AbstentionBench - underspecified context - BB/Disambiguate - F1: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports underspecified context - BB/Disambiguate - F1 as Abstention F1 (%); 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 F1 (%). Source: github.com. Saturation forecast: Estimated already saturated. 20 models tracked.

Top models

#ModelScoreOverall rank
1Llama 3.1 70B66.99#588
2Llama 3.1 405B Instruct62.56#470
3Llama 3.1 70B Instruct61.28#567
4Qwen 2.5 32B Instruct61.19#509
5Llama 3.3 70B Instruct60.58#541
6O160#190
7Gemini 1.5 Pro53.68#454
8GPT-4o50.76#357
9Llama 3.1 8B Instruct46.83#1017
10Llama 3.1 8B45.8#1130
11Llama-3.1-Tulu-3-70B-DPO44.83#732
12OLMo-7B-0724-Instruct-hf37.61#1441
13DeepSeek R1 Distill Llama 70B35.71#614
14Llama-3.1-Tulu-3-70B32.99#499
15Llama-3.1-Tulu-3-8B29.13#848

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

Interactive version: theaggregate.ai/benchmark?slug=abstentionbench-underspecified-context-bb-disambiguate-f1 · How It Works · Data refreshed daily, snapshot 2026-11-05.