AbstentionBench - false premise - QAQA - F1: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports false premise - QAQA - 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
1O174.13#190
2GPT-4o68.14#357
3Gemini 1.5 Pro67.51#454
4Llama-3.1-Tulu-3-70B66.39#499
5Llama-3.1-Tulu-3-70B-DPO63.81#732
6Llama 3.1 405B Instruct63#470
7Qwen 2.5 32B Instruct59.46#509
8Llama-3.1-Tulu-3-8B-DPO59.18#992
9OLMo-7B-0724-Instruct-hf59.02#1441
10Mistral 7B Instruct (v0.3)57.6#1255
11Llama 3.3 70B Instruct55.4#541
12Llama-3.1-Tulu-3-8B54.75#848
13Llama 3.1 70B Instruct54.55#567
14Llama 3.1 8B Instruct53.39#1017
15Llama-3.1-Tulu-3-8B-SFT47.8#977

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

Interactive version: theaggregate.ai/benchmark?slug=abstentionbench-false-premise-qaqa-f1 · How It Works · Data refreshed daily, snapshot 2026-11-05.