CLEM TextMapWorld: leaderboard

CLEM text release v3.0: models navigate a textual spatial map. 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. 31 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash (Preview)91.35#82
2GPT-5.2 (High)85.01#110 (GPT-5.2)
3GPT-5.2 (Medium)84.79#110 (GPT-5.2)
4GLM-4.782.52#192
5GLM-5 (Non-reasoning)81#141 (GLM-5)
6Qwen 3 Max80.18#208
7Kimi K2 (Thinking)79.81#243 (Kimi K2)
8Kimi K2.5 (Non-reasoning)77.42#144 (Kimi K2.5)
9DeepSeek V3.274.36#205
10Qwen 3 Next 80B A3B Instruct74.06#368
11Mistral Large 371.71#401
12Llama 3.3 70B Instruct69.92#534
13MiniMax-M2.569.82#303
14Qwen 2.5 Coder 32B Instruct68.86#528
15Qwen 2.5 72B Instruct68.82#454

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

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