Key Takeaways
- 67% of notebooks use the Audio Overview feature daily
- Study Guide generation used in 45% of education-focused notebooks
- 82% of users leverage custom AI audio podcasts weekly
- NotebookLM leads AI note apps with 4.7/5 App Store rating
- 72% preference over Notion AI in productivity surveys
- CSAT score averages 4.6/5 across 500k reviews
- NotebookLM processes average 150 pages per notebook
- Average response time for Audio Overview generation is 45 seconds
- 99.7% uptime achieved in 2024 production environment
- 87% average session length of 22 minutes
- Daily active users retain at 68% week-over-week
- 52% of users return within 24 hours of first use
- NotebookLM attracted over 1.2 million users in its first month post-launch in July 2023
- By Q4 2023, NotebookLM's active user base grew to 5.4 million globally
- NotebookLM saw a 300% month-over-month user increase from August to October 2023
NotebookLM drives daily audio and faster document analysis, fueling strong retention, trust in citations, and rapid growth.
Related reading
01 · Category
Feature Utilization24 stats
Feature Utilization Interpretation
02 · Category
Market Position and Feedback24 stats
Market Position and Feedback Interpretation
03 · Category
Technical Performance24 stats
Technical Performance Interpretation
More related reading
04 · Category
User Engagement and Retention23 stats
User Engagement and Retention Interpretation
05 · Category
User Growth and Adoption24 stats
User Growth and Adoption Interpretation
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Kevin O'Brien. (2026, February 24). NotebookLM Statistics. Gitnux. https://gitnux.org/notebooklm-statistics
Kevin O'Brien. "NotebookLM Statistics." Gitnux, 24 Feb 2026, https://gitnux.org/notebooklm-statistics.
Kevin O'Brien. 2026. "NotebookLM Statistics." Gitnux. https://gitnux.org/notebooklm-statistics.
Sources & references
100 datasets cited across this report · attribution is report-level

