reasoning benchmark
Hallusion Bench
A comprehensive benchmark designed to evaluate image-context reasoning in large visual-language models (LVLMs) by challenging models with 346 images and 1,129 carefully crafted questions to assess language hallucination and visual illusion
Updated Aug 11, 2026
Models16
Model coverage16
MetricScore
EvidenceB
Hallusion Bench Ranking
Higher score ranks better on this benchmark.
Hallusion Bench Score Distribution
A closer view of the leading scores on this benchmark.
Hallusion Bench Highlights
The leading models and scores on this benchmark.
What is Hallusion Bench?
What Hallusion Bench measures and how its scores work.
A comprehensive benchmark designed to evaluate image-context reasoning in large visual-language models (LVLMs) by challenging models with 346 images and 1,129 carefully crafted questions to assess language hallucination and visual illusion
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Hallusion Bench
- Modality
- multimodal
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- hallusion-bench|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Hallusion Bench.
Which model scores highest on Hallusion Bench?
Qwen3.5-27B is currently ranked first with 70.0%.
What does Hallusion Bench measure?
A comprehensive benchmark designed to evaluate image-context reasoning in large visual-language models (LVLMs) by challenging models with 346 images and 1,129 carefully crafted questions to assess language hallucination and visual illusion
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
16 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.