1080p Output
HappyHorse 1.0 targets 1080p clips in standard 16:9 and 9:16 formats, with an emphasis on physical coherence and cleaner temporal consistency.
Coming Soon
HappyHorse 1.0 brings cinematic video and synchronized audio into one forward pass.
Built around unified text-to-video and image-to-video generation, HappyHorse 1.0 functions as an open-source video generation model for 1080p motion, dialogue, ambience, and Foley without the usual multi-stage dubbing pipeline.
Pending full integration, this preview highlights the upcoming support for native audio alignment, physical coherence, multilingual lip-sync, and a faster sampling path for short clips.
Text to Video and Image to Video1080p cinematic outputDialogue, ambience, and Foley in one pass7-language native lip-sync8 denoising stepsComing Soon on AuraTuner
Resolution
Up to 1080p
Modes
Text to Video, Image to Video
Audio
Native synchronized output
Lip-Sync
7 supported languages
Sampling
8 denoising steps
Status
Coming Soon
WHY IT STANDS OUT
A video model shaped around one-pass audiovisual generation.
Most open video stacks still depend on multiple systems for silent video, dubbing, and lip-sync repair. HappyHorse 1.0 is a native joint model instead, where sound and motion are learned in the same generation sequence.
Native Joint Audio-Video Generation
Video tokens and audio tokens are denoised in one unified sequence, so dialogue timing, ambient sound, footsteps, and cut-driven sound changes are learned together instead of stitched together afterward.
7-Language Native Lip-Sync
English, Mandarin, Cantonese, Japanese, Korean, German, and French are described as part of the same generation process, with speech timing aligned to visible mouth motion.
Fast 1080p Inference
DMD-2 reduces the sampling loop to 8 denoising steps. Benchmark runtime expects around 38 seconds for a 5-second 1080p clip on a single H100, with faster lower-resolution previews.
Unified Text-to-Video and Image-to-Video
One model family handles prompt-first creation and reference-led animation without switching weight sets, helping style, identity, and physical realism stay consistent across both workflows.
Open-Source Model Direction
HappyHorse 1.0 operates as an open-source, open-weights video model designed to avoid the usual silent-video then dubbing then lip-sync pipeline.
Not For Production Runs Yet
HappyHorse 1.0 is a coming-soon preview in AuraTuner. Do not plan live campaigns around it until the model is available in the editor with real cost, latency, and output behavior.
AURATUNER PREVIEW
Stay Tuned, Coming soon to the AuraTuner.
HappyHorse 1.0 is currently in preview. It will be integrated into the standard generation flows once cost, latency, and output behavior are fully benchmarked. Use our existing models in the meantime.
HappyHorse 1.0 FAQ
Common questions about HappyHorse 1.0 features and availability in AuraTuner.
What is HappyHorse 1.0 in AuraTuner?
HappyHorse 1.0 is presented as a coming-soon AI video model page in AuraTuner. The current page is a preview landing page, not a live generation workflow inside the product.
Does HappyHorse 1.0 support text to video and image to video?
Yes. The landing page positions HappyHorse 1.0 around unified text-to-video and image-to-video generation with one model family rather than separate workflows.
What makes HappyHorse 1.0 different from other open video models?
The main differentiator described on the page is native joint audio-video generation, where dialogue, ambient sound, Foley, and video are generated together instead of using a silent-video-first pipeline followed by dubbing and lip-sync repair.
What output quality and speed does the page describe?
The page describes up to 1080p output, standard 16:9 and 9:16 formats, and an 8-step denoising path positioned around roughly 38 seconds for a 5-second 1080p clip on a single H100.