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TabType vs the alternatives

An honest, detailed comparison. TabType's goal is Cotypist-grade quality as a free, open-source, on-device app. This page is kept truthful — including where others still lead.

TabType vs Cotypist

Cotypist is the closest product and our reference point. It is closed-source and freemium; TabType is open-source (MIT) and free with no account.

Capability TabType Cotypist
On-device local LLM ✅ Qwen3-4B (MLX)
Apple Intelligence engine ✅ (macOS 26)
Ghost-text, word-by-word accept
Type-through (updates as you type)
Word alternatives ✅ ⌃⌥Space
Screen context (OCR)
Accessibility-tree transcript for chat apps
Your recent messages / previous writing as context
Personal phrase memory & few-shot
Speculative "parked" generation + KV cache
Text mirroring (pixel-perfect ghost)
Per-app & per-domain policies
Emoji / macros / autocorrect ✅ (+ Indian languages) partial
Notarized, App Store-smooth install ❌ (alpha, unnotarized)
Breadth of tested apps & polish ⚠️ growing ✅ mature
In-app auto-update ❌ (manual for now)

Where Cotypist still leads: it's notarized (no Gatekeeper dance), more polished, tested across more apps, and has auto-update. TabType is an alpha closing that gap in the open.

TabType vs other open-source / indie tools

  • Sombra — llama.cpp + macOS dictionary completions. Great lightweight approach; TabType adds richer context (AX transcripts, recent messages), speculative parking, and mirror rendering.
  • KeyType — explores constrained/grammar decoding. Impressive technique; TabType prioritizes context quality and per-app UX parity instead.
  • cotabby — focused-window OCR context. TabType extends this with accessibility-tree extraction (cleaner than OCR) and per-app extraction policies.

TabType vs GitHub Copilot / macOS predictive text

  • Copilot & code assistants — optimized for code in editors, often cloud-backed. TabType is for prose, everywhere, fully private, and deliberately stays out of the main code editor.
  • macOS inline predictive text — single-word, OS-limited. TabType predicts multi-word continuations with real context.

Have a correction? This comparison should stay honest — open an issue.