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language benchmark

VATEX

VaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research. Contains over 41,250 videos and 825,000 captions in both English and Chinese, with over 206,000 English-Chinese parallel translation pairs. Supports multilingual video captioning and video-guided machine translation tasks.

Updated Aug 11, 2026

Models2
Model coverage2
MetricScore
EvidenceB

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VATEX Ranking

Higher score ranks better on this benchmark.

2 rows
Columns

Show columns

01AMNova LiteAmazon77.8%100.0%2CAug 11, 2026
02AMNova ProAmazon77.8%0.0%2CAug 11, 2026

VATEX Score Distribution

A closer view of the leading scores on this benchmark.

VATEX

VATEX Highlights

The leading models and scores on this benchmark.

Rank #1Nova Lite77.8%Rank #2Nova Pro77.8%

What is VATEX?

What VATEX measures and how its scores work.

VaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research. Contains over 41,250 videos and 825,000 captions in both English and Chinese, with over 206,000 English-Chinese parallel translation pairs. Supports multilingual video captioning and video-guided machine translation tasks.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
VATEX
Modality
multimodal
Primary category
language
Score direction
higher
LLMBoard eligible
No
Evaluation key
vatex|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about VATEX.

Which model scores highest on VATEX?

Nova Lite is currently ranked first with 77.8%.

What does VATEX measure?

VaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research. Contains over 41,250 videos and 825,000 captions in both English and Chinese, with over 206,000 English-Chinese parallel translation pairs. Supports multilingual video captioning and video-guided machine translation tasks.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

2 model results are currently shown.

Does this benchmark affect the overall score?

No. This benchmark is shown for reference but does not contribute to the overall score.