VisEditBench - Robustness and Generalization: leaderboard
VisEditBench (arXiv 2608.10408v1, Table 2): zero-shot visualization code editing pass rate on the 116 tasks with the Robustness / Generalization editing intent. A pass needs executable code, task accuracy of at least 4.5 of 5, readability and visual quality of 4.0 and visual similarity of 90 under a GPT-4o evaluator (Gemini 2.5 Pro for GPT-4o outputs). Percent; higher is better. Rows printed as 1.00, impossible at this example count, are omitted.
Metric: Pass rate (%). Source: arxiv.org. Saturation forecast: Around February 2027. 18 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Claude Sonnet 4.6 | 86.2 | #94 |
| 2 | Claude Sonnet 4.5 | 75 | #148 |
| 3 | GPT-5 Mini | 71.55 | #193 |
| 4 | GPT-4o | 57.76 | #357 |
| 5 | GPT-5 | 56.89 | #105 |
| 6 | Gemma 3 27B | 23.28 | #606 |
| 7 | Gemini 3 Flash | 9.48 | #103 |
| 8 | Gemma 3 12B | 6.89 | #674 |
| 9 | Pixtral-12B | 5.17 | #805 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=viseditbench-robustness-and-generalization · How It Works · Data refreshed daily, snapshot 2026-11-05.