Paper2Pod vs Podcastfy

Paper2Pod converts research paper PDFs into podcasts that summarize key findings and insights. It is available on iOS and the web, and accepts papers as PDFs, through a connected Zotero library, or by research topic. Users can choose concise, normal, or detailed content and beginner, intermediate, or expert levels. They can also describe a research interest to receive recurring audio reviews of recent papers found through Semantic Scholar, grouped into themes and ranked by journal quality. A Zotero connection lets users search saved references and make podcasts without downloading and uploading papers again. The Free plan includes unlimited podcasts and research updates, concise length, every expertise level, the standard AI model, and chat with papers, figures, and Zotero imports. Pro costs $2.99 a month and adds all lengths, research overviews of papers in a field, a smart model, longer and deeper research updates, and priority support. Users retain ownership of uploaded content, while granting the service a license to use, store, and process it. The terms caution that AI may not interpret every paper perfectly, so generated audio may not fully match or represent its source. Account deletion does not automatically cancel a subscription.

Podcastfy is a free, open-source Python package that turns multimodal source material into multilingual audio conversations with generative AI. It accepts websites, PDFs, images, YouTube videos, raw text, transcript files and user-provided topics; topic generation can use grounded real-time web search. Users can set the podcast format, style, voices, language and structure, then generate short episodes of 2–5 minutes or longform episodes of 30 minutes or more. Transcript generation supports more than 100 language-model options, including OpenAI, Anthropic and Google models. Listed speech engines include OpenAI, Google, ElevenLabs and Microsoft Edge. Local language models are supported for transcript generation, offering the project’s stated privacy and control benefits. Usage is available through a Python package, command-line interface and beta FastAPI service for URLs, with MP3 audio export. API-key needs depend on selected models; a documented local-model and Edge TTS setup requires none. Python 3.11 or higher and ffmpeg are required. The project uses the Apache 2.0 license.