OpenMOSS/MOVA

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1106 stars · 91 forks observed · 2026-09-01

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

MOVA is an open-source foundation model and toolkit for joint video-audio generation, synthesizing synchronized video and audio in a single diffusion-based inference pass. It ships model weights, inference code, training and LoRA fine-tuning pipelines, evaluation code, a benchmark dataset, and ComfyUI integration.

Use cases

• generate videos with synchronized audio from text prompts
• create lip-synced talking videos in multiple languages
• add environment-aware sound effects to generated video
• fine-tune video-audio generation with LoRA on custom data
• evaluate video-audio generation models on a benchmark
• generate video programmatically via API
• use video-audio generation inside ComfyUI workflows

When to choose

• you need open-source video generation with native synchronized audio rather than a cascaded pipeline
• you want lip-sync and sound effects without closed models like Sora 2 or Veo 3
• you need weights, training code, and fine-tuning scripts to build on
• you want reproducible evaluation with a released benchmark

When to avoid

• you only need video without audio and prefer lighter established text-to-video models
• you lack GPU hardware for large diffusion model inference
• you need a polished end-user product rather than a research toolkit

Facets

library · maturity active

video-processing audio-processing deep-learning llm-inference stable-diffusion artificial-intelligence deep-learning machine-learning python video-audio-generation diffusion-models multimodal-generation lip-sync sound-effects lora-fine-tuning comfyui sglang foundation-model text-to-video video audio gpu linux docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="OpenMOSS/MOVA")