MarkText vs Novlr

MarkText is a free, open-source desktop Markdown editor that displays formatted text as you write. It offers WYSIWYG preview and source-code editing, plus focus and typewriter modes. Writing features include tables, KaTeX math, diagrams, footnotes, code highlighting, and YAML, TOML, and JSON front matter. Listed diagram tools include Mermaid, Vega, and Vega-Lite. The editor has 33 light and dark themes, with CSS customization available. Documents can be exported as PDF or self-contained HTML, and local files are supported. MarkText runs on Linux, macOS, and Windows. Installation notes require macOS 11 or later and Windows 10 or 11, and provide arm64 and x64 installers for those systems. Homebrew, Chocolatey, and Winget are also listed as installation options. The homepage says MarkText needs no account and has no tracking. It is released under the MIT License, has no subscription, and is described as a volunteer-built project.

Novlr is a creative writing workspace for planning, drafting, and publishing projects. Its tools include focus and typewriter modes, writing sprints, goals, streaks, analytics, notes, and a planning grid for following story arcs and plot threads alongside a manuscript. Writing and notes can be exported as DOCX, PDF, ODT, EPUB, or RTF. The Free plan costs nothing and includes two projects, online syncing, notes and planning, focus mode, writing sprints, and analytics. Starter costs $8 a month, billed yearly, with up to 10 projects, 30-day version history, goals, streaks, Academy courses, and community access. Studio costs $16 a month, billed yearly, and adds unlimited projects and version history, Novlr Sites, proofing tools, backups to Google Drive or Dropbox, and priority support. Novlr Sites offers themes and custom domains. Novlr works through current major browsers, including Safari on iOS and Chrome or Firefox on Android, but requires an active internet connection even when saved to a phone or tablet home screen. It has no mobile apps. The company says it does not use writing for AI processing or training.