AVTrace - Cat5 Cross-modal Localization - Text F1: leaderboard

AVTrace Cat5: Conditional cross-modal localization, measured by Text F1 (0–1) over 1,000 test questions. Five off-the-shelf omni-model runs use greedy decoding with 512 new tokens; source-native interfaces expose full clips, sampled frames/audio, or only 30 seconds depending on the model. A reference-blind Qwen3.5-27B normalizes answers before deterministic scoring against partly model-assisted silver references. Invalid answers receive zero; exact checkpoint revisions remain unreported.

Metric: Text F1 (0–1). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 5 models tracked.

Top models

#ModelScoreOverall rank
1Qwen3-Omni-30B (AVTrace Run: paper v1 off-the-shelf; full clips via native interface; greedy 512 tokens; exact checkpoint unreported)0.45
2MiniCPM-o-4.5 (AVTrace Run: paper v1 off-the-shelf; full clips via native interface; greedy 512 tokens; exact checkpoint unreported)0.36
3InteractiveOmni-4B (AVTrace Run: paper v1 off-the-shelf; first 30 seconds; greedy 512 tokens; exact checkpoint unreported)0.35
4gemma-4-E4B-it (AVTrace Run: paper v1 off-the-shelf; first 30 seconds; greedy 512 tokens; exact checkpoint unreported)0.32
5Qwen2.5-Omni-3B (AVTrace Run: paper v1 off-the-shelf; up to 300 uniform frames and 300-second audio window; greedy 512 tokens; exact checkpoint unreported)0.23

Interactive version: theaggregate.ai/benchmark?slug=avtrace-cat5-cross-modal-localization-text-f1 · How It Works · Data refreshed daily, snapshot 2026-11-05.