Pick Anki if you want the strongest spaced-repetition algorithm and don't mind building cards by hand. Pick Quizlet if you want a huge ready-made library and game-style review. Pick Queazy if you want an AI to turn your own lectures and PDFs into quizzes and flashcards in seconds, with every answer grounded in your material.
The three tools solve different bottlenecks. Anki optimizes review: its scheduler decides when you see a card again. Quizlet optimizes access: millions of pre-made sets you can study in a tap. Queazy optimizes creation: it reads your actual source material and writes the questions for you. Most "best flashcard app" arguments go in circles because people compare them on the one axis where their favorite happens to win.
Side-by-side
| Anki | Quizlet | Queazy | |
|---|---|---|---|
| Card creation | Manual (or imports) | Manual + some AI | AI from your PDFs/slides |
| Spaced repetition | Best-in-class (FSRS/SM-2) | Basic ("Learn" mode) | Built-in mastery + review queue |
| Pre-made content | Huge community decks | Largest set library | Generated from your material |
| Grounding / citations | N/A (your cards) | N/A | Cites your source pages |
| Spoken practice | Add-ons only | No | Built-in voice exam |
| Price | Free (iOS $24.99) | Freemium (paywalled AI) | Free in pre-launch |
| Learning curve | Steep | Gentle | Gentle |
Who each one is for
Anki is the right call in a high-volume program (med school, languages) where you'll adopt a community deck like AnKing. Its FSRS scheduler is the best free spaced-repetition engine available, and nothing beats it for holding thousands of facts over months. The cost is time: you build cards by hand or learn its import and add-on ecosystem.
Quizlet wins on convenience. If someone already made a set for your chapter, you're reviewing in under a minute, and the game modes (Match, Test) are motivating for shorter material. The trade-offs: the strongest study modes and AI features sit behind Quizlet Plus, and its spacing is weaker than Anki's.
Queazy is built for the step everyone hates — making the material in the first place. Upload a lecture PDF or slide deck and it generates quizzes, flashcards, and a voice-based oral exam, with each answer tied back to the page it came from. That grounding is the difference from a generic chatbot: it works from your syllabus, not the internet's average answer.
Upload one lecture PDF and watch Queazy turn it into a quiz and flashcards in seconds — free during pre-launch.
Generate a study kit freeA quick way to choose
- Long-term retention of thousands of discrete facts → Anki.
- A set that already exists plus fast game-style drills → Quizlet.
- Your own slides/PDFs turned into practice fast → Queazy.
Plenty of strong students run two: Queazy or Quizlet to create and drill quickly, Anki to retain what matters over months. The tools aren't mutually exclusive — your bottleneck picks the starter.
FAQ
Is Anki better than Quizlet for spaced repetition?
Yes. Anki's scheduler (FSRS or SM-2) is purpose-built and adapts intervals to your performance. Quizlet's "Learn" mode spaces items but is far less configurable and less aggressive about long-term retention.
What does Queazy do that the others don't?
It generates the study material from your own files and keeps every answer grounded in the source page, plus a spoken oral-exam mode. Anki and Quizlet expect you to bring or build the cards.
Can I use more than one?
Yes. A common combo is generating cards fast in Queazy or Quizlet, then exporting the keepers into Anki for long-term review.
Read next
- How to Make Effective Flashcards (That Actually Stick)
- Spaced Repetition: The Complete 2026 Guide (With Schedules)
- ChatGPT vs Queazy for Studying
Sources
- Settles, B., & Meeder, B. (2016). A trainable spaced repetition model for language learning. Proceedings of ACL. https://doi.org/10.18653/v1/P16-1174
- Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques. Psychological Science in the Public Interest, 14(1), 4-58. https://doi.org/10.1177/1529100612453266
