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FeynmanLM vs Anki
Anki is the standard-bearer of spaced repetition: free, open source, fifteen-plus years old, and beloved by med students and language learners. If your goal is memorizing thousands of discrete facts, Anki is hard to beat. FeynmanLM aims at a different target: understanding and retaining the sources you consume — articles, papers, podcasts, books — by explaining them back to an AI tutor rather than flipping self-graded cards.
At a glance
| FeynmanLM | Anki | |
|---|---|---|
| Price | $29 one-time (launch price, regular $67), 7-day trial | Free on desktop and Android; AnkiMobile for iOS is $24.99 one-time |
| AI costs | Pay-as-you-go: free with your existing AI subscription via MCP, or your own API key | No built-in AI; desktop-only community add-ons, bring-your-own-key |
| Platforms | Native macOS app (macOS 14+) | Windows, macOS, Linux, iOS, Android, web review |
| Data storage | Local SQLite + files in your private iCloud container | Local SQLite; free AnkiWeb sync or self-hosted sync |
| Source ingestion | Automatic: articles, papers, podcasts, books, YouTube, X posts | None — cards only; you author or import decks |
| Review method | Feynman-technique dialogue: explain it back, AI probes gaps | Self-graded flashcards (Again/Hard/Good/Easy), SM-2 or FSRS |
| Adaptivity | AI rephrases, follows up on weak spots, asks why | Cards are static; scheduling adapts, questions don't |
| Export | Files in your iCloud Drive; SQLite you can open | Excellent: .apkg/.colpkg/plain text, open format |
Pricing verified July 2026 — see apps.ankiweb.net.
Pricing: both are one-time
This is one comparison where the pricing models agree: no subscriptions on either side. Anki is free (or $24.99 once on iOS); FeynmanLM is $29 once at launch pricing. FeynmanLM's AI review is pay-as-you-go on top — free if you connect the Claude, ChatGPT, Gemini, or Grok subscription you already have, or metered at provider list price with your own API key.
Where Anki is better
- Price and platform reach. Free almost everywhere, including Windows, Linux, and Android.
- Rote memorization at scale. For vocabulary, anatomy, drug names, dates — thousands of discrete facts — self-graded flashcards with FSRS scheduling are the proven tool.
- Shared decks. Decades of community decks (med school, languages) you can download and start reviewing today.
- Total ownership. Open source, local files, self-hostable sync. The strongest possible longevity story.
- Zero AI dependency. Works offline forever, no API keys, no cloud anything.
Where FeynmanLM is better
- Understanding, not recognition. Anki asks "do you remember this card?" and you grade yourself. FeynmanLM asks you to explain the concept from scratch while an AI tutor with the full source text checks your explanation, probes gaps, and asks follow-ups. Static cards can't probe a gap they don't know about — see Why Quizzing?
- No card authoring. Anki's hidden cost is the hours spent making good cards. FeynmanLM skips the authoring step entirely: the source itself is the study material, and questions are generated fresh from it every session.
- Sources flow in automatically. Safari reading list, Apple Podcasts follows, PDFs, papers, books, YouTube — FeynmanLM tracks what you actually consume. Anki has no concept of a source.
- A study planner, not just a review queue. The weekly Schedule assigns sources to days and tracks completion and review history — closer to a study system than a card queue.
- Modern native Mac experience. Reader, Read Aloud, in-app Chat — versus Anki's famously dated UI.
Which should you choose?
Choose Anki for high-volume rote memorization — exams with thousands of facts, language vocabulary — especially on Windows, Linux, or Android, or if you want a zero-cost, zero-cloud tool that will outlive every startup.
Choose FeynmanLM if your problem is the flood of articles, papers, podcasts, and books you consume and forget — and you want to be tested on real understanding without spending evenings authoring flashcards.
They're complementary: several FeynmanLM users keep Anki for pure memorization and use FeynmanLM as the comprehension loop over their reading.