LUNAR - Curated Context: leaderboard

Personalized response quality with only the query-relevant behavioral evidence in context (an oracle setting), averaging GPT-5.1-judged personalization coverage and depth across daily-life domains such as clothing, food, housing and mobility (LUNAR, arXiv 2608.05246v2, Table 4). 1-5 scale; higher is better; 19 models.

Metric: Personalization score (1-5; mean of coverage and depth, GPT-5.1 judge). Source: arxiv.org. Saturation forecast: Around February 2027. 19 models tracked.

Top models

#ModelScoreOverall rank
1Kimi K2.64.07#113
2Gemini 3 Flash (Preview)4.02#90
3GLM-5.13.86#109
4DeepSeek V4 Flash3.78#155
5DeepSeek V4 Pro3.66#112
6MiniMax-M2.73.57#270
7GPT-4.1 Mini3.39#363
8Qwen 3 30B A3B 2507 Instruct3.37#492
9Ling-2.6-1T3.35#307
10Qwen 3 14B (Non-reasoning)3.27#542 (Qwen 3 14B)
11Ling-2.6-flash3.19#533
12GLM-4.7 Flash3.15#543
13Qwen 3 8B (Non-reasoning)3.12#678 (Qwen 3 8B)
14Qwen 3 32B (Non-reasoning)3.12#449 (Qwen 3 32B)
15GPT-4o Mini3.08#598

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

Interactive version: theaggregate.ai/benchmark?slug=lunar-curated-context · How It Works · Data refreshed daily, snapshot 2026-11-05.