> ## Documentation Index > Fetch the complete documentation index at: https://anki.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # What spaced repetition algorithm does Anki use? ## SM-2 As of Anki 23.10, Anki has two available algorithms. The first one is based on the [SuperMemo 2 algorithm](http://www.supermemo.com/english/ol/sm2.htm), and the second one is called [FSRS](https://github.com/open-spaced-repetition). Anki’s algorithm differs from SM-2 in some respects. Notably: * SM-2 defines an initial interval of 1 day then 6 days. With Anki, you have full control over the length of the initial learning steps. Anki understands that it can be necessary to see a new card a number of times before you’re able to memorize it, and those initial "failures" don’t mean you need to be punished by being shown the failed card many times over the course of a few days. Performance during the learning stage does not reflect performance in the retaining stage. * Anki uses 4 choices for answering review cards, not 6. There is only one *fail* choice, not 3. The reason for this is that failure comprises a small amount of total reviews, and thus adjusting a card’s ease can be sufficiently done by simply varying the positive answers. * Answering cards later than scheduled will be factored into the next interval calculation, so you receive a boost to cards that you were late in answering but still remembered. * Like SM-2, Anki’s failure button resets the card interval by default. But the user can choose to have the card’s interval reduced instead of being reset completely. Also, you can elect to review failed mature cards on a different day, instead of the same day. * *Remembered easily* not only increments the ease factor, but adds an extra bonus to the current interval calculation. Thus, answering *remembered easily* is a little more aggressive than the standard SM-2 algorithm. * Successive failures while cards are in learning do not result in further decreases to the card’s ease. A common complaint with the standard SM-2 algorithm is that repeated failings of a card cause the card to get stuck in "low interval hell". In Anki, the initial acquisition process does not influence a card’s ease. ## FSRS FSRS aims to learn your memory patterns and schedule reviews more efficiently than SM-2. FSRS is based on the "Three Component Model of Memory". The model asserts that three variables are sufficient to describe the status of a unitary memory in a human brain. These three variables include: * Retrievability (R): The probability that the person can successfully recall a particular information at a given moment. It depends on the time elapsed since the last review and the memory stability (S). * Stability (S): The time, in days, required for R to decrease from 100% to 90%. For example, S = 365 means that an entire year will pass before the probability of recalling a particular card drops to 90%. * Difficulty (D): The inherent complexity of a particular information. It represents how difficult it is to increase memory stability after a review. In FSRS, these three values are collectively called the "memory state". The value of R changes daily, while D and S change only after a card has been reviewed. Each card has its own DSR values, in other words, each card has its own memory state. To accurately estimate the DSR values, FSRS analyzes the user's review history and uses machine learning to find parameters that provide the best fit to the review history. Note that the users should not tweak the parameters manually. If you want to adjust the scheduling, all you need to do is choose an appropriate value of desired retention. With FSRS, users can target a specific value of retention, allowing them to balance how much they remember and how many reviews they have to do. Higher retention leads to more reviews per day. Aside from allowing users to easily control their retention, FSRS has some other advantages when compared to Anki's default algorithm. With FSRS, users have to do fewer reviews than with Anki's default algorithm to achieve the same retention level. FSRS is also much better at scheduling cards that have been reviewed with a delay, for example, if the user took a break from Anki for a few weeks or months. The scheduling code can be found in `rslib/src/scheduler/states`. Here is a summary (see the [deck options](/manual/deck-options) section of the manual for the options that are mentioned in *italics*): ## Learning/Relearning Cards If you press…​ * Again\ Moves the card back to the first step setted in [Learning/Relearning Steps.](/manual/deck-options?#learning-steps) * Hard\ Repeats the current step after the first step, and is the average of Again and Good. * Good\ Moves the card to the [next step](/manual/deck-options?#learning-steps). If the card was on the final step, the card is converted into a review card (it 'graduates'). * Easy Immediately converts the card into a review card. New cards have no ease, so no matter how many times you press 'Again' or 'Hard', the future ease factor of the card won't be affected. The same can be said about relearning cards: pressing 'Again' or 'Hard' won't have any effect over the card's ease. ## Review Cards In SM-2, once a card is graduated, it gets an ease factor. By default is 2.5, but you can set another value using the [Deck Options](/manual/deck-options?#starting-ease). If you press…​ * Again\ The card is placed into relearning mode, the ease is decreased by 20 percentage points (that is, 20 is subtracted from the *ease* value, which is in units of percentage points), and the current interval is multiplied by the value of *new interval* (this interval will be used when the card exits relearning mode). * Hard\ The card’s ease is decreased by 15 percentage points and the current interval is multiplied by the value of *hard interval* (1.2 by default) * Good\ The current interval is multiplied by the current ease. The ease is unchanged. * Easy\ The current interval is multiplied by the current ease times the *easy bonus* and the ease is increased by 15 percentage points. For Hard, Good, and Easy, the next interval is additionally multiplied by the *interval modifier*. If the card is being reviewed late, additional days will be added to the current interval, as described in a [previous FAQ.](/faqs/due-times-after-a-break) In FSRS, once a card is reviewed at least once, it gets assigned DSR values. If you press…​ * Again\ The card is placed into relearning mode, stability significantly decreases, and difficulty significantly increases. * Hard\ The card’s stability either increases or stays the same, and difficulty moderately increases. * Good\ The card’s stability increases, and difficulty may increase or decrease very slightly. * Easy\ The card’s stability significantly increases, and difficulty moderately decreases. ## Limitations When using SM-2, there are a few limitations on the scheduling values that cards can take. Eases will never be decreased below 130%; SuperMemo’s research has shown that eases below 130% tend to result in cards becoming due more often than is useful and annoying users. Intervals will never be increased beyond the value of *maximum interval*. Finally, all new intervals (except Again) will always be at least one day longer than the previous interval. ## Why doesn’t Anki use SuperMemo’s latest algorithm? The simple answer is that SuperMemo’s latest algorithm is proprietary, and requires licensing. As Anki is an open source application, it can only make use of algorithms that have been made freely available, such as FSRS. [Preliminary tests](https://github.com/open-spaced-repetition/fsrs-vs-sm17) seem to indicate FSRS is roughly on par with SM-17.