CLEM Codenames: leaderboard

CLEM text release v3.0: models communicate and infer associations in a word guessing game. 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: Around January 2027. 30 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.2 (High)87.69#110 (GPT-5.2)
2GPT-5.2 (Medium)73.08#110 (GPT-5.2)
3Gemini 3 Flash (Preview)64.62#82
4GLM-4.745.38#192
5GLM-4.643.85#252
6Kimi K2 (Thinking)43.84#243 (Kimi K2)
7GPT-OSS-20B43.08#518
8MiniMax-M2.538.46#303
9Llama 3.1 70B Instruct34.61#561
10Qwen 3 Max25.39#208
11Llama 3.3 70B Instruct24.61#534
12Kimi K2.5 (Non-reasoning)22.31#144 (Kimi K2.5)
13Qwen 2.5 Coder 32B Instruct22.31#528
14DeepSeek V3.2 (Non-reasoning)22.31#205 (DeepSeek V3.2)
15DeepSeek V3.222.31#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-codenames · How It Works · Data refreshed daily, snapshot 2026-10-20.