AbstentionBench - answer unknown - CoCoNot/Unsupported - Precision: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports answer unknown - CoCoNot/Unsupported - 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
1Mistral 7B Instruct (v0.3)100#1255
2O1100#190
3DeepSeek R1 Distill Llama 70B100#614
4Llama-3.1-Tulu-3-70B-DPO99.14#732
5Qwen 2.5 32B Instruct99.11#509
6Llama-3.1-Tulu-3-8B-DPO99.11#992
7GPT-4o99.1#357
8OLMo-7B-0724-Instruct-hf98.78#1441
9Llama-3.1-Tulu-3-8B98.21#848
10Llama 3.1 405B Instruct98.13#470
11Llama 3.1 8B Instruct98.11#1017
12Llama 3.1 70B Instruct98.06#567
13Gemini 1.5 Pro97.41#454
14Llama-3.1-Tulu-3-70B96.64#499
15Llama 3.3 70B Instruct96.26#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-answer-unknown-coconot-unsupported-precision · How It Works · Data refreshed daily, snapshot 2026-11-05.