AbstentionBench - underspecified intent - CoCoNot/Incomprehensible - F1: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports underspecified intent - CoCoNot/Incomprehensible - 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
1Qwen 2.5 32B Instruct97.92#509
2Llama-3.1-Tulu-3-8B-SFT97.92#977
3GPT-4o96.84#357
4Llama-3.1-Tulu-3-70B-DPO96.84#732
5Llama 3.1 8B Instruct95.74#1017
6Llama-3.1-Tulu-3-8B95.74#848
7Gemini 1.5 Pro94.62#454
8Llama-3.1-Tulu-3-70B94.62#499
9Llama-3.1-Tulu-3-8B-DPO93.48#992
10Llama 3.1 405B Instruct92.31#470
11O192.31#190
12Llama 3.1 70B Instruct91.11#567
13Mistral 7B Instruct (v0.3)91.11#1255
14OLMo-7B-0724-Instruct-hf86.05#1441
15Llama 3.3 70B Instruct83.33#541

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-intent-coconot-incomprehensible-f1 · How It Works · Data refreshed daily, snapshot 2026-11-05.