ConfBench - Confidence AUROC: leaderboard

ConfBench (Amazon, 2026) degrades 75 verified invoices with 20 controlled augmentation pipelines into 1,346 variants and asks a vision-language model to extract entities and state a confidence for each, here as verbalized top-4 guesses from the OCR text plus the image. Score is the AUROC of the confidences for telling correct from incorrect extractions, on a 0-1 scale where 0.5 is chance; higher is better.

Metric: AUROC of the verbalized confidence for separating correct from incorrect extracted entities (0-1, 0.5 is chance; verbalized top-4 guesses with probabilities in one call, OCR text with Amazon Textract confidences plus the document image, over the entity fields of 1,346 degraded variants of 75 RealKIE-FCC-Verified invoices). Source: arxiv.org. Saturation forecast: Around February 2027. 7 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 4.60.84#102
2Claude Sonnet 4.50.77#250
3Claude Haiku 4.50.74#568
4Qwen 3.6 27B0.72#341
5Kimi K2.50.67#256
6Qwen 3 VL 235B A22B0.62#479
7Gemma 3 12B0.58#2000

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=confbench-confidence-auroc · How It Works · Data refreshed daily, snapshot 2026-11-13.