Independent AI Image & Video Benchmarks for Japan
We test image and video generation models on real Japan-market production tasks—using the same inputs, multiple runs, and human review—to measure usability, reroll cost, and Japan-specific failure patterns.
Models
11
Active image & video models benchmarked
3-Run cases
6
Same model, same prompt, 3 completed generation attempts
Comparisons
263
Public generation runs evaluated
Video models
Compare Seedance, Kling, Veo and more on Japanese business scenes, short-form social media ads, store PR and real-estate before-and-after visuals.
Image models
Compare GPT Image, FLUX, NanoBanana and others for e-commerce product imagery, business portraits, characters and backgrounds.
Production-first scoring
Human reviewers evaluate prompt adherence, consistency, motion quality and temporal stability — and report commercial usability separately for context.
For overseas teams
Market intelligence and research for AI companies, investors and production teams entering Japan.
Featured 3-model comparison
ラーメンを食べる人物 I2V 動画比較｜飲食・食品広告で使えるモデルは？ — 4モデル・12Run・8秒
What breaks in Japan
Failure patterns we look for when testing image and video models on Japan-market prompts.
Hands & faces
Distorted hands, unnatural expressions, and inconsistent skin tones.
Japanese text
Garbled characters on signs, menus, packaging and documents.
Camera drift
Video models ignore static-camera or no-movement instructions.
Cultural details
Food, clothing and settings that miss regional authenticity.
Research and benchmark production for Japan
Independent practical evaluation, model localization assessment and side-by-side benchmark production for AI companies, investors and production teams entering Japan.
Japan-market model verificationSponsored benchmark productionLocalization assessment