AnKing Deck Alternative: AI-Generated USMLE Flashcards From Your Own Notes

AnKing v12 ships with roughly 35,000 cards. If you do the math at a reasonable 200-300 reviews per day at full maturity, that is something like 60 to 90 days of pure review time before the deck stabilizes, ignoring the new cards you have to introduce along the way.

That number is the reason "anking alternative" is a search students type at 1am during M2. They opened the deck late, they have their own lecture notes, or their school's curriculum does not map cleanly to First Aid, and the standard "just mature AnKing" advice no longer fits.

This post is for those students. Not a hit piece on AnKing - it is genuinely the best community deck that exists - but an honest look at when a 35K premade deck is the wrong tool, and what to do instead.

What AnKing is, briefly

AnKing is the consolidated community deck for USMLE Step 1 and Step 2 CK. It started as a merge of Lightyear, Lolnotacop, Zanki, and Pepper, then got cleaned up, retagged, and shipped as a single living deck with a team maintaining it across versions.

Most of the cards are cloze deletions of First Aid facts, with extra coverage from Boards and Beyond, Pathoma, Sketchy, UWorld, and Amboss. Tags map to FA chapters and to the resources above, so you can suspend everything except what you covered this week.

It is the standard for a reason. The card phrasing is tight, the community has surfaced edge cases over a decade, and there is a mature ecosystem of tagging tools, add-ons, and shared workflows built around it.

The honest critique

Three things to be straight about.

Maturity timelines are brutal. Mature means the card has graduated to long intervals - you only see it every few weeks. To get there, you have to do the card multiple times across rising intervals. With 35K cards, even unsuspending only the "high-yield" subset still leaves you with 8K-15K cards depending on tags, and that is a real wall if you start past the optimal window.

Bloat is real. Some cards are 12 years old. Some test minutiae that has not been on a Step exam since 2017. Some are duplicates that survived the merge. The maintainers prune aggressively, but a deck this size cannot help carrying some dead weight.

Version updates create friction. When v13 ships, cards you suspended can get unsuspended (because tag schemas changed), card content can shift, and your scheduling history sometimes loses fidelity through the update path. The official migration scripts are good, but they are not magic.

None of this is a reason to abandon AnKing. It is a reason to be honest about who the deck is built for: a student who started in M1, kept up daily, and has time to mature it before dedicated.

Why students search for "AnKing alternative"

The four most common situations.

You started M2 with no cards reviewed. You meant to start in M1, you did not, and now you have 12 months until dedicated. Maturing 35K cards in 12 months while also doing UWorld, NBMEs, and your shelf rotations is not a real plan.

You have your own M1 lecture notes and want cards from those. Your school's pathology block ran for 9 weeks and your professor emphasized 8 topics that are barely in First Aid. AnKing covers FA. It does not cover Dr. Whoever's slide deck on her own research interest that will absolutely be on the shelf.

You are a non-trad or second-degree student. Your curriculum is integrated, organ-system based, or accelerated, and the assumption that everyone is doing Bros + Sketchy + Pathoma + FA in parallel does not match your day. You need cards aligned to your lectures, not to a resource bundle.

You want cards from your own slides. AnKing covers shared board-prep resources. It does not contain your school's anatomy lab photos, your histology professor's slides, or your cardiology attending's ECG of the week.

If you are in any of those four buckets, "just mature AnKing" is bad advice. You need a way to make cards from your own material, fast.

The AI alternative: cards from your uploads

The other path is to generate flashcards directly from your notes, lecture slides, PDFs, or textbook chapters. Upload the material and get back question-and-answer cards you can review in the same active-recall workflow.

Scholarly's flashcards feature does this. You drop in a lecture PDF, a PowerPoint, a First Aid section, or your own handwritten notes, and you get back a question-and-answer deck generated from that material. PDF to flashcards handles textbook chapters and scanned notes. If you specifically want AnKing-style {{c1::blanks}}, the separate cloze deletion generator can draft cloze text for you to review and paste into Anki; it does not change the flashcard deck's export format.

On paid plans, the cards export to Anki as a .apkg file containing basic question-and-answer notes, so you can review them alongside AnKing. The export does not carry Scholarly tags, citations, or review history.

The "use both" workflow

This is what most people who try AI cards actually settle on. Not a replacement for AnKing, a supplement.

1. Keep AnKing as your high-yield FA backbone. Unsuspend the subset that matches what you are currently covering. Do those reviews daily.
2. Generate AI cards from your school's lectures. For every week of class, upload the slide deck or your notes, generate 30-80 cards, and add them to a separate "School" deck inside Anki.
3. Generate AI cards from your weak areas. When you bomb a UWorld block on renal acid-base, upload the explanations or the relevant FA section and generate targeted cards on the specific gaps.
4. Generate AI cards from board prep resources your school emphasizes that AnKing does not cover. Some schools push Costanzo physio, some push BRS path - AnKing's coverage of these is incomplete by design.

The split is roughly: AnKing for the universal high-yield, AI cards for everything your specific curriculum needs that AnKing does not cover. You end up with one fewer source of FOMO, because the gaps in AnKing are filled by your own material instead of a vague feeling that you are missing something.

