Multimodal Agents Benchmark

Chartography

Category

Multimodal Agents

Score type

percent

Scale

relative

higher is better

Models tested

3

What is Chartography?

Chartography is a benchmark for agents that perceive and act across visual interfaces. It was built to compare language models on a clearly defined set of tasks under the same grading rules, so scores are directly comparable between models.

What does it test?

Chartography measures agents that perceive and act across visual interfaces. In detail, it checks:

  • interpreting what is on screen and deciding what to do next
  • combining visual perception with tool or UI actions
  • completing multi-step tasks that require looking and acting alternately
  • recovering when a UI action does not produce the expected result

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.

Frequently asked questions

What is the Chartography benchmark?

Chartography is a benchmark for agents that perceive and act across visual interfaces. It was built to compare language models on a clearly defined set of tasks under the same grading rules, so scores are directly comparable between models.

What does Chartography test?

Chartography mainly measures agents that perceive and act across visual interfaces. Concretely, it checks: interpreting what is on screen and deciding what to do next; combining visual perception with tool or UI actions; completing multi-step tasks that require looking and acting alternately.

How is the Chartography 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 Chartography 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/chartography/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 3 models tested

Reset
# Model Score Date Source Verified
1 DeepSeek-V4.1-Flash-1017
DeepSeek
83%
17.10.2026 Report Verified
2 DeepSeek-V4.1-Flash
DeepSeek
78.9%
10.09.2026 Report Verified
3 DeepSeek-V4-Flash-Vision-Exp
DeepSeek
64.3%
08.09.2026 Report Verified

What now?

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