PhantomBench - Entities (Date): leaderboard

PhantomBench (2026) asks language models about generated terms and entities that do not exist, verified absent from a 2.3-trillion-token corpus, and counts answers that invent content instead of abstaining, as labeled by a Gemini 2.5 Flash judge. This board is the hallucination rate in percent on 1,200 non-existent entities such as events, holidays, elections, disasters and creative works, when the prompt asks when it originated, presupposing it exists; lower is better.

Metric: Hallucination rate (%): share of answers that do not abstain on the Phantom-E subset (1,200 generated non-existent entities: events, holidays, elections, disasters, creative works and places), verified absent from the 2.3-trillion-token Dolma corpus, when the prompt asks when the concept originated or was introduced (presupposing it exists); a Gemini 2.5 Flash judge labels abstention; reasoning-model rates count only generations that reached a final answer; lower is better. Source: arxiv.org. 16 models tracked.

Top models

#ModelScoreOverall rank
1Llama 3.1 8B Instruct1.33#4246
2Qwen 2.5 7B Instruct9.67#2564
3Qwen 3 14B10#1233
4Qwen 3 8B11.75#1830
5Gemma 2 9B (IT)16.25#2262
6Mistral 7B Instruct (v0.3)20.08#6653
7Qwen 3 4B20.5#2281
8Qwen 3 1.7B32.08#5520
9Gemini 2.5 Pro33.25#266
10Qwen 3 32B33.42#960
11Gemini 2.5 Flash37.17#453
12DeepSeek R1 Distill Qwen 32B48.46#1788
13GPT-OSS-20B (Low)56.18#1147 (GPT-OSS-20B)
14Gemma 3 12B (IT)77.33#1837

Interactive version: theaggregate.ai/benchmark?slug=phantombench-entities-date · How It Works · Data refreshed daily, snapshot 2026-11-13.