MM-CondChain: leaderboard

Metric: Path F1 (%), the harmonic mean of True-path accuracy (follow every condition to the final answer) and False-path accuracy (stop at the perturbed condition and pick its auxiliary answer), averaged over the Natural, Chart and GUI domains; zero-shot multiple choice with a boxed answer, unparseable outputs wrong; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 27 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Pro53.33#77
2GPT-550.34#91
3Gemini 3 Flash48.31#93
4Qwen 3 VL 235B A22B (Thinking)46.83#228 (Qwen 3 VL 235B A22B)
5Qwen 3.5 397B A17B45.9#141
6Qwen 3 VL 235B A22B Instruct45.45#264
7Kimi K2.545.25#139
8Gemini 2.5 Pro40.91#145
9Qwen 3 VL 30B A3B (Thinking)40.4#338 (Qwen 3 VL 30B A3B)
10Qwen 3.5 122B A10B40.12#170
11Qwen 3 VL 8B (Thinking)38.25
12GLM-4.6V36.99#309
13Qwen 3 VL 8B Instruct32.65#401
14Gemini 2.5 Flash29.64#237
15Qwen 3.5 9B28.62#363

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=mm-condchain · How It Works · Data refreshed daily, snapshot 2026-10-11.