Research Prototype

Open Weights.
Cinematic Realism.
Happy Horse 1.0

Happy Horse Generator, powered by Happy Horse 1.0, is an open-source AI video generation model for text-to-video and image-to-video, combining synchronized audio, physical realism, and multilingual lip-sync in one system.

View Benchmark Rank Read Architecture

Top-Tier Performance

Based on thousands of human-rated blind comparisons from the Artificial Analysis Video Arena, Happy Horse 1.0 consistently leads global rankings for visual quality, physical realism, and prompt alignment across both Text-to-Video and Image-to-Video generation.

Peak Arena Score
1404 Globally #1

Global Leaderboard

Rank
Model
Arena Elo
1
HappyHorse HappyHorse-1.0
1365
2
ByteDance Dreamina Seedance 2.0
1273
3
Skywork SkyReels V4
1245
4
Kling AI Kling 3.0 1080p (Pro)
1243
5
xAI grok-imagine-video
1230

Technical Architecture

Developed and released in early 2026, Happy Horse 1.0 is built around a 40-layer self-attention Transformer architecture.

It is fully open source under commercial-use licensing. The release includes the base model, the 8-step distilled model, our proprietary super-resolution module, and optimized inference code — ready for native on-premise infrastructure.

40-Layer Core

Core Capabilities

Unified Transformer

40-layer self-attention network with robust single-stream processing and per-head gating for high-stability training scaling.

Joint Video & Audio

Generates synchronized dialogue, ambient sound, and Foley natively alongside video frames — no secondary post-production needed.

8-Step DMD-2 Distillation

Radically reduces denoising steps without CFG, accelerated heavily by the MagiCompiler runtime for 10x faster generation.

Multilingual Lip-Sync

Native support for 7 languages (EN, ZH, JP, KO, DE, FR) boasting industry-leading Word Error Rate metrics in open arenas.

1080p Resolution Target

5–8 second pristine clips natively upscaled to 1080p spanning standard social aspect ratios (16:9, 9:16).

Self-Hostable First

Strictly permissive, open-source model designed to run in-house. Transparent code guarantees privacy for enterprise teams.

Deployment Infrastructure

Happy Horse 1.0 codebases and model weights are currently undergoing final staging.

Release Status

Preparing Release Package

FP8 quantization targets, distilled checkpoints, and public release documentation are being finalized for the first open rollout.

Codebase
Final QA
Weights
Packaging
Docs
In Review
Pipeline 87%
Inference stack validation
Done
Model artifact bundling
Active
Public documentation
Pending

Frequently Asked Questions

Happy Horse Generator is the official website and product identity for Happy Horse 1.0, an open-source AI video generation model focused on text-to-video and image-to-video with synchronized audio.
Happy Horse 1.0 is a 15B-parameter open-source AI video generation model that jointly produces video and synchronized audio from text or image prompts.
Yes. Happy Horse is released as completely true open source with straightforward commercial-use rights, spanning the base model, distilled layers, and super-resolution units.
Yes. Happy Horse 1.0 is designed for both text-to-video and image-to-video generation, and the benchmark sections on this page reflect performance across both tasks.
Yes. Happy Horse jointly generates video and synchronized audio, including speech, ambient sound, and other soundtrack elements, instead of relying on a separate audio pipeline.
Yes. Happy Horse includes multilingual lip-sync capabilities and is designed to support multiple languages with strong prompt alignment and speech-to-motion consistency.
An NVIDIA H100 or A100 GPU cluster with at least 48GB VRAM per node is strictly recommended. A standard 5-second 1080p generation currently clocks ~38s on a single H100.
The Happy Horse codebase, model weights, distilled checkpoints, and release documentation are currently in final staging. The deployment section on this page reflects that release-preparation status.
Yes. Happy Horse is positioned as a self-hosted, on-prem friendly open-source video generation model, making it suitable for teams that need privacy, deployment control, and commercial-use flexibility.