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SPECIFICTION
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ListenHub vs Mozilla Document-to-Podcast

ListenHub

listenhub.ai

Mozilla Document-to-Podcast

github.com

Side by side

FigureListenHubMozilla Document-to-Podcast
Price from$8.33/mo—
Free plan——
Free trial——
Open source——
WebYes—
Windows—Yes
macOS—Yes
Linux—Yes
APIYes—
Self-hosted—Yes
Plans published40
Spec score · AI Podcast Generators7.5 (#11)7.4 (#15)
Input formatsUsers can start with a prompt, web or YouTube link, PDF, Word, EPUB, Markdown, or TXT document, and JPG, PNG, or WebP reference images.The CLI accepts PDF, HTML, TXT, DOCX, and Markdown files.
SupportListenHub lists [email protected] for technical support and questions.The README directs users with issues to the troubleshooting documentation before opening a new issue, and the docs invite questions on Discord.

Plans

ListenHub

  • Starter$100 a year
  • Basic$200 a year
  • Pro$399 a year
  • EnterprisePriced on request

ListenHub pricing →

Mozilla Document-to-Podcast

No plans published.

Mozilla Document-to-Podcast pricing →

In their own words

ListenHub

ListenHub has no write-up on Specifiction yet; its figures are above.

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Mozilla Document-to-Podcast

Mozilla Document-to-Podcast is an open-source Mozilla.ai blueprint that turns documents into two-speaker podcasts. Its workflow extracts and cleans text, uses a language model to create a conversational script, then generates speech audio. The CLI accepts PDF, HTML, TXT, DOCX and Markdown files, and saves podcast.txt and podcast.wav in the selected output folder. Users can customize prompts, speakers, voice profiles and model settings, and select text models that load with llama.cpp; Kokoro-82M is supported out of the box for text-to-speech. The project offers a command-line interface and a Streamlit demo app, with installation through PyPI or an editable clone. It is designed for local processing without external API calls or GPU access. The stated requirements include Windows, macOS or Linux, Python 3.10 or later (3.12 or later for Apple M chips), at least 8 GB RAM and 20 GB disk space. When cleaned text exceeds the model's context-based character limit, the CLI may use only part of the input.

Visit github.com