AbstentionBench - subjective - MoralChoice - Recall: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports subjective - MoralChoice - 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
1Llama 3.1 70B57.35#588
2Llama 3.1 8B38.38#1130
3Llama-3.1-Tulu-3-70B29.71#499
4Llama-3.1-Tulu-3-70B-DPO29.26#732
5O129.12#190
6Llama 3.1 405B Instruct28.09#470
7Llama-3.1-Tulu-3-8B-DPO27.79#992
8Mistral 7B Instruct (v0.3)26.62#1255
9Llama-3.1-Tulu-3-8B26.32#848
10GPT-4o26.18#357
11Qwen 2.5 32B Instruct26.18#509
12Llama-3.1-Tulu-3-8B-SFT25.74#977
13Llama 3.1 8B Instruct25.29#1017
14Llama 3.3 70B Instruct24.26#541
15Llama 3.1 70B Instruct24.26#567

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-moralchoice-recall · How It Works · Data refreshed daily, snapshot 2026-11-05.