Vision & Language Benchmark

SimpleVQA

SimpleVQA - simple visual question answering benchmark.

Category

Vision & Language

Score type

percent

Scale

100%

higher is better

Models tested

11

What is SimpleVQA?

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

What does it test?

SimpleVQA 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: SimpleVQA - simple visual question answering benchmark.

Frequently asked questions

What is the SimpleVQA benchmark?

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

What does SimpleVQA test?

SimpleVQA 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 SimpleVQA 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 SimpleVQA 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/simplevqa/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 11 models tested

Reset
# Model Score Date Source Verified
1 Muse-Spark-Open-816B-A42B
Meta Superintelligence Lab
73.6%
15.10.2026 Report Verified
2 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
61.7%
01.02.2026 Report Verified
3 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
61.3%
01.02.2026 Report Unverified
4 Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
58.9%
16.04.2026 Qwen Team (official model card) Verified
5 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
58.3%
16.04.2026 Qwen Team (official model card - comparison) Unverified
6 Qwen3.6-27B
Qwen Team (Alibaba Cloud)
56.1%
22.04.2026 Qwen Team (official model card) Verified
7 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
56%
16.04.2026 Qwen Team (official model card - comparison) Unverified
8 Gemma4-31B-it
Google
52.9%
16.04.2026 Qwen Team (official model card - comparison) Unverified
9 Gemma4-26B-A4B
Google
52.2%
16.04.2026 Qwen Team (official model card - comparison) Unverified
10 Qwen3.5-4B
Qwen
43.4%
01.02.2026 Report Verified
11 LFM3-VL-2B
LiquidAI
36.3%
— Report Verified

What now?

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