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

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports answer unknown - CoCoNot/Unknowns - Precision as Abstention Precision (%); 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 Precision (%). Source: github.com. Saturation forecast: Estimated already saturated. 20 models tracked.

Top models

#ModelScoreOverall rank
1GPT-4o100#357
2Llama 3.1 8B Instruct100#1017
3Llama 3.3 70B Instruct100#541
4Llama 3.1 70B Instruct100#567
5Mistral 7B Instruct (v0.3)100#1255
6Llama 3.1 8B100#1130
7Gemini 1.5 Pro100#454
8Llama 3.1 405B Instruct100#470
9Qwen 2.5 32B Instruct100#509
10Llama 3.1 70B100#588
11O1100#190
12DeepSeek R1 Distill Llama 70B100#614
13Llama-3.1-Tulu-3-8B-SFT100#977
14Llama-3.1-Tulu-3-8B100#848
15Llama-3.1-Tulu-3-70B100#499

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