If you've used a flashcard app before, there's a good chance it was quietly using math from 1987. SuperMemo's SM-2 algorithm — a fixed set of rules for spacing repetitions — became the default almost everywhere, including in apps you've probably heard of. It works, but it treats every card, and every learner, the same way.
FSRS (Free Spaced Repetition Scheduler) is different. It's a modern, open-source algorithm that builds an actual memory model for each card you study, based on how you've personally performed on it — not a generic formula.
The problem with fixed intervals
Older algorithms schedule your next review using a small set of hardcoded multipliers: get a card right, and its interval roughly doubles, regardless of how confidently you knew it or how hard the material actually is. Two very different cards — an easy one and a genuinely tricky one — can end up on nearly identical schedules.
The result is a review queue padded with cards you already know cold, while genuinely difficult material doesn't get the extra attention it needs.
What FSRS does differently
FSRS models each card with a small set of memory parameters — difficulty, stability, and retrievability — and updates them after every single review based on your actual answer and response time. Over time, it learns your personal forgetting curve, not just the card's.
In practice, that means reviews land right when you're about to forget — not too early (wasted time) and not too late (you already forgot).
Published benchmarks from the open-source spaced-repetition community have shown FSRS reducing the number of reviews needed to hit a given retention target compared to SM-2-style scheduling, while improving actual retention.
Why we built StudyBudy on it
We didn't want to write our own scheduling algorithm from scratch and hope it was good — FSRS is peer-reviewed, open-source, and actively maintained by researchers and developers who care about getting the memory science right. Every deck you study in StudyBudy, free or Pro, runs on it.
If you want to see it in action, the fastest way is to just start a deck — the scheduler adapts from your very first review.
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