Artificial Analysis 实测四款图像编辑模型连续 30 次编辑表现
We gave four frontier image editing models the same photo and 30 edits in a row: Ideogram 4.5 keeps most of the room intact, while the others drift, GPT Image 2
Artificial Analysis 让 GPT Image 2.5 Sunburst、Ideogram 4.5、FLUX 3 和 Nano Banana 2.1 对同一张照片连续执行 30 步房产布景编辑，测试多轮编辑一致性。结果显示 Ideogram 4.5 和 FLUX 3 采用局部编辑，在添加花瓶等小改动时 95% 以上画面基本不变；GPT Image 2.5 Sunburst 每次编辑都会重绘大部分画面，仅约五分之一保持不变，导致色彩和细节偏差逐轮累积；Nano Banana 2.1 介于两者之间，编辑保持局部但画面其余部分会轻微偏移并逐渐变暗。
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通过 30 步连续编辑实测，对比四款图像编辑模型的局部修改能力与画面漂移差异。
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We gave four frontier image editing models the same photo and 30 edits in a row: Ideogram 4.5 keeps most of the room intact, while the others drift, GPT Image 2.5 Sunburst most visibly.
We've seen some interesting demos of multi-turn editing consistency from the latest image editing models, so we ran our own test: GPT Image 2.5 Sunburst, #1 on our Image Editing leaderboard, against Ideogram 4.5, FLUX 3 and Nano Banana 2.1. Our leaderboard scores single edits; this tests what happens when 30 consecutive changes stack up, with each model editing its own previous output through a 30-step real estate staging sequence: light the fire, add a sofa, repaint the walls, swap day for twilight, and more.
Why are the final results so different?
@ideogram_ai's Ideogram 4.5 and @bfl_ml's FLUX 3 edit locally. On small edits like adding a vase of tulips, we measured that they left 95% or more of the image essentially untouched. GPT Image 2.5 (Sunburst) re-renders most of the entire image on every edit, leaving only about a fifth of the image unchanged, so small shifts in colour and detail compound over turns. Nano Banana 2.1 sits in between: its edits stay local, but the rest of the image shifts slightly and gradually darkens.