FailBench - phail: leaderboard

FailBench evaluates video-language models and specialist detectors judging robot task success across real and simulated robot videos under a shared prompt, input and decoding recipe. Macro results average two-class datasets; the failure-only reflect subset uses failure recall. This series reports FailBench - phail from 2609.03611v1, S4.T2: Balanced Accuracy (%). Higher is better.

Metric: Balanced Accuracy (%). Source: arxiv.org. Saturation forecast: Around February 2027. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash89#105
2Qwen 3 VL 8B (Thinking)77#423
3GPT-4o67#358
4Gemma 4 31B (IT)67#180
5Qwen 3 VL 4B (Thinking)63#546

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #6 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=failbench-phail · How It Works · Data refreshed daily, snapshot 2026-11-07.