CARV - Union (Different Source): leaderboard
Metric: Accuracy (%) on 500 CARV visual analogy tasks (controlled scenes of everyday items and furniture, edited with Gemini-2.5 Flash Image; the model writes a caption of the answer image, and a GPT-4o evaluator checks it against the ground-truth image), direct prompting: apply the union of the transformations of two image pairs whose sources and query all differ; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 13 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5.1 | 51 | #131 |
| 2 | Gemini 2.5 Pro | 40.4 | #145 |
| 3 | Gemini 2.5 Flash | 37.4 | #237 |
| 4 | Qwen 3 VL 8B (Thinking) | 20.8 | |
| 5 | GPT-4o | 9 | #333 |
| 6 | Qwen 2.5 VL 32B Instruct | 6.2 | #443 |
| 7 | Qwen 3 VL 30B A3B Instruct | 4.2 | #365 |
| 8 | Qwen 2.5 VL 7B Instruct | 2.2 | #643 |
| 9 | Qwen 3 VL 8B Instruct | 0.6 | #401 |
| 10 | InternVL3-8B | 0.2 | #606 |
| 11 | InternVL3-14B | 0 | #494 |
No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.
Interactive version: theaggregate.ai/benchmark?slug=carv-union-different-source · How It Works · Data refreshed daily, snapshot 2026-10-11.