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anime sports Seedance 2.0 prompt

Two Anime Characters Perform a Combined Ultimate Attack

A Japanese full-color anime prompt depicting a climactic team-up special move between two characters. It uses dynamic handheld camera work, extreme dolly-ins, double exposure, and 2x/4x speed ramps with dramatic lighting and rapid cuts between extreme close-ups and extreme long shots.

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FinishFish | AI Anime @finishfish_ai · Original post: Sep 2, 2026

Prompt

[@キャラA]と[@キャラB]の連携必殺技。ダイナミックなカメラワーク、ドラマチックショット、手持ちカメラ、急激な画面奥へのエクストリームドリーイン、二重露光、二倍速、四倍速、必殺技にあったライティング処理、過剰に派手な必殺技の演出、日本のフルカラーアニメ、カット割、セリフなし、エクストリームクローズアップとエクストリームロングショットの連続、ライティング処理、高画質、1000万ドルの大作映画アニメ、クライマックスシーン、全シリーズで一度しか使われなかった最高の大技。

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Copy the prompt using the green "Copy prompt" button above.
Open your model — launch Seedance 2.0 on its official interface.
Paste & generate — keep the verbatim prompt text for best adherence. Set aspect ratio to 16:9 and clip duration to 15s.

Spec sheet

Duration	15s
Camera	dolly · handheld · close-up · wide shot
Lighting	dramatic lighting · cinematic lighting
Mood	epic · dramatic
Aspect ratio	16:9
Difficulty	intermediate
Model	Seedance 2.0
Prompt language	Chinese
Includes	Not specified

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What makes this prompt work

Every insight below is verified against benchmark generation parameters, not asserted. How our prompt engineering benchmarks work →

CAMERA: "dolly" is a core cinematic camera technique for establishing spatial immersion and subject framing. Also present: "handheld", "close-up", "wide shot".
LIGHTING: "dramatic lighting, cinematic lighting" establishes luminance depth, volumetric shadow falloff, and tonal contrast across the generation.
MOOD: "epic, dramatic" — Mood and aesthetic tone are explicitly directed to maintain emotional consistency throughout the scene.
DURATION: At 15s, this clip is optimized for high temporal coherence and fluid, realistic motion physics.
MODEL: Seedance 2.0 (ByteDance) provides the underlying diffusion and motion architecture. Camera, lighting and duration cues transfer across models — what differs is how literally each model interprets motion.
PROMPT LANGUAGE: The prompt is written in Chinese. This library keeps every prompt in its original language rather than translating it — the exact words are what was conditioned during generation.