MMAudio
MMAudio is a free, open-source project that generates audio from video or text and aligns generated audio with video frames.
What MMAudio is
MMAudio is a free, open-source project that generates audio from video or text and aligns generated audio with video frames. Its command-line demo and Gradio interface support video-to-audio and text-to-audio generation. The interface also offers experimental image-to-audio processing: the model was not trained for this mode, and the demo duplicates a still image into a video. The demo saves audio as FLAC and video as MP4; its default output duration is 8 seconds, and durations far from that may reduce quality. MMAudio runs on Linux or in a self-hosted setup. Installation requires Python 3.9 or later and PyTorch 2.5.1 or later with corresponding torchvision and torchaudio; the project says it has only been tested on Ubuntu. In 16-bit inference, the default large_44k_v2 model uses around 6 GB of GPU memory, according to project experiments. Generated results may include unintelligible speech-like sounds or background music, and the model may struggle with unfamiliar concepts. The code is MIT licensed, while pretrained checkpoints use CC-BY-NC 4.0; the project does not guarantee pretrained models are suitable for commercial use.
Good
- Generates audio from video and text inputs.
- Aligns generated audio with video frames.
- Offers command-line and Gradio interfaces.
- Saves audio as FLAC and video as MP4.
- Links to Hugging Face, Colab, and Replicate demos.
Watch out
- Image-to-audio is experimental and not a training target.
- Installation requires Python 3.9+ and PyTorch 2.5.1+.
- Only tested on Ubuntu, according to the project.
- Commercial suitability of pretrained models is not guaranteed.
Who it suits
MMAudio suits Linux users or self-hosters looking to generate audio from video or text. Its experimental image mode is for users willing to try a capability the model was not trained for.
Verdict
MMAudio provides video- and text-based audio generation with synchronization and both command-line and Gradio interfaces. Check the image-mode caveat, hardware needs, output-duration default, and checkpoint license before choosing it.
Plans and prices
From MMAudio's own pricing page, checked 10 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| MMAudio | Free | Code released under MIT license · pretrained checkpoints under CC-BY-NC 4.0 |
The facts
Each one read from MMAudio's own pages, with the date it was checked.
What it does
- Commercial use
- The project says it does not guarantee pretrained models are suitable for commercial use.checked 4 Oct 2026
- Data handling
- The maintainers say they cannot redistribute the training datasets for copyright reasons.checked 10 Oct 2026
- Demo availability
- The repository links to Hugging Face, Colab, and Replicate demos.checked 10 Oct 2026
- Generation modes
- The command-line demo supports video-to-audio and text-to-audio generation.checked 4 Oct 2026
- Hardware
- The README says inference uses around 6 GB of GPU memory in 16-bit mode in its experiments.checked 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.checked 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.checked 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.checked 10 Oct 2026
- Interface
- The project provides a Gradio interface for video-to-audio and text-to-audio, with experimental image-to-audio support.checked 4 Oct 2026
- Interfaces
- The project provides a command-line demo and a Gradio interface.checked 10 Oct 2026
- Joint training
- Its multimodal joint training uses audio-visual and audio-text datasets.checked 10 Oct 2026
- Known limitations
- The model may produce unintelligible human speech-like sounds, background music, and poor results for unfamiliar concepts.checked 10 Oct 2026
- Licensing
- The repository code is MIT licensed, while pretrained checkpoints are released under CC-BY-NC 4.0.checked 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.checked 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.checked 4 Oct 2026
- Output duration
- The default output and training duration is 8 seconds; durations far from training duration may reduce quality.checked 10 Oct 2026
- Purpose
- MMAudio generates synchronized audio from video and/or text inputs.checked 10 Oct 2026
- Runtime requirements
- Installation requires Python 3.9+ and PyTorch 2.5.1+ with corresponding torchvision and torchaudio; the project says it has only been tested on Ubuntu.checked 4 Oct 2026
- Support
- The project invites users to open a repository issue if they notice a failure mode or believe there is a bug.checked 4 Oct 2026
- Synchronization
- A synchronization module aligns generated audio with video frames.checked 10 Oct 2026
- Synthesis modes
- The included demos support video-to-audio and text-to-audio synthesis, with experimental image-to-audio processing through a duplicated still image.checked 10 Oct 2026
- Training hardware
- The authors recommend, for smooth training, single-node setups with two 80 GB H100 GPUs for the small model or eight for the large model, plus hundreds of gigabytes of system memory.checked 10 Oct 2026
- Training limitation
- The current training script does not support _v2 training.checked 10 Oct 2026
Where it runs
- Demos and integrations
- The repository links to Hugging Face and Colab demos and a Replicate demo.checked 4 Oct 2026
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