Auto86%Harbor: pendingMultimodal

Meta-Video

Meta-Video: Efficient Standardized Evaluation for Video Understanding

A balanced 1,000-question benchmark over 791 videos for efficient video understanding evaluation, preserving model rankings with 5x speedup.

How to run

ltb · meta-video
$ npm i -g lettokenburn-cli
$ ltb bench info meta-video

External harness. No Harbor adapter has been generated for this benchmark yet. `ltb bench info` prints the known links.

Runs happen on your machine with your own subscription; only the score summary is pushed. CLI docs

Scores

5 sourced entries
HarnessSourceConfidenceLink
Qwen3-VL-8B-Instruct58.9N/AIndependentmediumOct 13, 2026arxiv.org
Qwen3-VL-4B55.3N/AIndependentmediumOct 13, 2026arxiv.org
InternVL3.5-8B-Instruct52.3N/AIndependentmediumOct 13, 2026arxiv.org
InternVL3.5-4B44.6N/AIndependentmediumOct 13, 2026arxiv.org
Qwen2.5-VL-7B40.6N/AIndependentmediumOct 13, 2026arxiv.org

Every number links to where it was published. Low-confidence rows are muted and need per-cell verification.

Reproduced by the community

All runs
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About

Meta-Video curates 1,000 QA pairs from 791 videos across diverse tasks, filtering out questions solvable without visual input to ensure discriminability. It establishes a standardized evaluation protocol by isolating configuration choices like frame sampling and input formatting that cause significant score variance.

The benchmark preserves model rankings of source suites while requiring one-fifth of the inference compute for full frame-count sweeps. Reference scores are released for five models, demonstrating that unexamined evaluation defaults can shift accuracy by up to 19.5 percentage points.