Omni2Web - Direct Editing Grounding: leaderboard

The target-grounding component of Omni2Web direct editing (Han et al., 2026): the share of rubric items for which the edited page changes the element each step refers to, over 918 bilingual screen recordings of weakly referential web-editing requests, where speech, cursor movement and edit history identify the targets. Percent, judged by Gemini 3.1 Pro; higher is better.

Metric: Target-grounding rate (%; Track A rubric items: the edited HTML changes the element each active step refers to; 918 bilingual screen recordings of weakly referential webpage edit requests (speech plus cursor), 13,907 edit steps; the model edits the source HTML directly from the recording under its native input interface (omni: audio-visual video; vision-language: video or 1 fps frames plus manual transcript); rubric items judged by Gemini 3.1 Pro; unusable outputs score zero). Source: arxiv.org. Saturation forecast: Around February 2027. 15 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.5 Flash59.2#98
2GPT-5.6 Sol55.92#29
3Claude Opus 554.11#20
4Qwen 3.8 Max43.51#55
5Kimi K343.32#53
6Grok 4.642.52#44
7Seed 2.1 Pro37.54#133
8MiMo-V2.531.44#353
9MiniMax-M331.12#265
10Gemini 3.1 Pro (Preview)26.93#91
11Muse Spark 1.122.29#82
12Qwen 3.5 Omni Plus20.79#237
13Seed 2.0 Lite20.38#286
14Qwen 3.8 27B12.25#199

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=omni2web-direct-editing-grounding · How It Works · Data refreshed daily, snapshot 2026-11-12.