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What is Mochi?
Mochi is a spaced-repetition flashcard app built around Markdown notes. You write cards in Markdown — headings, lists, code blocks and images included — and Mochi schedules them for review at intervals meant to help you remember them long term. It runs on Mac, Windows, Linux, iOS and Android, and there is a browser version you can try without installing anything.
It is aimed at two overlapping groups: language learners and people who study from their own notes.
Language learning. Cards can include built-in dictionary lookups, text-to-speech for pronunciation and listening practice, image search for visual cues, and auto-translation to or from your target language. If you are building vocabulary decks, this removes a lot of switching between apps.
Note-taking and studying. Notes support two-way references (backlinks) so ideas connect to each other, tags for grouping, and saved filters and views for finding things again. AI-generated text can produce example sentences or study prompts. The idea is that your reading or research notes become review material rather than a separate pile of cards.
Two design choices matter in practice:
- Local first. Your data lives on your device and syncs when you are online. That is good for offline study and for people who dislike cloud-dependent tools, but it also means you should think about your own backup habits.
- Markdown as the format. This is the main trade-off against simpler flashcard apps. Markdown gives you fast typing, reusable formatting and portable plain text, but it is less friendly if you prefer a mouse-driven editor or want a highly graphical card layout.
A user quoted on the site, Andres B., says he uses it daily and finds the interface ahead of Anki's, having previously used Anki for months. Treat that as one person's comparison of interface feel, not a claim that Mochi does everything Anki does — Anki has a large shared deck ecosystem and a long history of add-ons, which is a real difference if you rely on either.
A practical next step: pick one narrow use case — say, 20 vocabulary words for a language you are studying — and build that deck first. If typing in Markdown feels natural and the review schedule keeps you returning, the note-taking and backlink features are worth exploring. If you want ready-made shared decks or a purely click-based editor, compare against Anki before committing.
How does Mochi's spaced repetition system compare to Anki for daily study?
Mochi's spaced repetition is built for daily study that feels lighter and more integrated than Anki's, but Anki still wins on raw scheduling control and ecosystem depth. The trade-off is polish and note-taking flow versus granular tuning and shared decks.
Where they differ for a daily habit
| Aspect | Mochi | Anki |
|---|---|---|
| Card creation | Markdown notes that become flashcards; references and backlinks connect ideas | Plain fields plus templates; more setup, more flexibility |
| Review feel | Clean interface, keybinds, pasteable media, local-first sync | Functional but denser; add-ons shape the experience |
| Language tools | Built-in dictionaries, text-to-speech, image search, auto-translate | Mostly via add-ons or manual setup |
| Scheduling control | Smart review schedules, presented as simple | Highly tunable learning steps, ease, intervals |
| Ecosystem | Smaller; focused on notes and study | Huge shared deck library and long-standing community |
Mochi's page describes spaced repetition as "smart review schedules that help you remember more for longer," with data stored locally and synced when online. It also lists references, tags, filters and saved views, and AI-generated example sentences. Anki's reputation rests on algorithmic control and a vast deck ecosystem, which Mochi does not claim to match.
What daily use actually looks like
If your routine is "read something, take notes, turn it into cards, review on phone and laptop," Mochi's Markdown-plus-references approach reduces friction. A learner reviewing vocabulary can look up a word, hear it spoken, and attach an image without leaving the app. A student can link a note to related notes and let the review system surface them over time.
Anki suits a different daily pattern: you want to import a large shared deck, adjust intervals, or rely on add-ons for statistics and automation. The cost is more time on configuration and a less pleasant note-taking surface.
One user quoted on Mochi's page, Andres B., says he used Anki for months but finds Mochi's UX "waay ahead." That is his observation, not a measured comparison. Practically, UX matters most when it keeps you reviewing daily; scheduling depth matters most when you need precise control over a large, long-term collection.
How to decide
- Choose Mochi if you want notes and flashcards in one place, value Markdown and linking, and prefer defaults over tuning.
- Choose Anki if you depend on shared decks, add-ons, or fine-grained interval control.
