AbstentionBench - stale - CoCoNot/Temporal - Recall: leaderboard

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

Top models

#ModelScoreOverall rank
1Llama-3.1-Tulu-3-70B91.89#499
2Llama-3.1-Tulu-3-8B86.49#848
3Llama-3.1-Tulu-3-70B-DPO81.08#732
4GPT-4o78.38#357
5Llama-3.1-Tulu-3-8B-DPO78.38#992
6Llama 3.1 8B Instruct75.68#1017
7Llama 3.1 405B Instruct75.68#470
8O175.68#190
9Qwen 2.5 32B Instruct72.97#509
10Llama-3.1-Tulu-3-8B-SFT72.97#977
11Llama 3.1 70B Instruct67.57#567
12Mistral 7B Instruct (v0.3)67.57#1255
13OLMo-7B-0724-Instruct-hf67.57#1441
14Llama 3.3 70B Instruct64.86#541
15Gemini 1.5 Pro59.46#454

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

Interactive version: theaggregate.ai/benchmark?slug=abstentionbench-stale-coconot-temporal-recall · How It Works · Data refreshed daily, snapshot 2026-11-05.