Study Scheduling
Spaced repetition algorithms
How SM-2, Leitner, and FSRS schedule flashcard reviews — and why FSRS is Deckbase's default.
Algorithm overview
A spaced repetition algorithm decides when to show you a card again after you review it. The goal is to schedule each review just before you would otherwise forget the answer, so you get maximum retention with minimum effort.
Different algorithms make that decision in different ways. Some use fixed boxes, some use fixed formulas, and some use machine-learning models of memory. Deckbase uses FSRS because it adapts to your personal recall history, but the other algorithms are still useful to understand — especially if you are migrating from another app.
Quick comparison
| Algorithm | How it works | Best for |
|---|---|---|
| FSRS | Models memory with Difficulty, Stability, and Retrievability; personalizes intervals from your review history. | Long-term learning, mixed decks, large card libraries. |
| SM-2 | Multiplies intervals by an ease factor based on your last rating. | Simple, predictable scheduling; small to medium decks. |
| Leitner | Moves cards between boxes; correct answers advance, failures move back. | Beginners, simple apps, learning a small set of facts. |
FSRS
FSRS (Free Spaced Repetition Scheduler) is an open-source algorithm created by Jarrett Ye. It models memory for each card using three values — Difficulty, Stability, and Retrievability — and calculates intervals from your personal review history instead of applying fixed rules.
Because FSRS adapts to each learner, it typically reduces daily review volume by 20–30% compared with SM-2 for the same retention target. It is the default scheduler in Deckbase and is also available in Anki 23.10 and later.
- Adapts intervals to your actual recall patterns.
- Usually fewer reviews for the same retention.
- More complex than SM-2 or Leitner; benefits from more review history.
SM-2
SM-2 is the SuperMemo-2 algorithm created by Piotr Wozniak in 1987. Anki used a modified version of SM-2 as its default scheduler for many years, and it is still available as a fallback in Anki today.
SM-2 tracks a single value called the ease factor. When you rate a card Easy, the ease factor increases and future intervals grow faster. When you rate it Again or Hard, the ease factor drops and intervals shrink. The algorithm is simple and robust, but it does not model memory directly and can push cards into "ease hell" if they are lapsed repeatedly.
- Simple to understand and implement.
- Works well for small to medium decks.
- Less efficient than FSRS for large, long-term libraries.
Leitner system
The Leitner system is the simplest spaced repetition method. Cards start in Box 1. If you answer correctly, the card moves to the next box and is reviewed less often. If you answer incorrectly, it moves back to Box 1.
Leitner is easy to explain and works without any software, which is why it appears in paper flashcard systems and basic apps. The downside is that intervals are fixed by box number, not by your actual recall probability. Two cards in the same box may be at very different memory strengths.
- Easy to learn and teach.
- Good for small, focused sets of facts.
- Not ideal for large decks or long-term retention goals.
Review steps and your algorithm
Every card starts the same way, no matter which method you use: when it's brand new, or when you forget it, you see it again after a few minutes, then a bit longer, then longer still. Once it "graduates," it stops showing up every few minutes and starts showing up every few days instead. What happens after that point is different for each method:
FSRS
Before it graduates: Same minutes-then-longer steps as every method.
After it graduates: Figures out on its own how long to wait, based on how well you're actually remembering that card.
SM-2
Before it graduates: Same minutes-then-longer steps as every method.
After it graduates: Waits a set number of days at first, then waits a little longer each time you get it right.
Leitner
Before it graduates: Same minutes-then-longer steps as every method.
After it graduates: Goes into "Box 1." Get it right and it moves up a box (longer wait); get it wrong and it drops back down.
Why Deckbase uses FSRS
Deckbase chose FSRS because it is the only mainstream algorithm that adapts to your personal memory. SM-2 and Leitner apply the same schedule to every learner. FSRS learns from your ratings and calculates intervals that fit your actual forgetting curve.
That adaptivity matters most when you study for months or years. Independent benchmarks on hundreds of millions of Anki reviews show FSRS reduces prediction error by roughly two-thirds compared with SM-2, which typically means 20–30% fewer reviews for the same retention.
For details on how FSRS works in Deckbase, see FSRS in Deckbase.
FAQ
Which algorithm is best for beginners?
Leitner is the easiest to understand, but FSRS is better for long-term retention. Most beginners do well with FSRS because modern apps like Deckbase handle the tuning automatically.
Is SM-2 outdated?
SM-2 is older and less efficient than FSRS for large decks, but it is still functional. If you have a small deck or prefer predictable rules, SM-2 is fine.
Can I use Leitner or SM-2 instead of FSRS?
Yes — Settings → Spaced repetition algorithm lets you pick FSRS, SM-2, or Leitner at any time, and you can switch back and forth freely. FSRS is the default because it generally outperforms both for long-term learning, but SM-2 and Leitner are fully supported if you prefer them.
Will my SM-2 intervals transfer from Anki?
No. When you import an Anki deck into Deckbase, cards start fresh with FSRS intervals. Your review history and SM-2 ease factors are not transferred.
For a deeper technical explanation of FSRS, see the FSRS guide • For setup help, see Docs overview