Benchmark Almanac

DPG-Bench

Fading

Text-to-image models draw 1,000 dense prompts with many objects, attributes and relations. A VQA model checks each element of the prompt graph in the image.

Filed under the generation subcategory used for GenEval. The overall score averages over prompt elements.

Released
March 2024
Kind
Image generation and editing
Level
Everyday
Scored
Graded by a model
Answers
Open-ended
Tasks
All public
Last in a launch post
January 2026, dropped before it saturated
Last model added
January 2026
1
Model scored in lab cards
2
Launch posts list it, from 2 labs
2
System cards report it, from 2 labs

Janus-Pro-7B leads with 84.2%

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

  1. 1 Janus-Pro-7B 84.2%

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 Janus-Pro-7B 84.2% Jan 2025 Lab model card

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card
0% 20% 40% 60% 80% 100% 2025 Near the ceiling (85%) Janus-Pro-7B 0% 20% 40% 60% 80% 100% 2025 Near the ceiling (85%) Janus-Pro-7B

Source: Labs’ model cards

Labs headline it less often now, last in January 2026

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

DeepSeek
Z.ai
DateLaunch postScoreAs the post writes it
Jan 14, 2026 GLM-Image 84.8 DPG-Bench overall 84.78
Jan 27, 2025 Janus-Pro-7B 84.2 DPG-Bench Overall

2 system cards report it, from 2 labs

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
Jan 14, 2026 GLM-Image model card 84.8 DPG-Bench overall 84.78 Capabilities
Jan 27, 2025 Janus-Pro-7B technical report 84.2 DPG-Bench Overall (Table 5) Capabilities

More in Vision

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  • ChartQA In use Models answer human-written and generated questions about chart images that need visual and arithmetic reasoning. Scored by relaxed accuracy with a 5 percent numeric tolerance. Command A Vision 90.9%