Vision & Language Benchmark

HallusionBench

HallusionBench - benchmark for language and visual hallucination.

Category

Vision & Language

Score type

percent

Scale

100%

higher is better

Models tested

10

What is HallusionBench?

HallusionBench is a benchmark for understanding images combined with text. The official description says: "HallusionBench - benchmark for language and visual hallucination". Below we describe in simple words what benchmarks of this type generally examine.

What does it test?

HallusionBench measures understanding images combined with text. In detail, it checks:

  • answering questions about images (figures, photos, charts, memes)
  • reading text inside images and connecting it to the question
  • visual reasoning such as counting, locating and comparing objects
  • combining what is seen with general knowledge

How to read the score

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Official methodology note: HallusionBench - benchmark for language and visual hallucination.

Frequently asked questions

What is the HallusionBench benchmark?

HallusionBench is a benchmark for understanding images combined with text. The official description says: 'HallusionBench - benchmark for language and visual hallucination'. Below we describe in simple words what benchmarks of this type generally examine.

What does HallusionBench test?

HallusionBench mainly measures understanding images combined with text. Concretely, it checks: answering questions about images (figures, photos, charts, memes); reading text inside images and connecting it to the question; visual reasoning such as counting, locating and comparing objects.

How is the HallusionBench score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.

Where do I get HallusionBench data and scores?

The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/hallusionbench/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 10 models tested

Reset
# Model Score Date Source Verified
1 d1-2B
LiquidAI
72.1%
— LiquidAI/d1-2B model card (performance table) Unverified
2 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
70%
16.04.2026 Qwen Team (official model card - comparison) Unverified
3 Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
69.8%
16.04.2026 Qwen Team (official model card) Verified
4 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
67.9%
16.04.2026 Qwen Team (official model card - comparison) Unverified
5 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
67.6%
01.02.2026 Report Verified
6 Gemma4-31B-it
Google
67.4%
16.04.2026 Qwen Team (official model card - comparison) Unverified
7 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
66.7%
01.02.2026 Report Unverified
8 Gemma4-26B-A4B
Google
66.1%
16.04.2026 Qwen Team (official model card - comparison) Unverified
9 LFM3-VL-2B
LiquidAI
65.6%
— Report Verified
10 Qwen3.5-4B
Qwen
65%
01.02.2026 Report Verified

What now?

You've seen how models score on HallusionBench — here's what to do next.