AbstentionBench - underspecified context - GSM8K - Precision: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports underspecified context - GSM8K - 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. 23 models tracked.

Top models

#ModelScoreOverall rank
1GPT-4o100#357
2Llama 3.3 70B Instruct100#541
3Qwen 2.5 32B Instruct100#509
4Llama-3.1-Tulu-3-8B100#848
5Llama-3.1-Tulu-3-70B100#499
6Llama-3.1-Tulu-3-70B-DPO100#732
7O1 (High)100#190 (O1)
8O199.91#190
9Llama 3.1 70B Instruct99.91#567
10Gemini 1.5 Pro99.91#454
11Llama-3.1-Tulu-3-8B-DPO99.78#992
12Llama 3.1 8B Instruct99.73#1017
13Llama 3.1 405B Instruct99.65#470
14Llama-3.1-Tulu-3-8B-SFT99.52#977
15DeepSeek R1 Distill Llama 70B98.95#614

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-gsm8k-precision · How It Works · Data refreshed daily, snapshot 2026-11-05.