Implementing FSRS in 100 Lines

submited by

Style Pass

2025-01-10 07:00:05

A while back I wrote an implementation of SM-2, the algorithm used by Anki to schedule flashcard reviews. While reading up on it I heard about FSRS, a new algorithm that is slated to replace SM-2 as Anki’s default scheduler. The pitch for FSRS is efficiency: 30% less review time for isoretention compared to SM-2. So I got curious.

Initially I had difficulty understanding FSRS, because the information about it is scattered all over the place: GitHub wikis, blogs, Reddit. On top of that there are different versions of the algorithm, and sources don’t always specify which one they talk about.

So I put everything I could find together, and cleaned it up. The implementation turned out to be just 100 lines, though much of it remains cryptic: while SM-2 was intelligently designed, FSRS was evolved by training a model on a dataset of Anki reviews. But you don’t need a PhD in machine learning to understand the implementation.

The rest of this post explains the theory of FSRS, with equations interleaved with Rust code. If you just want the code, scroll to the end. The repository is here.