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FSRS Review Interval Calculator

Explore how the Free Spaced Repetition Scheduler (FSRS) algorithm determines when you should review a card. Adjust stability, difficulty, and target retention to see how intervals change in real time.

Parameters

30 days
1 day365 days

How long the memory can last before dropping to 90% recall probability.

5 / 10
EasyVery hard

Higher difficulty slows stability growth after successful reviews.

90%
70%95%

The probability of recall you want at the time of next review. Higher retention means shorter intervals.

Results

Next Review In

35.2days

~1 month


New Stability

35.2days

+17% from current


Retrievability at Review

90%

Probability of successful recall at review time

A good response is the standard successful recall. FSRS increases stability based on the current difficulty and how close you were to forgetting.

How FSRS Works

The Free Spaced Repetition Scheduler (FSRS) is a modern, open-source algorithm that models human memory mathematically. Unlike older systems like SM-2 (used in Anki by default), FSRS is built on the DSR (Difficulty, Stability, Retrievability) model of memory. Each card carries three core parameters: how hard it is to learn, how long the memory can persist, and the current probability that you can recall it.

Stabilityis the key concept. It represents the number of days after which your recall probability drops to a reference point (typically 90%). A stability of 30 days means that 30 days after your last review, you have a 90% chance of recalling the card. After a successful review, stability increases -- the memory becomes more durable. After a lapse (pressing "Again"), stability drops back down, and the card is scheduled for near-term review.

Difficulty controls how fast stability grows. Easy cards gain stability rapidly after each review, while difficult cards grow more slowly. FSRS adjusts difficulty over time based on your actual performance, so cards naturally calibrate to your learning capacity. This is one of the reasons FSRS outperforms fixed-interval systems -- it adapts to each individual card and learner.

Desired retention is the lever you control. Setting it to 90% means FSRS will schedule reviews so that at the moment a card appears, you have roughly a 90% chance of recalling it. Lowering retention (e.g., to 80%) spaces reviews further apart but increases the chance you will have forgotten. Raising it (e.g., to 95%) keeps cards fresher but increases daily review load. The sweet spot for most learners is between 85% and 92%.

Note: The calculator above uses a simplified educational model of the FSRS formulas. The full FSRS v5 algorithm includes additional parameters optimized on real review data. For production-grade scheduling, use a complete FSRS implementation like the one built into Revu.

Experience FSRS Scheduling in Revu

Revu uses the full FSRS algorithm to schedule your reviews automatically. Import your study materials, and let the scheduler optimize your retention with zero configuration.

Get started with Revu