- Try both for two weeks with the same material and track which one you actually open each day.
For a concrete test, take ten vocabulary words and ten concepts from a recent reading. Build them in Mochi using Markdown and a reference link, then build the same set in Anki. Whichever you finish faster and review more consistently is the better daily fit.
Can I use Mochi offline, and how does syncing work across devices?
Yes. Mochi is designed local-first: your cards and notes live on your device, so you can study without an internet connection, and syncing happens when you're back online. It runs on Mac, Windows, Linux, iOS, and Android, so the same library can follow you across desktop and mobile.
H3 What that means in practice
- Offline studying: Reviews, note-taking, and Markdown editing work from local storage. A flight, commute, or spotty Wi-Fi won't block a study session.
- Sync on reconnect: Changes made offline are pushed to your other devices once you have a connection, rather than requiring you to be online the whole time.
- Cross-device continuity: Start a deck on a laptop and continue on a phone; the local copy plus sync is what keeps them aligned.
H3 Trade-offs to plan for Local-first is excellent for speed and for keeping your material usable without a connection, but it puts more weight on sync behaving well. If two devices edit the same card while both are offline, expect to check for conflicts or duplicated edits after they reconnect. It also means your devices need enough local storage for your media, since images and audio are part of the library.
H3 A practical test Make one card on your phone in airplane mode, add a second card on your desktop, then bring both online and confirm both appear everywhere. That single check tells you whether your sync setup fits how you actually study.
If you want a second opinion on how local-first flashcard tools compare, Anki is the long-standing alternative, though its sync model and interface differ.
What's the best way to create language flashcards with dictionaries and text-to-speech in Mochi?
Build the card around the word, not a translation pair. In Mochi, the workflow that fits the page evidence is: write the note in Markdown, look the term up with the built-in dictionaries without leaving the note, add text-to-speech so you hear it, and optionally pull in an image or an auto-translation. Then let spaced repetition scheduling decide when you see it again.
A practical card recipe
- Front: the target-language word or phrase in a heading, with an example sentence below it.
- Back: definition from the dictionary lookup, plus part of speech and any gender or article.
- Audio: attach text-to-speech to the word and to the example sentence, so you practise the term in isolation and in context.
- Image: use image search when the word is concrete; skip it for abstract grammar points where a picture adds noise.
- Extra: an auto-translated line, hidden or on the back, so you are not reading the answer before you recall it.
- Tag the note by language, topic and difficulty so filters and saved views can build a session for you.
Why this beats a bare word list
Recognition and production are different skills. Hearing the card spoken trains listening and pronunciation; the dictionary lookup keeps the definition accurate rather than invented; the example sentence gives you grammar in context. Markdown formatting lets you bold the target word, nest a list of senses, or include a code block if you are studying something technical.
Trade-offs to watch
- Text-to-speech is only as good as its pronunciation for your language; for tonal or heavily irregular languages, treat it as a prompt, not a model.
- Auto-translate is convenient but can flatten nuance. For close synonyms, write your own distinction in the note.
- Image search makes concrete nouns stick but slows you down; batch it rather than doing it per card.
- AI-generated example sentences are useful for volume, but check them if you are studying a language you cannot yet judge.
Where Mochi fits
The local-first storage and Markdown base are the two features that shape this workflow: your notes live on your device and sync when online, and everything is plain formatted text rather than a rigid field layout. If you already keep vocabulary notes, you can convert them into reviewable cards instead of maintaining a second system. The page lists availability for Mac, Windows, Linux, iOS and Android, and a pricing page with a $0 tier shown, so you can test the loop before committing.
If you want a second opinion on the spaced-repetition side or on language-specific card design, the communities around Anki and the general language-learning discussion on Reddit are useful, but Mochi's own documentation and forums are the place to check how its dictionary, text-to-speech and reference features actually behave in your target language.
Next step: pick ten words you keep forgetting, build one card each with the recipe above, and review them for a week. If recall improves without the cards feeling like a chore, scale the format; if not, drop the image or auto-translate step first, since those are the slowest parts of the loop.
