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MMAudio
What it is
MMAudio generates audio synchronized with video from video and/or text inputs. Its synchronization module aligns generated sound with video frames. The command-line demo and Gradio interface support video-to-audio and text-to-audio generation, while the interface also offers experimental image-to-audio processing. In that image mode, the model was not trained for image-to-audio and the demo duplicates the still image into a video. MMAudio is free open source for Linux or self-hosted use. Installation requires Python 3.9 or later, PyTorch 2.5.1 or later, and matching torchvision and torchaudio; the project says it has only been tested on Ubuntu. Its default large_44k_v2 model uses around 6 GB of GPU memory for 16-bit inference, according to project experiments. Demos save audio as FLAC and video as MP4, with an eight-second default output and training duration. The model may produce unintelligible speech-like sounds or background music and may struggle with unfamiliar concepts. Code is MIT licensed, while pretrained checkpoints use CC-BY-NC 4.0, and commercial suitability is not guaranteed.
For and against
For
- Synchronizes generated audio with video frames
- Supports video-to-audio and text-to-audio
- Provides command-line and Gradio interfaces
- Open-source code under the MIT license
- Links to Hugging Face, Colab, and Replicate demos
Against
- Image-to-audio mode is experimental
- Project tested only on Ubuntu
- Pretrained checkpoints use CC-BY-NC 4.0
- Commercial suitability is not guaranteed
The verdict
MMAudio offers self-hosted audiovisual generation with command-line and Gradio workflows. Its experimental image mode, Linux-focused setup, model limitations, and checkpoint license matter when planning use.
Who it suits
MMAudio suits developers running Linux or self-hosted experiments who want synchronized audio from video or text and can meet its Python and PyTorch requirements.
Plans and prices
MMAudio
Code released under MIT license · pretrained checkpoints under CC-BY-NC 4.0
Read 10 Oct 2026 · github.com
On the record
- Commercial use
- The project says it does not guarantee pretrained models are suitable for commercial use.github.com · read 4 Oct 2026
- Data handling
- The maintainers say they cannot redistribute the training datasets for copyright reasons.github.com · read 10 Oct 2026
- Demo availability
- The repository links to Hugging Face, Colab, and Replicate demos.github.com · read 10 Oct 2026
- Demos and integrations
- The repository links to Hugging Face and Colab demos and a Replicate demo.github.com · read 4 Oct 2026
- Generation modes
- The command-line demo supports video-to-audio and text-to-audio generation.github.com · read 4 Oct 2026
- Hardware
- The README says inference uses around 6 GB of GPU memory in 16-bit mode in its experiments.github.com · read 10 Oct 2026
- Image limitation
- Image-to-audio is experimental and the model was not trained for it; the demo duplicates the image into a video for processing.github.com · read 4 Oct 2026
- Input processing
- The CLIP encoder resizes frames to 384×384 pixels, while Synchformer resizes the shorter edge to 224 pixels and center-crops each frame.github.com · read 4 Oct 2026
- Installation
- The repository documents installation with Python 3.9 or later and PyTorch 2.5.1 or later, and says it has only been tested on Ubuntu.github.com · read 10 Oct 2026
- Interface
- The project provides a Gradio interface for video-to-audio and text-to-audio, with experimental image-to-audio support.github.com · read 4 Oct 2026
- Interfaces
- The project provides a command-line demo and a Gradio interface.github.com · read 10 Oct 2026
- Joint training
- Its multimodal joint training uses audio-visual and audio-text datasets.github.com · read 10 Oct 2026
- Known limitations
- The model may produce unintelligible human speech-like sounds, background music, and poor results for unfamiliar concepts.github.com · read 10 Oct 2026
- Licensing
- The repository code is MIT licensed, while pretrained checkpoints are released under CC-BY-NC 4.0.github.com · read 4 Oct 2026
- Model license
- The code is MIT licensed, while the pretrained checkpoints are released under CC-BY-NC 4.0; the README does not guarantee pretrained models are suitable for commercial use.github.com · read 10 Oct 2026
- Output and duration
- The demo saves audio as FLAC and video as MP4, and its default output and training duration is 8 seconds.github.com · read 4 Oct 2026
- Output duration
- The default output and training duration is 8 seconds; durations far from training duration may reduce quality.github.com · read 10 Oct 2026
- Purpose
- MMAudio generates synchronized audio from video and/or text inputs.github.com · read 10 Oct 2026
