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Async vs AudioGen

Async

async.com

AudioGen

github.com

Side by side

FigureAsyncAudioGen
Price fromFreeFree
Free planYesYes
Free trial——
Open source——
WebYes—
Linux—Yes
iOSYes—
APIYesYes
Self-hosted—Yes
Plans published51
Spec score · AI Sound Effect Generators8.3 (#6)8.8 (#2)
Spec score · AI music generators7.4 (#103)8.0 (#54)
Free planYesYes
SupportAsync’s help center provides guides covering accounts and billing, recording, video editing, AI generation, and other product areas.The model card directs questions and comments to the project’s GitHub repository or its issue tracker.

Plans

Async

  • FreeFree
  • EssentialsPrice not published
  • ProPrice not published
  • TeamsPrice not published
  • BusinessPriced on request

Async pricing →

AudioGen

  • AudioGen (self-hosted)Free

AudioGen pricing →

In their own words

Async

Async is an online AI video editor where users create and edit videos through chat. It can remove filler, pauses, repetitions, bad takes, and awkward moments. Magic Dust reduces background noise and clarifies voices, while chat can generate B-roll, visuals, scenes, or music within an edit. Users can add subtitles and turn moments from longer videos into short-form clips. Async presents the workflow for ads, vlogs, explainers, podcasts, and other formats, and says it is built for creators and teams. Its browser-based remote interview feature supports up to 10 participants with separate tracks; local recording and automatic transcription are also listed. The Voice API supports text-to-speech and speech-to-text, including streaming over WebSockets. Async is available on the web and iOS, with no Android version listed. The Free plan is free and includes 10 lifetime AI credits, one hour of media upload to AI chat, exports up to 720p, and 2 GB storage. Paid pricing starts at $11.99/mo (annual).

Visit async.com

AudioGen

AudioGen is a text-to-sound model provided through AudioCraft. It generates audio samples from text descriptions and can continue from an audio prompt, with conditional and unconditional generation modes. Sampling controls include greedy, temperature, top-K, and top-P methods. The listed pretrained model, facebook/audiogen-medium, has 1.5 billion parameters; the example API generates sound and saves it as WAV. The implementation uses an autoregressive Transformer and a 16 kHz EnCodec tokenizer. The repository provides API access and a local Jupyter notebook demo. Running the medium model locally requires a GPU with at least 16 GB of memory; installation requires Python 3.9 and PyTorch 2.1.0, with ffmpeg recommended. The model was trained on English descriptions and performs less well in other languages. It cannot generate realistic vocals, and prompts may need refinement. Code is MIT-licensed, while weights use CC-BY-NC 4.0; training datasets are not provided. The listed self-hosted plan is free.

Visit github.com