CLEM ImageGame: leaderboard

CLEM text release v3.0: models communicate symbolic grid descriptions in text. Scores combine protocol-valid play and conditional task quality, higher is better. Headline preserves the native published product of macro-average played percentage and macro-average conditional quality; per-game scores multiply source-published played and quality components without extra rounding. Source temperature, player configuration and exact evidenced model/checkpoint settings are retained. Undefined conditional quality remains missing rather than imputed zero.

Metric: Game Clemscore (%), text v3.0; published played × quality / 100. Source: huggingface.co. Saturation forecast: Not forecast. 26 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.2 (High)99.82#110 (GPT-5.2)
2GPT-5.2 (Medium)99.8#110 (GPT-5.2)
3GLM-4.792.5#192
4Qwen 3 Next 80B A3B Instruct92#368
5GLM-4.691.35#252
6Gemini 3 Flash (Preview)87.5#82
7GLM-5 (Non-reasoning)84.73#141 (GLM-5)
8Llama 3.1 70B Instruct82.9#561
9Llama 3.3 70B Instruct80.4#534
10Kimi K2 (Thinking)72.22#243 (Kimi K2)
11GPT-OSS-20B60.5#518
12MiniMax-M2.558.98#303
13Qwen 2.5 72B Instruct49.25#454
14Llama 3.1 8B Instruct24.12#1035
15Qwen 3 Max17.5#208

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=clem-imagegame · How It Works · Data refreshed daily, snapshot 2026-10-20.