VS-Bench (VisualSwap) - MathVision: leaderboard

VS-Bench (Shi et al., 2026) probe accuracy on the 200 image pairs built from competition mathematics problems from MathVision: after reasoning about an edited image, the model is shown the original image mid-response with a self-reflection prompt and must answer for the image now in front of it. Accuracy in percent; higher is better.

Metric: Probe accuracy (%; 200 image pairs sourced from MathVision: answer on the swapped image after a self-reflection prompt). Source: arxiv.org. Saturation forecast: Around February 2027. 15 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3 VL 32B Instruct43.5#582
2Qwen 3 VL 235B A22B Instruct40.5#521
3Qwen 3 VL 32B (Thinking)32#557
4Qwen 3 VL 8B Instruct31#982
5Qwen 3 VL 235B A22B (Thinking)31#451
6Qwen 3 VL 30B A3B Instruct29.5#870
7Qwen 3 VL 8B (Thinking)27#887
8Qwen 3 VL 30B A3B (Thinking)24.5#710
9Qwen 2.5 VL 7B Instruct15.5#1842

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

Interactive version: theaggregate.ai/benchmark?slug=vs-bench-visualswap-mathvision · How It Works · Data refreshed daily, snapshot 2026-11-12.