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Alibaba ATH Happy Horse 1.1 integration

Happy Horse 1.1 is the latest iteration of Alibaba ATH’s flagship video model, delivering state-of-the-art motion fidelity, prompt adherence, and visual quality, now with 9 aspect ratios for text-to-video.
Happy Horse 1.1 Text-to-Video is an AI video generation API that creates MP4 videos from text descriptions. Built by Alibaba ATH (Taotian Innovation Unit, led by Zhang Di), it produces high-fidelity video with cinematic motion at 720P (1280x720) or 1080P (1920x1080) resolution, supports 9 configurable aspect ratios, and durations from 3 to 15 seconds.

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Key capabilities

  • State-of-the-art quality: Latest iteration of the Alibaba ATH Happy Horse video family
  • Resolution options: 720P (1280x720) and 1080P (1920x1080) output
  • 9 aspect ratios: 16:9, 9:16, 1:1, 4:3, 3:4, 21:9, 9:21, 5:4, 4:5
  • Flexible durations: 3 to 15 seconds of video output (default 5 seconds)
  • Multilingual prompts: Up to 2500 characters describing scene, motion, and style
  • Reproducible results: Fixed seed support (0 to 2147483647) for consistent generation
  • Async processing: Webhook notifications or polling for task completion

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Use cases

  • Marketing videos: Create product showcases and brand content from text descriptions
  • Social media content: Generate short-form videos for TikTok, Instagram, and YouTube in portrait or landscape
  • Concept visualization: Transform ideas and scripts into motion for rapid prototyping
  • Educational content: Illustrate concepts with AI-generated video explanations
  • Storyboarding: Pre-visualize scenes from a script before live production
  • Creative exploration: Experiment with text prompts and aspect ratios for unique visual content

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API operations

Generate videos by submitting a text prompt to the API. The service returns a task ID for async polling or webhook notification.

POST /v1/ai/text-to-video/happy-horse-1-1

Create a new text-to-video generation task

GET /v1/ai/text-to-video/happy-horse-1-1

List all Happy Horse 1.1 T2V tasks with status

GET /v1/ai/text-to-video/happy-horse-1-1/{task-id}

Get task status and results by ID

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Parameters

When the task completes, the generated MP4 video URL is returned in data.generated. The URL is valid for 24 hours — download and persist it to permanent storage immediately.

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Frequently Asked Questions

Happy Horse 1.1 is an AI video generation model developed by Alibaba ATH (Taotian Innovation Unit), led by Zhang Di. It is the latest iteration of the Happy Horse video family and generates high-fidelity MP4 video from text prompts.
Submit a text prompt describing your desired video, receive a task ID immediately, then poll the GET endpoint or wait for a webhook notification when processing completes. The model generates an MP4 video at 720P or 1080P resolution in durations from 3 to 15 seconds.
Happy Horse 1.1 T2V supports 9 aspect ratios: 16:9, 9:16, 1:1, 4:3, 3:4, 21:9, 9:21, 5:4, and 4:5. The default is 16:9.
Happy Horse 1.1 T2V supports integer durations from 3 to 15 seconds. The default is 5 seconds. Allowed values: 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15.
Processing time depends on resolution, duration, and server load. Higher resolution (1080P) and longer durations take more time. For production workflows, use webhooks instead of polling for scalable integration.
Rate limits depend on your subscription tier. See the Rate Limits page for current limits by plan.
See the Pricing page for current rates and subscription options.
Both are Alibaba ATH video models. Happy Horse 1.1 is the newer iteration and expands text-to-video and reference-to-video to 9 aspect ratios (16:9, 9:16, 1:1, 4:3, 3:4, 21:9, 9:21, 5:4, 4:5) versus 5 in 1.0. Choose Happy Horse 1.1 for the latest quality and wider aspect ratio coverage.

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Best practices

  • Prompt writing: Be specific about scenes, characters, camera movements (zoom, pan, tilt), lighting, and atmosphere. Detailed prompts produce better results than vague descriptions.
  • Duration selection: Start with shorter durations (3-5 seconds) for quick iterations, then increase for final outputs.
  • Reproducibility: Save the seed value from successful generations to recreate similar results with the same parameters.
  • Production integration: Use webhooks for scalable applications instead of polling.
  • Error handling: Implement retry with exponential backoff for 503 errors during high-demand periods.