AbstentionBench - false premise - FalseQA - F1: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports false premise - FalseQA - 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
1Gemini 1.5 Pro75.54#454
2Qwen 2.5 32B Instruct74.51#509
3O174.26#190
4GPT-4o72.38#357
5Llama 3.3 70B Instruct71.96#541
6Llama 3.1 405B Instruct68.37#470
7Llama 3.1 70B Instruct66.79#567
8OLMo-7B-0724-Instruct-hf65.12#1441
9Llama-3.1-Tulu-3-70B-DPO64.96#732
10Mistral 7B Instruct (v0.3)64.89#1255
11Llama-3.1-Tulu-3-70B64.83#499
12Llama 3.1 8B Instruct60.74#1017
13DeepSeek R1 Distill Llama 70B58.74#614
14Llama-3.1-Tulu-3-8B-SFT57.17#977
15Llama-3.1-Tulu-3-8B-DPO55.8#992

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-falseqa-f1 · How It Works · Data refreshed daily, snapshot 2026-11-05.