Comparison: AnKing vs Brosencephalon vs Lightyear vs AI-generated

Deck	Cards	Best for	Friction
AnKing v12	~35,000	Students who start M1, follow FA + Bros/B&B closely	Maturity timeline, bloat, version updates
Brosencephalon (legacy)	~17,000	Historical reference, still loved by some	No longer maintained, missing recent resources
Lightyear	~25,000	Boards and Beyond-aligned learners	Lower coverage of Step 2 material
AI-generated (Scholarly)	As many as you need from your own material	M2 starters, non-trads, lecture-heavy schools	Cards are personalized; no community-vetted tag tree

The AI-generated row is the column that does not exist anywhere else: cards built specifically from your material, in any quantity, with no maturity backlog because the deck did not exist before you uploaded.

Where AnKing still wins

Be honest with yourself.

Community-vetted high-yield tags. A decade of medical students has marked which cards predict UWorld and NBME performance. The "AnKing_Net" tag, the "high_yield" subtag, the resource crosswalks - that institutional memory does not exist for any new deck.

Mature shared workflows. AnKi Hub, AnKing's official updates, AnkiConnect-based add-ons, the cloze-one-by-one and pass/fail workflows - all built around the standard tag schema.

Brosencephalon-era depth on classic topics. Some of those cards are 8 years old and still beat anything generated today on the genetics and embryo content, because they have been refined by thousands of medical students suggesting edits.

If you are an M1 with 18+ months until dedicated, AnKing is still the right backbone. The argument here is not "switch off AnKing" - it is "supplement AnKing with your own material" or "use AI cards if AnKing was never going to fit your timeline."

Where AI cards win

Personalization. Your school's slides, your attending's pet topics, your weak areas. A community deck cannot know those things.

Speed. Generation automates the first draft of a lecture deck. You still need to review and prune the cards, but you do not have to type every question and answer from scratch.

No maturity backlog. A deck of 200 cards from this week's lecture does not have a 60-day on-ramp. You start reviewing today, the cards are mature in a few weeks, done.

Coverage of your lecture's quirks. The 8 topics your professor emphasized that are barely in First Aid. The ECG patterns your cardio attending tested in clinic. The drug names your pharm professor invented mnemonics for. AnKing cannot cover those because they are local.

A note on Anki itself

If you are reading this and have not yet committed to Anki as the review engine, both AnKing and AI-generated cards can live inside Anki. The scheduler (SM-2 historically, now FSRS by default in modern Anki) does not care where a standard basic note came from. Cards exported from Scholarly arrive as new basic question-and-answer notes and can then be scheduled by Anki like any other new card.

You do not have to pick a flashcard ecosystem. You pick a card source.

FAQ

How does generated-card quality compare to AnKing? AnKing cards have been hand-edited for years and the phrasing is tight. Scholarly instead drafts standard question-and-answer cards from your specific material. Review them before studying: AnKing wins on community-vetted craft, while generated cards win on coverage of your own lectures and weak areas.

Does Scholarly support FSRS? Not for reviewing inside Scholarly. Our built-in review uses an SM-2 style scheduler, with a per-card ease factor and interval. If you want FSRS, paid plans can export the cards as a standard .apkg; once they are in your Anki collection, FSRS handles them like any other new basic note.

Can I export to Anki? Yes, on paid plans. Cards generated in Scholarly export as a .apkg file containing Anki basic notes. Import the file into Anki and review the cards as normal. Scholarly tags, citations, and review history are not preserved.

Does it do image occlusion? No. Scholarly can use uploaded slides, lecture screenshots, anatomy images, and diagrams as source material for standard question-and-answer cards, but it does not currently create masked image-occlusion regions or export image-occlusion note types. If image occlusion is central to your workflow, AnKing or Anki's own image-occlusion tools remain the better fit.

Can I import AnKing tags into the AI cards? No. Scholarly can import supported basic and cloze notes from an .apkg file, but it converts them into its own question-and-answer format and does not preserve Anki's tag hierarchy, media layout, scheduling, or review history. For exported Scholarly cards, apply any AnKing-style tags after importing the deck into Anki.

How long does setup take? You can upload a source, generate a deck, and begin reviewing without installing an add-on or learning a shared tag tree. Generation time varies with the source and requested deck size, and the cards still need a human review before you rely on them for exam prep.

What to do this week

If you are an M1 with time, start AnKing the normal way and add AI cards from your lectures alongside it.

If you are an M2 who never started AnKing and dedicated is approaching, generate AI cards from First Aid plus your own weak-area material, skip the 35K maturity wall, and use AnKing's free high-yield subset only for the topics where community-vetted phrasing matters most.

If you are a non-trad or in an integrated curriculum, lean heavier on AI cards from your own lectures, use AnKing as a reference deck rather than a daily review deck, and keep the focus on the material your school actually tests.

The point is not that AnKing is wrong. The point is that "mature AnKing" is one strategy, not the only strategy, and for a lot of students in 2026, it is no longer the right one.