Vision & Language Benchmark

MathVision

MathVision - visual math problem solving benchmark. Reports Without CI and With CI (Consistency Inference) scores.

Category

Vision & Language

Score type

percent

Scale

100%

higher is better

Models tested

18

What is MathVision?

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

What does it test?

MathVision 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: MathVision - visual math problem solving benchmark. Reports Without CI and With CI (Consistency Inference) scores.

Frequently asked questions

What is the MathVision benchmark?

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

What does MathVision test?

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

Model scores 18 models tested

Reset
# Model Score Date Source Verified
1 Kimi K3
Moonshot AI
97.8%
18.08.2026 Report Verified
2 Qwen3.8-Flash-Next
Qwen Team (Alibaba)
90.6%
26.08.2026 Report Verified
3 Qwen3.8-27B
Qwen Team (Alibaba Cloud)
90%
18.08.2026 Report Verified
4 Kimi K2.6
Moonshot AI
87.4%
23.08.2026 Report Verified
5 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
86.2%
01.02.2026 Report Verified
6 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
86%
01.02.2026 Report Unverified
7 Gemma4-31B-it
Google
85.6%
02.07.2026 Report Verified
8 Qwen3.6-27B
Qwen Team (Alibaba Cloud)
85.1%
18.08.2026 Report Unverified
9 Kimi K2.5
Moonshot AI
84.2%
23.08.2026 Report Verified
10 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
83.9%
01.02.2026 Report Unverified
11 Gemma4-26B-A4B
Google
82.4%
02.07.2026 Report Verified
12 Gemma4-12B
Google
79.7%
02.07.2026 Report Verified
13 Qwen3.5-4B
Qwen
74.6%
01.02.2026 Report Verified
14 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
74.6%
01.02.2026 Report Unverified
15 Gemma4-E4B
Google
59.5%
02.07.2026 Report Verified
16 Gemma4-E2B
Google
52.4%
02.07.2026 Report Verified
17 LFM3-VL-2B
LiquidAI
51.6%
— Report Verified
18 Gemma3-27B
Google
46%
02.07.2026 Report Unverified

What now?

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