AbstentionBench - subjective - KUQ/Controversial - Recall: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports subjective - KUQ/Controversial - Recall as Abstention Recall (%); values converted from 0-1 to percent. Precision and recall must be read together: always abstaining is not necessarily useful. Scenario/dataset pairs and SFT/DPO/RL checkpoints remain separate; no synthetic overall average. Source: facebookresearch/AbstentionBench analysis/abstention_performance.csv.

Metric: Abstention Recall (%). Source: github.com. Saturation forecast: Estimated already saturated. 20 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 1.5 Pro75.37#454
2Llama-3.1-Tulu-3-70B71.81#499
3Llama-3.1-Tulu-3-70B-DPO71.51#732
4GPT-4o70.33#357
5Llama 3.1 8B Instruct67.95#1017
6Llama 3.3 70B Instruct67.95#541
7Llama-3.1-Tulu-3-8B-DPO64.99#992
8Llama 3.1 405B Instruct64.09#470
9O163.2#190
10Llama-3.1-Tulu-3-8B61.42#848
11Llama 3.1 70B Instruct58.46#567
12Qwen 2.5 32B Instruct58.46#509
13Mistral 7B Instruct (v0.3)54.9#1255
14Llama-3.1-Tulu-3-8B-SFT51.93#977
15OLMo-7B-0724-Instruct-hf51.63#1441

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

Interactive version: theaggregate.ai/benchmark?slug=abstentionbench-subjective-kuq-controversial-recall · How It Works · Data refreshed daily, snapshot 2026-11-05.