Cheetah Hunt in Golden Savanna at Sunset

A 10-second National Geographic-style wildlife sequence shot with 800mm telephoto and 120fps high-speed tracking. It follows a crouching cheetah from a hidden close-up of its eyes through a full-speed sprint to a dust-clouded turn dissolving into sunset backlight.

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John @johnAGI168 ·
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Prompt

【风格】国家地理非洲野生动物纪录片(National Geographic African Wildlife),4K超清,超长焦摄影(800mm Telephoto),高速追踪车拍摄(Tracking Vehicle 120fps),东非大草原黄金时刻光线
【时长】10秒
【场景】黄昏的东非稀树草原,金黄色的枯草齐腰高,天际线是一棵巨大的金合欢树剪影,夕阳低悬在地平线上将整个草原染成深金色,地面热浪扭曲远景
[00:00-00:04] 镜头1:草丛中的眼睛(Telephoto Close-Up 800mm, Shallow DOF)
超长焦浅景深特写:金黄色草丛占满画面,完全看不到任何动物。突然草丛缝隙中露出一双琥珀色的眼睛——一头母猎豹趴伏在草中,只有眼睛到耳尖的部分露出草尖。面部的黑色泪痕纹路从眼角延伸到嘴角,鼻头是粗糙的黑色皮革质感。瞳孔猛然收缩成一条竖线——锁定猎物。耳朵微微向后压平贴紧头骨。前景和背景的草丛虚化成金色光斑,只有猎豹的双眼锐利清晰。
[00:04-00:07] 镜头2:全速爆发(High-Speed Tracking 120fps, Side Profile)
侧面高速跟拍:猎豹从草丛中弹射而出进入全速冲刺,时速一百公里。升格慢动作下脊椎像弹簧一样极致弯曲再完全伸展——弯曲时后腿超过前腿,伸展时身体拉成一条水平线四肢全部离地腾空。每一步蹬地的瞬间爪垫下的干草和红土被踢成扇形飞散。腹部的白色短毛随奔跑节奏波浪起伏,尾巴像舵一样在高速转向时甩向一侧维持平衡。面部肌肉紧绷,嘴微张露出犬齿,鼻孔极度扩张。
[00:07-00:10] 镜头3:尘土中的结局(Super Slow-mo, Head-On Tracking)
正面超慢镜迎面跟拍:猎豹直冲镜头方向全速奔来,身后扬起一道三米高的金色尘土尾迹。它猛然侧身急转——四只爪同时在地面刨出四道土痕,身体几乎侧翻到与地面平行,尾巴甩成反方向的弧线。急转瞬间扬起的尘土形成一堵弧形的金色土墙,夕阳逆光穿透土墙将尘粒一颗颗照亮成悬浮的金色星尘。猎豹从尘墙中冲出的剪影渐渐消融在夕阳金光中。
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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
"tracking" is a core cinematic camera technique for establishing spatial immersion and subject framing. Also present: "close-up", "wide shot", "slow motion".
LIGHTING
"golden hour, backlight, silhouette" establishes luminance depth, volumetric shadow falloff, and tonal contrast across the generation.
MOOD
"dramatic, epic" — Mood and aesthetic tone are explicitly directed to maintain emotional consistency throughout the scene.
DURATION
At 10s, 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.
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