VDEBench
Image editing models make local text and table edits to 3,506 Chinese and English document images. Scores check the edit and that the rest of the page is preserved.
Added to Hugging Face's official benchmark list in October 2026.
- Made by
- Yi et al. (VDE-Bench authors)
- Released
- January 2026
- Kind
- Documents, charts and text in images
- Level
- Everyday
- Scored
- Checked automatically
- Answers
- Open-ended
- Tasks
- All public
- Last model added
- September 2025
- Scores refreshed
- November 12th, 2026
In the authors’ words
Image editing models can modify visual content through natural language, but editing dense documents requires precise local changes amid tightly coupled text, tables, and layout. We introduce VDE Bench, an evaluation resource for studying instruction-guided editing of Chinese and English document images. VDE Bench contains 3,506 instruction-guided image editing samples, including 1,578 text-region edits and 1,928 table-region edits. The benchmark pairs editing instructions and reference images with annotated editing regions and structured OCR outputs. Its evaluation protocol combines region-level and full-page measurements to assess textual correctness, structural fidelity, and visual content preservation. By focusing on the interaction between local edits and their surrounding document context, VDE Bench complements existing visual text editing benchmarks and provides a resource for diagnosing document-specific editing failures.
FLUX.2 [klein] 4B leads with 0.77 among models released by September 2025
Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.
The newest model with a score here came out in September 2025, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon - GPT-6 Astra
- Claude Opus 5.5
- and 16 more
- 1 FLUX.2 [klein] 4B 0.77
- 2
BAGEL-7B-MoT 0.71 - 3
Qwen-Image-Edit (2511) 0.66 - 4 FireRed-Image-Edit-1.1 0.64
- 5 Qwen-Image-Edit-2509 0.62
- 6 OmniGen2 0.56
Source: Official VDEBench leaderboard
| # | Entry | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | FLUX.2 [klein] 4B | 0.77 | Official leaderboard | ||
| 2 | BAGEL-7B-MoT | 0.71 | May 2025 | Official leaderboard | |
| 3 | Qwen-Image-Edit (2511) | 0.66 | Official leaderboard | ||
| 4 | FireRed-Image-Edit-1.1 | 0.64 | Official leaderboard | ||
| 5 | Qwen-Image-Edit-2509 | 0.62 | Sep 2025 | Official leaderboard | |
| 6 | OmniGen2 | 0.56 | Official leaderboard |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Official VDEBench leaderboard
No lab model card reports it yet
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.
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