The phrase “FSRS vs Anki” hides a mismatch worth clearing up first: Anki is an app, and FSRS is a scheduling algorithm that Anki offers as an option alongside its original SM-2 scheduler. So the honest comparison is not app versus app — it is two schedulers, plus how much work each setup asks of you around them.
Where the confusion comes from
For most of its history, Anki scheduled reviews with SM-2, the classic ease-factor algorithm. It now also offers FSRS as an optional scheduler, so two Anki users can be running two different algorithms depending on their settings. When people compare “FSRS vs Anki,” they are usually comparing FSRS against the traditional SM-2 behaviour that Anki was known for.
Keeping that straight is the whole game. You are choosing a scheduler, and both apps can run FSRS.
The same words, two workloads
Put it in concrete terms. Take one batch of new vocabulary — say 300 words, a normal step between HSK levels. Feed the identical batch to each scheduler and watch what the daily review pile looks like a month later.
Under SM-2 (Anki’s classic scheduler): intervals grow by a fixed ease factor. The word you find trivially easy and the one you keep blanking on are pushed apart by similar multipliers, so the easy word keeps coming back long after you have it, and the hard word’s schedule is not aggressive enough. You spend minutes on cards that teach you nothing.
Under FSRS: the scheduler tracks each word’s difficulty and stability, then returns it when your recall probability has fallen to a target — typically around 90%. The easy word drops out of rotation for weeks; the stubborn one comes back soon. Across the same 300 words, the total review load for a given retention lands roughly 20–30% lower than SM-2.
That is the practical difference for vocabulary. Same cards, same goals, less time spent re-confirming what you already know.
A slim comparison
| FSRS | Anki’s traditional SM-2 | |
|---|---|---|
| Scheduling basis | Difficulty, stability and retrievability per card | Fixed ease factor and interval multiplier |
| Reviews at equal retention | About 20–30% fewer | Baseline |
| Personalisation | Can fit its parameters to your review history | Limited |
| Where you meet it | Built into EnjoyCards; offered in Anki as an option | Anki’s classic default behaviour |
Note the last row: FSRS is not exclusive to either app. Anki users can switch to it, and EnjoyCards applies it automatically.
The part that is not about the algorithm
If both setups can run FSRS, the deciding difference shifts to everything else.
Anki’s strength is control. Add-ons, hand-tuned parameters, huge shared decks, and a community that will help you customise almost anything. That depth is real, and for some learners it is the point. It also comes with a cost: time to learn the tool, and time to build cards by hand or hunt down a deck that fits.
A tool like EnjoyCards trades some of that control for speed. Cards are generated for you, the scheduler is configured out of the box, and the daily session is short. That is a smaller feature set, but for a learner whose bottleneck is making the cards, it removes the exact step that causes most decks to be abandoned.
So “which is better” depends on which problem you have. If your problem is “I want maximum control over my schedule and a 20,000-card deck,” Anki is the better answer. If your problem is “I keep meaning to build a vocabulary deck and never do,” the automatic scheduler and generated cards matter more than any parameter you could tune.
A fair verdict
- On scheduling alone, FSRS wins. Fewer reviews for the same retention is a measurable, repeatable advantage.
- Anki can use FSRS too. The algorithmic benefit is not exclusive to one app.
- The bigger difference for most learners is card creation. This is where the two setups diverge far more than on the algorithm.
- Neither fixes bad input. Sloppy cards, passive re-reading, or dishonest grading will slow any system down.
For a fuller picture of the vocabulary curve itself — 1,000 words covering about 85% of everyday speech, 2,000–3,000 reaching roughly 90–95% — see how many words you need to speak a language. For the mechanics of FSRS, our spaced repetition guide explains the intervals, and the FSRS in EnjoyCards walkthrough shows how the algorithm is applied in practice.
If you want the algorithm handled for you, Download EnjoyCards for free and run your next vocabulary batch on FSRS without configuring a thing.