C3-Bench - Relevance: leaderboard

C3-Bench (2026) evaluates context-aware change captioning: describing what changed between two images according to criteria that differ across 51 real-world change contexts. This board is relevance (0 to 10), whether the caption covers the changes the context asks for and ignores the rest, scored by a GPT-5.2 judge over 4,996 human-labelled image pairs and averaged over three judge runs. Higher is better.

Metric: Relevance (the caption covers the changes the context asks for and ignores the rest) (0-10) of change captions on the 4,996 human-labelled C3-Bench image pairs (51 change contexts across natural scenes, remote sensing, image editing and anomalies), scored by a GPT-5.2 judge against the reference description with the context-specific change criteria; mean of three judge runs; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 26 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.25.98#176
2GPT-5.15.98#229
3Gemini 3 Pro5.95#137
4Gemini 3 Flash5.86#164
5Gemini 2.5 Pro5.85#266
6GPT-4o5.83#741
7Gemini 2.5 Flash5.69#453
8InternVL3-78B5.59#738
9Qwen 3 VL 32B Instruct5.58#585
10Qwen 3 VL 8B Instruct5.54#981
11InternVL3-38B5.46#903
12GPT-4o Mini5.23#1623
13Llama 4 Scout Instruct5.19#1543
14Qwen 2.5 VL 7B Instruct5.07#1833
15Qwen 2.5 VL 72B Instruct5.06#846

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

Interactive version: theaggregate.ai/benchmark?slug=c3-bench-relevance · How It Works · Data refreshed daily, snapshot 2026-11-13.