This is one of the most significant technical advantages NotebookLM has, as its entire purpose is to work with large amounts of your specific content.
The "number of tokens supported" is technically called the context window. Think of it as the AI's short-term memory for a single conversation or query. A larger context window means it can "read" and "remember" much more information at once to answer your questions.
Here is a comparison table that translates these technical limits into practical terms.
Comparison of Context Window: Google NotebookLM vs. ChatGPT
| Platform | Token Limit (Context Window) | Approx. Number of Words¹ | Approx. Number of PDF Pages² | Key Use Case & Implication |
| ChatGPT (Free Tier) |
~4,000 - 16,000 tokens | ~3,000 - 12,000 words | ~6 - 24 pages | Good for short documents. Can summarize a single article, a chapter, or a short report. It will forget the beginning of a long document by the time it reaches the end. |
| ChatGPT Plus (Paid Tier) | 128,000 tokens | ~96,000 words | ~192 pages | Excellent for long-form content. Can analyze an entire novel, a detailed financial report, or a lengthy research paper in a single go. This is a very powerful capability. |
| Google NotebookLM |
1,000,000 tokens |
~750,000 words | ~1,500 pages | Designed for massive research projects. Can analyze multiple books, entire codebases, or years of financial statements at the same time. This scale is fundamentally different. |
| Google NotebookLM | 2,000,000 tokens (across 50 sources) |
~1,500,000 words | ~3,000 pages | You can load a small library of content into a single project and the AI can draw connections across all of it, even if you don't reference it all in one query. |
¹ Word Count Assumption: The conversion from tokens to words is an approximation. The common rule of thumb is that 100 tokens ≈ 75 words.
² PDF Page Assumption: This is a rough estimate. The number of words per page can vary dramatically based on font size, margins, spacing, and images. This calculation assumes a dense, text-heavy document with ~500 words per page (e.g., a standard research paper or book).
Note: the above is based on the information at the time of writing. The number of tokens will increase over time as each LLM tries to outshine each other.
What This Means to You
You can frame it like this:
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ChatGPT (Free): You can ask it to analyze a few pages of your meeting notes.
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ChatGPT Plus (Paid): You can upload your company's entire 150-page quarterly report and ask it to find the key risks. This is very impressive.
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Google NotebookLM: You can upload your company's last ten quarterly reports (totaling 1,500 pages), and then ask: "What financial trends have emerged over the last two and a half years, and what were the most frequently cited risks across all reports?"
That last query is something ChatGPT simply cannot do because the source material won't fit in its "memory" (context window).
The big deal isn't just that the number is bigger; it's what that size enables. NotebookLM's massive context window is the core technology that allows it to be a true research assistant across a large body of work, rather than just an analyst of a single document.
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