CLEM PrivateShared: leaderboard

CLEM text release v3.0: models track private and shared information during dialogue. 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: Estimated already saturated. 30 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.2 (High)95.7#110 (GPT-5.2)
2GPT-5.2 (Medium)94.27#110 (GPT-5.2)
3Kimi K2.5 (Non-reasoning)92.69#144 (Kimi K2.5)
4GLM-4.791.15#192
5Llama 3.3 70B Instruct90.59#534
6Kimi K2 (Thinking)88.81#243 (Kimi K2)
7Llama 3.1 70B Instruct88.12#561
8GLM-4.686.92#252
9Gemini 3 Flash (Preview)83.26#82
10GLM-5 (Non-reasoning)57.03#141 (GLM-5)
11Qwen 3 Max55.94#208
12Qwen 2.5 Coder 32B Instruct49.53#528
13Qwen 2.5 72B Instruct45.26#454
14DeepSeek V3.2 (Non-reasoning)43.4#205 (DeepSeek V3.2)
15DeepSeek V3.242.6#205

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

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