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

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports answer unknown - KUQ/Unsolved problems - 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
1DeepSeek R1 Distill Llama 70B93.75#614
2Llama-3.1-Tulu-3-8B91.62#848
3Llama-3.1-Tulu-3-8B-SFT91.24#977
4O190.86#190
5Llama-3.1-Tulu-3-8B-DPO90.75#992
6Llama 3.3 70B Instruct88.64#541
7Gemini 1.5 Pro88.35#454
8Llama-3.1-Tulu-3-70B88.08#499
9GPT-4o87.96#357
10Llama-3.1-Tulu-3-70B-DPO86.84#732
11Llama 3.1 70B Instruct86.25#567
12Qwen 2.5 32B Instruct86.06#509
13Mistral 7B Instruct (v0.3)85.71#1255
14Llama 3.1 70B84.51#588
15Llama 3.1 8B83.94#1130

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