AbstentionBench - underspecified context - MMLU History - F1: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports underspecified context - MMLU History - 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. 21 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 1.5 Pro71.88#454
2GPT-4o67.8#357
3Qwen 2.5 32B Instruct62.3#509
4O160.71#190
5Llama-3.1-Tulu-3-70B-DPO58.18#732
6Llama 3.1 8B Instruct53.57#1017
7Llama-3.1-Tulu-3-70B52.83#499
8O1 (High)52.83#190 (O1)
9Llama 3.1 70B Instruct51.85#567
10Llama 3.1 405B Instruct47.27#470
11TinyLlama-1.1B-Chat-v1.034.62#1547
12Llama 3.3 70B Instruct33.33#541
13OLMo-7B-0724-Instruct-hf29.79#1441
14Llama-3.1-Tulu-3-8B26.67#848
15Llama-3.1-Tulu-3-8B-DPO26.67#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-underspecified-context-mmlu-history-f1 · How It Works · Data refreshed daily, snapshot 2026-11-05.