AbstentionBench - answer unknown - KUQ/Unsolved problems - Recall: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports answer unknown - KUQ/Unsolved problems - 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 Pro77.45#454
2Llama-3.1-Tulu-3-70B72.34#499
3GPT-4o71.49#357
4Llama-3.1-Tulu-3-70B-DPO70.21#732
5O167.66#190
6Llama-3.1-Tulu-3-8B-DPO66.81#992
7Llama 3.3 70B Instruct66.38#541
8Llama-3.1-Tulu-3-8B65.11#848
9Llama 3.1 8B Instruct64.68#1017
10Llama 3.1 405B Instruct63.83#470
11Mistral 7B Instruct (v0.3)61.28#1255
12Qwen 2.5 32B Instruct60.43#509
13Llama 3.1 70B Instruct58.72#567
14OLMo-7B-0724-Instruct-hf56.17#1441
15Llama-3.1-Tulu-3-8B-SFT53.19#977

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

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