multimodal benchmark
CrossVid Leaderboard
CrossVid evaluates models' ability to perform cross-video reasoning by integrating information across multiple videos.
Updated Sep 5, 2026
Models2
Model coverage2
MetricScore
EvidenceB
CrossVid Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelBY | Score65.00% | Percentile100.00% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelBY | Score63.20% | Percentile0.00% | Participants2 | EvidenceC | Evaluated |
CrossVid Highlights
The leading models and scores on this benchmark.
CrossVid Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for CrossVid
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What is CrossVid?
What CrossVid measures and how its scores work.
CrossVid is a multimodal benchmark for cross-video reasoning.
It measures performance on integrating information across multiple videos, reported as a Score in ratio units.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- CrossVid
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- overall
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about CrossVid.
Which model scores highest on CrossVid?
Seed 2.1 Pro is currently ranked first with 65.00%.
What are the top three models on CrossVid?
The current leaders are Seed 2.1 Pro (65.00%) and Seed 2.1 Turbo (63.20%).
Which CrossVid model has the lowest official input price?
No matched official input price is currently available.
Which models are fastest among CrossVid results?
No matched runtime record is currently available.
Does the highest score result prove overall model quality?
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.