IdeaAMBIG - Readiness Assessment - Real-World: leaderboard

IdeaAMBIG (arXiv 2609.10539v1, Table 1): the model judges whether a research-idea specification is Ready or NotReady for implementation, on real-world specifications from GitHub issues and reproducibility reports. Score is Macro-F1 over 100 Ready and 100 NotReady specifications, in percent; higher is better. Zero-shot fixed prompts at temperature 0.

Metric: Macro-F1 (%; 100 Ready and 100 NotReady specifications per subset). Source: arxiv.org. Saturation forecast: Around 2028. 13 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.6 Sol67.5#22
2Claude Sonnet 559.3#65
3Qwen 3.5 397B A17B57.5#154
4Gemma 4 31B (IT)47.1#178
5Gemini 3.1 Pro (Preview)45.8#64
6GLM-5.245.1#80
7DeepSeek V3.244.5#210
8DeepSeek R1 052844.3#232
9Qwen 3 8B40.1#678
10Qwen 3 32B34.5#449
11Qwen 3.5 9B33.3#391
12Kimi K332.7#35
13GPT-OSS-120B30#346

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

Interactive version: theaggregate.ai/benchmark?slug=ideaambig-readiness-assessment-real-world · How It Works · Data refreshed daily, snapshot 2026-11-05.