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Home/Open source/HappyHorse-1.0
Open source

HappyHorse-1.0

Alibaba ATH, open-sourced 2026-04 under Apache 2.0 — commercially usable. This is the weights release, not the metered HappyHorse 1.1 API above. At 15B parameters, VRAM is the hard gate: full FP16 needs 30GB+, so consumer cards (12 / 16 / 24GB) must use INT8 / GGUF quantisation or CPU offload, at a speed cost.

32 GB
VRAM floor
15B
Parameters
1
open-weight models

Open source Highest bar

Weights are free, hardware is not: you buy the GPU up front (one-time estimate, may rise) and still pay for power and time. Six of the twelve are Apache 2.0 (HappyHorse-1.0, SANA-WM, Bernini, MAGI-2, LingBot-Video, LongLive 2.0); LTX-2 and LTX-2.5 use community licences and SANA-Video uses the NVIDIA Open Model License. Hardware runs from one RTX 5090 to 8× H100. See all 12 →

Hardware requirements, as published

VRAM floor
30GB+ in full FP16
Official hardware
Single card with 30GB+; 12 / 16 / 24GB cards need INT8 / GGUF quantisation or CPU offload
Output
1080P / 15 sec with joint audio-video generation
Size
15B parameters
Licence
Apache 2.0 (commercially usable)
Full FP16 needs 30GB+ of VRAM; consumer cards (12 / 16 / 24GB) must use INT8 / GGUF quantisation or CPU offload, at a speed cost.Alibaba ATH · happyhorse.com
1 records · showing Specs checked 2026-11-10 · hardware 2026-10-21
# Platform / model Layer VRAM · setup One-time hardware
— OSSHappyHorse-1.0 ↗Alibaba ATH · 2026-04 · Apache 2.0 · 15B Open source 32 GB30GB+ in FP16 · 24GB needs quant ≈ ¥35,000 · one-time1× RTX 5090 32GB · estimate, may rise
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