AbstentionBench - stale - FreshQA - Precision: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports stale - FreshQA - 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
1Llama 3.1 70B62.5#588
2O153.13#190
3Gemini 1.5 Pro51.52#454
4Llama 3.1 8B51.02#1130
5GPT-4o46#357
6DeepSeek R1 Distill Llama 70B45.45#614
7Llama-3.1-Tulu-3-8B36.61#848
8Llama 3.3 70B Instruct35.71#541
9Llama-3.1-Tulu-3-8B-SFT34.72#977
10Llama-3.1-Tulu-3-8B-DPO34.19#992
11Llama-3.1-Tulu-3-70B-DPO33.9#732
12Llama-3.1-Tulu-3-70B33.33#499
13OLMo-7B-0724-Instruct-hf32.06#1441
14Qwen 2.5 32B Instruct31.9#509
15Llama 3.1 70B Instruct30.11#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-stale-freshqa-precision · How It Works · Data refreshed daily, snapshot 2026-11-05.