Video-MemComp OVO Allocation Weights - HLD: leaderboard

Video-MemComp v1: streaming evaluation of official development sets. Table 1 mixes reproduced starred rows and results from prior papers; frame sampling and average KV budget differ by system and remain in row identity. Backbone checkpoint revision and decoding are not fully specified; source-qualified systems are retained. This is video QA under cache compression, not an unmodified backbone score. Appendix F identifies Qwen2.5-VL-7B on OVO. These are distinct hyperparameter arms evaluated on the same questions, not independently sampled tasks; preserve every configuration. HLD. Metric: Accuracy (%).

Metric: Accuracy (%). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 27 models tracked.

Top models

#ModelScoreOverall rank
1Video-MemComp Qwen2.5-VL-7B Allocation Weights [0.30, 0.675, 0.025]36.56
2Video-MemComp Qwen2.5-VL-7B Allocation Weights [0.35, 0.625, 0.025]35.48
3Video-MemComp Qwen2.5-VL-7B Allocation Weights [0.00, 0.00, 1.00]34.95
4Video-MemComp Qwen2.5-VL-7B Allocation Weights [0.275, 0.675, 0.05]34.95
5Video-MemComp Qwen2.5-VL-7B Allocation Weights [0.60, 0.10, 0.30]34.95
6Video-MemComp Qwen2.5-VL-7B Allocation Weights [1.00, 0.00, 0.00]34.95
7Video-MemComp Qwen2.5-VL-7B Allocation Weights [0.50, 0.40, 0.10]34.41
8Video-MemComp Qwen2.5-VL-7B Allocation Weights [0.60, 0.05, 0.35]34.41
9Video-MemComp Qwen2.5-VL-7B Allocation Weights [0.675, 0.275, 0.05]34.41
10Video-MemComp Qwen2.5-VL-7B Allocation Weights [0.70, 0.25, 0.05]34.41

Interactive version: theaggregate.ai/benchmark?slug=video-memcomp-ovo-allocation-weights-hld · How It Works · Data refreshed daily, snapshot 2026-10-27.