C3-Bench - Correctness: 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 correctness (0 to 10), how closely the caption matches the reference change, scored by a GPT-5.2 judge over 4,996 human-labelled image pairs and averaged over three judge runs. Higher is better.

Metric: Correctness (how closely the caption matches the reference change) (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 May 2027. 26 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.25.47#176
2Gemini 3 Pro5.45#137
3GPT-5.15.43#229
4Gemini 3 Flash5.42#164
5Gemini 2.5 Pro5.18#266
6Qwen 3 VL 32B Instruct5.18#585
7Qwen 3 VL 8B Instruct5.07#981
8Gemini 2.5 Flash4.99#453
9GPT-4o4.95#741
10GPT-5 Mini4.87#348
11InternVL3-78B4.86#738
12InternVL3-38B4.72#903
13Llama 4 Scout Instruct4.63#1543
14GPT-4o Mini4.56#1623
15Qwen 2.5 VL 72B Instruct4.54#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-correctness · How It Works · Data refreshed daily, snapshot 2026-11-13.