FDE Requirement Discovery - Extreme ambiguity: leaderboard

Enterprise text-to-SQL FDE study Table 1:10 independent simulated-customer discovery trajectories per model and ambiguity level; recovery of 17 known core requirements, judged against frozen annotations. The three ambiguity levels and their mean remain separate. Dialogue counts do not measure capability and delivery-agent training outcomes are different protocols. No unreported reasoning setting is inferred. Metric: Recovery rate (%).

Metric: Recovery rate (%). Source: arxiv.org. Saturation forecast: Around February 2027. 15 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 5.583.5#3
2Claude Opus 580.6#16
3Claude Sonnet 5.578.8#14
4GPT-6.1 Sol76.5#7
5Claude Fable 575.3#20
6Grok 4.772.9#26
7GPT-5.6 Sol71.8#22
8Gemini 2.5 Flash62.4#255
9Gemma 4 31B60#212
10GLM-5.3 Flash52.4#77
11Command A51.2#498
12GPT-OSS-120B50.6#346
13Llama 3.3 70B45.3#578
14GPT-5.4 Mini44.1#228
15Grok 4.20 (Reasoning)42.4#179 (Grok 4.20)

No result here: #6 GPT-6 Astra, #9 Gemini 4 Argon, #10 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=fde-requirement-discovery-extreme-ambiguity · How It Works · Data refreshed daily, snapshot 2026-11-05.