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Yevideo Inspiration
Alibaba ATH · Happy Horse 1.0
Happy Horse 1.0: A next-gen AI video model strong at both text and image to video
Happy Horse 1.0 is developed by Alibaba’s ATH team and is among the most watched new video models in 2026. On the public Artificial Analysis Video Arena benchmarks, its text-to-video and image-to-video scores rank near the top in the no-audio category, and stay in the first tier with audio as well. Beyond generation, it supports multi-image reference guidance, editing existing clips, native 1080p, multi-shot storytelling, audio output, and multilingual prompts. On Yevideo, one workbench lets you run all four pipelines—from quick concept tests to presentable 1080p samples.
Expressive faces: eyes, mouth, and emotion that actually perform
Many AI videos fail in close-ups—stiff faces, dead eyes, emotions that feel pasted on. Happy Horse 1.0 puts more effort into facial performance in text-to-video: micro-expressions, gaze direction, lip corners, and brow tension stay coherent in motion, closer to real acting than a “moving mask.” In prompts, spell out emotional layers (restraint, surprise, bitter smile, release after tension) and shot distance (close-up for eyes, medium for body). You get subtler, more believable faces for dialogue scenes, emotional shorts, and ads where the audience must read the face.
- Strong for close-ups, dialogue, emotional story beats, and brand films where faces must read clearly
- Describe emotion and expression (eyes, mouth, breath)—not just “beautiful”
Fluid motion and believable physics
Happy Horse 1.0 image-to-video is not about “anything moving”—it’s about moving smoothly and plausibly. Turns, steps, and gestures connect with fewer pops and joint breaks; falls, collisions, splashes, and fabric respect gravity, inertia, and contact more often. The model keeps your reference look while making action feel natural.
- Temporal coherence: complex action with less stutter and frame-to-frame jerk
- Physics you can trust: gravity, inertia, contact; less float and interpenetration for liquids, cloth, and rigid bodies
- Reference look preserved: describe motion and camera, not what the image already shows
Bring image-to-video to life with Happy Horse 1.0
Happy Horse 1.0 turns still visuals into playable motion while keeping the original image at the center—composition, mood, and subject silhouette stay anchored. The goal is to animate the frame, not replace it with a different picture. Portraits, product heroes, and stylized posters gain attention with thoughtful motion and camera work—ideal when you must keep the source visual and ship video-first content. Upload a first frame on Yevideo, choose 720p or 1080p and aspect ratio, and extend strong key art into motion samples fast.
- The source image stays hero: motion and camera change—not a swap of face or product
- Great for portraits, e-commerce heroes, brand KV, and locked IP looks
- Prompt for direction, amplitude, and rhythm—avoid repeating what’s already in the frame
Multi-image reference + multilingual: control characters with character1/2…
When one image cannot carry your IP or brand bible, upload 1–9 references and map them with character1, character2, and so on in prompt order. Outputs align better with intended casting, wardrobe, and scene direction. Use clear assets (720p+, short side ≥400px). Prompts work in Chinese, English, and more—handy for cross-border ads, regional short-form variants, and global product demos from one visual system.
- Multi-image reference suits IP series, campaigns, and unified worlds
- Mixed-language prompts are fine—keep subject and action references consistent
- Lock appearance with references; use text for motion and camera
Text to video: from words to playable shots
No reference image required—generate 3–15 second clips from prompts. Ideal for story beats, visual exploration, marketing, and short-form when the idea is still text. Supports 720p / 1080p, multiple aspects, and audio options where enabled in the workbench.
- Prompt who / where / what / mood / how the camera moves
- Strong Arena text-to-video (no audio) scores—good for pitches and direction tests
- Start short and 720p; move to 1080p when the look is right
Image to video: one first frame, coherent motion
Upload a single first frame (JPEG / PNG / WebP). Happy Horse 1.0 adds motion while preserving the source look. Strong image-to-video Arena results—great for character animation, product shots, and stylized scenes when you need movement, not a new still.
- One first frame; clean subject edges help
- Describe motion direction, scale, and pace—don’t repeat the image
- 720p / 1080p, 3–15 seconds
Reference-to-video: 1–9 images guide character and style
Upload 1–9 references; use character1, character2… in prompt order for multi-character scenes, wardrobe, and set elements. More control than single-image mode when you must match brand boards, storyboards, or IP bibles.
- Reference order = character index—keep prompt labels aligned
- Prefer large, sharp images over tiny compressed files
- Clarify primary vs secondary action before pushing motion harder
Video edit: change what exists—don’t regenerate from scratch
Upload a 3–60 second reference clip and describe edits—background, lighting, local swaps, style tweaks. Happy Horse 1.0 editing keeps overall structure while you refine details, A/B variants, or extend ideas. Optional 0–5 reference images; audio strategies include auto and origin.
- Reference video: long side ≤2160px, short side ≥320px, fps >8
- One change class per pass (light / background / subject) for higher success
- Use origin to keep source audio; auto when the model should handle sound
Who is Happy Horse 1.0 best for?
If you need more than a “moving still”—structured, physically believable 1080p video you can pitch or publish—Happy Horse 1.0’s four pipelines fit: text-to-video for ideas, image-to-video for key art, multi-image reference for character lock, video edit for finishing.
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The shot is in your head—you can’t shoot it yet
Happy Horse 1.0 text-to-video lets you rehearse beats, emotion, and camera early. Strong Arena text scores help validate the story before live action or 3D spend.
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FAQ
What is Happy Horse 1.0? How is it related to Alibaba?
Happy Horse 1.0 is an AI video model from Alibaba’s ATH (Alibaba ATH) team, covering text-to-video, image-to-video, multi-image reference, and video editing. Yevideo integrates it so you can use it in the browser workbench without deploying your own API.
Why is Happy Horse 1.0 considered strong at text and image to video?
On public benchmarks such as Artificial Analysis Video Arena, Happy Horse 1.0 ranks among the leaders for text-to-video and image-to-video (no audio), and stays in the first tier with audio—competitive on both prompt-driven and image-driven paths. Results still depend on prompts, references, and shot complexity; test short clips in the workbench first.
Does Happy Horse 1.0 support audio and multiple languages?
Audio-related options are available per workbench settings; the video-edit pipeline supports strategies such as auto and origin. Prompts accept multiple languages including Chinese and English—useful for cross-border and regional short-form variants.
How should I choose between Happy Horse 1.0, Seedance 2.0, and Veo 3.1?
There is no universal winner—pick what fits the job. Happy Horse 1.0 leads on Arena text/image scores (no audio) and emphasizes stable motion, plausible physics, and 1080p multi-shot work. If you rely on another vendor’s native audio pipeline or existing toolchain, run parallel tests. A common workflow: same storyboard on Happy Horse 1.0 and an alternative, then choose by look and cost.
Which mode fits which use case?
Text-to-video: start from script or idea. Image-to-video: key visual is set—add motion. Multi-image reference: lock IP, brand, or storyboard with several references. Video edit: refine or vary an existing clip. All four are reachable from the Yevideo sidebar and mode switcher.
How is Happy Horse 1.0 priced on Yevideo?
Credits depend on model, resolution, and duration; estimates show before generation. Start with 720p and shorter clips to explore, then move to 1080p or longer outputs when satisfied.