100%0%0%n 8
85MiMo-V2.6-ProNone35.135.11335 / 948 / 136599%59.0$0.007275%25%0%n 8
86Qwen3.8 2.4T A95BLow35.135.11872 / 1304 / 189599%59.5$0.1588%12%0%n 8
87GLM-5.2High34.834.81681 / 1650 / 162399%76.8$0.1275%25%0%n 8
88GPT-5.5Medium34.534.51666 / 1500 / 147499%59.9$0.4488%12%0%n 8
89GLM-5.3 FlashXLow34.434.41314 / 1077 / 125199%58.0$0.008575%25%0%n 8
90MiMo-V2.5-ProEnabled33.836.31432 / 756 / 160699%61.4$0.130%75%25%n 8
91o3High33.737.16203 / 1425 / 707598%48.5$0.0968%0%32%n 28
92GLM-5.3Low33.433.41767 / 1542 / 181299%59.7$0.05100%0%0%n 8
93Ox AlphaHigh33.434.36367 / 3785 / 628799%50.3$0.0073%17%10%n 29
94Space Bunny AlphaXHigh33.235.7996 / 624 / 115698%62.7$0.0013%62%25%n 8
95Qwen3.8 MaxMedium33.233.21785 / 1476 / 187699%54.4$0.10100%0%0%n 8
96GPT-5.6 TerraMedium33.233.21804 / 1396 / 196799%62.0$0.1088%12%0%n 8
97DeepSeek V4 ProXHigh33.133.11700 / 1524 / 188599%69.5$0.1163%37%0%n 8
98Claude Opus 4.8None32.934.11475 / 999 / 156599%58.0$0.1688%0%12%n 8
99Grok 4.5Low32.832.82109 / 1711 / 229799%58.3$0.0788%12%0%n 8
100Kimi K3High32.632.62009 / 1924 / 221599%53.9$0.2988%12%0%n 8

Not yet ranked (13)

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.

  • 6Programs still being generated The model has not yet finished a player program for every game.
  • 7Too many programs failed Too few of its player programs compiled and ran to qualify for a rank.
Show all 13 entriesHide entries
Entries that are not yet ranked, with their score so far and why they are not ranked
Model Reasoning Score so far Why not ranked yet
Step 5 PreviewMedium59.1Programs still being generated
Solar Mini 4XHigh29.7Too many programs failed
Step 5 PreviewLow19.6Programs still being generated
Ling 3.1 FlashNone18.8Programs still being generated
Qwen3.8 27BNone18.3Too many programs failed
Nex N2 ProNone17.6Too many programs failed
Solar Mini 4Medium17.5Programs still being generated
Ling 3.0 FlashNone16.0Programs still being generated
Ling 3.0 FlashEnabled14.9Too many programs failed
GPT-4.1 NanoReasoning12.6Too many programs failed
North Mini CodeNone11.0Too many programs failed
Solar Mini 4None5.3Programs still being generated
Granite 4.2 8BLow4.0Too many programs failed

How this is scored

1. Generate players

Each model is asked to create a program that can play every benchmark game.

2. Play matches

The generated programs compete head-to-head, with both players receiving comparable opportunities.

3. Score each game

Wins, draws, and losses produce a rating for each program; after an allowance for rating uncertainty it becomes a 0–100 score for each game.

4. Combine games

The main score is the mean across playable games, multiplied by the program success rate raised to 0.25. Failed programs lower this reliability factor; they are not averaged in as zero game scores. A program rejected only for being too slow does not play and does not lower it.

5. Keep settings clear

Each model and reasoning setting keeps its own row in the standings.

6. Add context

Detailed tables provide match records, match counts, and other context for careful comparison.