How do I turn my Markdown notes into a connected knowledge base using references and tags?
Mochi treats notes and flashcards as the same object: you write in Markdown, then attach spaced-repetition review to whatever you want to remember. The connection layer is built from two simple mechanics — references (links between notes) and tags — and the page evidence describes both as core features rather than add-ons.
The basic loop
- Write a note in Markdown. Headings, lists and code blocks format normally, so a note can start as ordinary reading notes.
- Tag it immediately. Tags are described as simple and flexible, which suits broad groupings like
#spanish,#thesis,#chapter-3rather than a rigid folder tree. - Add references. Linking notes both ways builds a connected web of ideas, so a note about a concept can point to the source note that produced it, and the source note shows the connection back.
- Turn the parts worth remembering into cards. Because notes and flashcards share one format, you can card a definition, a sentence pattern or an example without copying it into a separate app.
- Review on a schedule. Spaced repetition decides when each card returns, so the knowledge base stays active instead of becoming an archive.
A concrete scenario
Suppose you are reading a book in your target language. You keep one Markdown note per chapter, tag each #book-title and #vocabulary, and reference the author or theme notes you already have. New words become cards inside the chapter note, so the card carries its original context. During review you see the word; when you want the context back, the reference takes you to the chapter. Over a few months the tags give you broad views and the references give you the specific paths between ideas.
References vs. tags
| References | Tags | |
|---|---|---|
| Best for | Specific, meaningful links between two notes | Broad grouping and retrieval |
| Granularity | One note to one note | Many notes to one label |
| Grows into | A web you navigate | Saved views and filters |
| Risk | Link sprawl if used casually | Tag sprawl if you invent new ones freely |
The practical rule: use tags for categories you would search by, and references for relationships you would want to follow. If a tag would only ever apply to one note, it is probably a reference instead.
Keeping it usable
- Decide on a small tag vocabulary early and reuse it; the page notes filters, saved views and search as the tools that make tags pay off.
- Reference in both directions where it matters, since backlinks are what turn a pile of notes into a navigable base.
- Keep cards short and note bodies long. The note holds the context; the card holds the prompt.
- Do not card everything. Spaced repetition is only efficient if the review queue stays meaningful.
Mochi is available on Mac, Windows, Linux, iOS and Android, with data stored locally and synced when online, and there is a free tier shown as $0 plus a pricing page — check Mochi for current plan details. If you already work in Markdown and want review and linking in one place, this fits well; if you need a large shared team wiki, a dedicated notes platform may suit better.
Is the free plan enough for serious learners, or should I upgrade to a paid subscription?
The free plan is enough to test whether Mochi's spaced-repetition workflow fits you, but it is not designed to be the long-term home for a serious learner's whole collection. The page lists a $0 tier alongside "Pricing & Plans," and the feature set it advertises — markdown cards, smart review schedules, local-first storage, references, tags, filters — is the core of the product rather than a stripped-down demo. What you are really deciding is how much you will depend on sync and cross-device study.
Where free usually suffices
- You study on one device and can keep your data local.
- Your deck is small enough that losing cloud sync or extra storage would not hurt.
- You want to learn the markdown-and-backlinks workflow before committing money.
Where upgrading makes sense
- You want the same deck on Mac, Windows, Linux, iOS and Android without manual transfer.
- You are building a large, long-term collection and care about continuous sync.
- You rely on cross-device review during commutes, classes or lab time.
A practical way to decide
Spend two weeks building one real deck — say, 200 vocabulary cards for a language course or a semester's worth of lecture notes. Track two things: how often you wanted to review on a second device, and whether the free tier's limits interrupted that. If sync or capacity became the bottleneck, upgrade; if not, stay free and revisit after your next exam cycle.
One caveat from the page itself: the testimonials are enthusiastic but anonymous-ish and clearly selected for marketing, so treat them as tone, not evidence. The $0 figure is the only concrete price signal here; check the pricing page for what the paid tiers actually include before committing. If you already use another spaced-repetition tool, comparing its official pricing directly is the fastest sanity check — for instance Anki.
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