TAR-Bench - Temporal Localization: leaderboard

TAR-Bench (2026) evaluates vision-language models on 960 human-curated questions about 80 held-out traffic-anomaly clips, zero-shot and without reasoning mode. The Temporal Localization task covers the predicted anomaly interval against the annotated interval. Score is mean IoU, in percent; higher is better.

Metric: Mean IoU (%; the predicted anomaly interval against the annotated interval; zero-shot in non-reasoning (direct-answer) mode through VLMEvalKit, mean of 3 runs, on TAR-Bench: 960 human-curated annotations for 80 held-out traffic-anomaly clips from 17 public YouTube videos). Source: arxiv.org. Saturation forecast: Around 2029. 11 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)32.2#94
2Qwen 3.5 27B (Non-reasoning)26.7#359 (Qwen 3.5 27B)
3Qwen 3 VL 8B Instruct25.1#981
4Gemma 4 31B (IT)22.3#342
5Qwen 3 VL 32B Instruct21.1#585
6Qwen 3.5 9B (Non-reasoning)20.4#803 (Qwen 3.5 9B)

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

Interactive version: theaggregate.ai/benchmark?slug=tar-bench-temporal-localization · How It Works · Data refreshed daily, snapshot 2026-11-13.