AbstentionBench - answer unknown - CoCoNot/Unknowns - Recall: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports answer unknown - CoCoNot/Unknowns - 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 405B Instruct100#470
2O1100#190
3Llama-3.1-Tulu-3-70B100#499
4Llama-3.1-Tulu-3-70B-DPO100#732
5GPT-4o98.51#357
6Llama 3.1 70B Instruct98.51#567
7Qwen 2.5 32B Instruct98.51#509
8Llama-3.1-Tulu-3-8B-SFT98.51#977
9Llama-3.1-Tulu-3-8B98.51#848
10Llama-3.1-Tulu-3-8B-DPO98.51#992
11Llama 3.3 70B Instruct97.01#541
12Gemini 1.5 Pro97.01#454
13Llama 3.1 8B Instruct95.52#1017
14Mistral 7B Instruct (v0.3)95.52#1255
15OLMo-7B-0724-Instruct-hf85.07#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-answer-unknown-coconot-unknowns-recall · How It Works · Data refreshed daily, snapshot 2026-11-05.