Vision & Language Benchmark

ZEROBench

ZEROBench - visual reasoning puzzle benchmark. Very challenging, scores typically in single digits.

Category

Vision & Language

Score type

percent

Scale

relative

higher is better

Models tested

10

What is ZEROBench?

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

What does it test?

ZEROBench 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: ZEROBench - visual reasoning puzzle benchmark. Very challenging, scores typically in single digits.

Frequently asked questions

What is the ZEROBench benchmark?

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

What does ZEROBench test?

ZEROBench 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 ZEROBench score calculated?

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

Where do I get ZEROBench 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/zerobench/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 DeepSeek-V4.1-Flash-1017
DeepSeek
51%
17.10.2026 Report Verified
2 Muse-Spark-Open-816B-A42B
Meta Superintelligence Lab
50%
15.10.2026 Report Verified
3 DeepSeek-V4.1-Flash
DeepSeek
49%
10.09.2026 Report Verified
4 Kimi K3
Moonshot AI
41%
18.08.2026 Report Verified
5 DeepSeek-V4-Flash-Vision-Exp
DeepSeek
35%
08.09.2026 Report Verified
6 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
10%
01.02.2026 Report Unverified
7 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
9%
01.02.2026 Report Verified
8 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
8%
01.02.2026 Report Unverified
9 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
4%
01.02.2026 Report Unverified
10 Qwen3.5-4B
Qwen
3%
01.02.2026 Report Verified

What now?

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