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AI Summarizer for Study Notes

Model:
Paste lecture notes, a textbook chapter, a research paper, or any long text and get a study-friendly summary. Pick the output style — bullet list, tight paragraph, hierarchical outline, mind-map-ready markdown, or five key points. Optional study-prompt toggle appends review questions at the end so you can self-quiz.
Works best with 500-10,000 words. Very long documents use /pdf/summarizer/ for page-aware chunking. 0 words
~500 tokens · Qwen 2.5 7B · medium bullet summary
Paste at least a paragraph to summarize.
Your summary
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Summarize lecture notes, textbook chapters, and readings with free AI. Bullet / paragraph / outline / mind-map / 5-key-points formats, optional study questions.

Hvernig á að nota AI Summarizer for Study Notes

1
Sláðu inn innslátt þinn

Sláðu inn texta, hlaða skrá, eða lýsa því sem þú vilt. Engin reikningur þarf.

2
Smelltu til að búa til

AI okkar vinnur beiðni þína í sekúndum með bestu opinberu líkanunum.

3
Sækja og deila

Hlaða niður, afrita eða deila niðurstöðunni þinni. Frjáls til einkanota og viðskipta.

Use this tool via API

Automate this tool from your own code. OpenAI-compatible REST endpoint, Bearer-token auth, no extra SDK required. Token costs match the web interface.

curl -X POST https://api.free.ai/v1/chat/ \
  -H "Authorization: Bearer sk-free-..." \
  -H "Content-Type: application/json" \
  -d '{"model": "qwen7b", "messages": [{"role": "user", "content": "Explain quantum entanglement for a 5-year-old."}]}'

AI Summarizer for Study Notes — FAQ

Free.ai Study Summarizer turns lecture notes, textbook chapters, research papers, or any long text into a study-friendly summary. Choose the output style — bullet list, paragraph, hierarchical outline, mind-map markdown, or 5 key points — plus an optional study-questions section for self-quizzing.

Yes — Qwen 2.5 7B runs on our own GPUs inside the daily token pool. Summary cost scales with input length (~500-3,000 tokens typical). Signed-in free accounts get 10,000 tokens on signup, enough for 10-30 summaries.

Notion AI is $10/user/month; Mem costs $10/month for AI; Glean is enterprise-only at $30+/seat; Otter summaries are locked to your recorded meetings. Free.ai works on any text you paste — no ecosystem lock-in, no subscription, no workspace required.

Five styles: (1) Bullet list — scannable, sub-headed; (2) Paragraph — flowing prose for sharing; (3) Hierarchical outline — preserves source structure; (4) Mind-map markdown — ready for Markmap or Mermaid; (5) 5 key points — exactly five ranked takeaways.

Check "Add 5 study questions at the end" and the summary appends a Study Questions section with 5 self-quiz prompts — mix of recall and analysis. Perfect for pre-exam review. Check "Extract key terms" for a bonus glossary of 5-8 important terms.

Match source (default — preserves the source's register), Explain-like-12, High-school, College, or Expert. Useful for translating dense academic writing into study-group language or tightening lecture notes into exam-grade prose.

No — first summary runs free, no email required. Sign up for 10,000 tokens on signup and generation history.

Best with 500-10,000 words (covers most lecture notes, chapters, and papers). For longer PDFs, use /pdf/summarizer/ which handles page-aware chunking and returns per-page references.

Yes — all 99 languages Free.ai supports. Paste Spanish lecture notes, summary comes back in Spanish with the same style and length settings.

No — the system prompt explicitly instructs the model to summarize only what's in the text, preserve hedges ("may", "suggests"), and not inject examples or opinions. If you see a claim in the summary that isn't in your source, report it — that's a bug.

Yes — download as .md (markdown, good for Notion / Obsidian / Logseq) or .txt (plain, good for email / Google Docs paste). Copy-to-clipboard gives clean text with markdown syntax stripped.

Yes — POST to /v1/chat/ with the summarizer system prompt. Useful for apps that need to bulk-summarize user-uploaded notes. Bearer auth with monthly limits. Snippets at /api/.

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