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anki fsrs settings (2026): fast, stable, low-stress

a practical fsrs setup: desired retention, optimisation cadence, and review-load control — without over-tweaking.

If you’re using Anki seriously, FSRS is the first scheduling change in years that can materially improve efficiency for many learners — but only if you keep the setup simple. Your goal is not “perfect graphs”. Your goal is stable daily review load, predictable memory, and exam-ready recall under time pressure.

What FSRS changes (in plain English)

FSRS adjusts scheduling based on your review history so that the spacing is better matched to your actual forgetting. The setup has two high-leverage levers: (1) your desired retention and (2) how often you optimise parameters.
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Step 1 — Turn on FSRS (once, properly)

In Deck Options, enable FSRS for the deck preset you actually use. Apply it consistently — toggling between schedulers creates noise and makes the system harder to interpret.
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Step 2 — Choose a sensible desired retention (start simple)

Pick a single number as a default (e.g., ~0.90). Higher retention increases review load; lower retention reduces load but increases misses. Start stable, then adjust after you’ve run the system for a few weeks.
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Step 3 — Optimise parameters on a schedule, not emotionally

Optimise when you have enough data (think: weeks of consistent reviews), then leave it alone. A simple cadence (e.g., monthly) prevents endless fiddling and keeps your learning workflow predictable.
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Step 4 — Control review load with deck hygiene

If reviews are exploding, the fix is often not more tuning. Reduce new cards, suspend low-yield cards, and improve card design. Review load is a systems problem, not a motivation problem.
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Step 5 — Use exam proximity to adjust (not perfectionism)

As you approach exam day, your goal shifts from “long-term elegance” to “short-term reliability”. You can temporarily raise retention slightly or reduce new cards — but keep one change at a time.

Common failure mode

Optimising too frequently and changing multiple variables at once. You end up chasing noise, not learning. Fix workflow first (consistent reviews + good cards), then tune FSRS.

Minimum viable FSRS setup

Enable FSRS → set a single desired retention → optimise infrequently → protect review load by controlling new cards and improving card quality. That’s enough to win.
SourceAnki Manual — Deck Options (FSRS + Optimise guidance)
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SourceAnki Forums — Practical notes on FSRS optimisation behaviour
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