What does a 1M-token context window actually hold?
A 1,048,576-token context window holds roughly 786,000 words of English — about 2,600 paperback pages, or 8 to 9 full-length novels. Move the slider to convert any token count into units you can picture.
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1,048,576
tokens
- Words of English
- 786,432
- 0.75 words per token
- Paperback pages
- 2,621
- 300 words per page
- Full-length novels
- 8.7
- 90,000 words each
- Lines of code
- 104,858
- 10 tokens per line
- Hours of speech
- 87.4
- 150 words per minute
Comparison
How Kimi context windows compare
Kimi K3 is the outlier. Every other current Kimi model sits at 262,144 tokens — a quarter of K3’s window.
- Kimi K31,048,576 tokens · 2,621 pages
- Kimi K2.7 Code262,144 tokens · 655 pages
- Kimi K2.7 Code HighSpeed262,144 tokens · 655 pages
- Kimi K2.6262,144 tokens · 655 pages
- Kimi K2.5262,144 tokens · 655 pages
| Model | Tokens | Words | Pages | Lines of code |
|---|---|---|---|---|
| Kimi K3 | 1,048,576 | 786,432 | 2,621 | 104,858 |
| Kimi K2.7 Code | 262,144 | 196,608 | 655 | 26,214 |
| Kimi K2.7 Code HighSpeed | 262,144 | 196,608 | 655 | 26,214 |
| Kimi K2.6 | 262,144 | 196,608 | 655 | 26,214 |
| Kimi K2.5 | 262,144 | 196,608 | 655 | 26,214 |
FAQ
Understanding context windows
What does a 1 million token context window actually hold?
A 1,048,576-token context window holds roughly 786,000 words of English — about 2,600 paperback pages, or 8 to 9 full-length novels. In code, at roughly 10 tokens per line, it is around 105,000 lines.
Which Kimi model has the largest context window?
Kimi K3 has the largest context window of any Kimi model at 1,048,576 tokens. Kimi K2.7 Code, K2.7 Code HighSpeed, K2.6 and K2.5 all have 262,144-token windows — one quarter the size.
Does the context window include the model’s response?
Yes. The context window is the total budget for input and output combined. If you send a 900,000-token prompt to a model with a 1,048,576-token window, only about 148,000 tokens remain for the response.
Is a bigger context window always better?
No. Larger inputs cost more per request and usually take longer to process, and retrieval accuracy across very long contexts varies by model. A large window is valuable when you genuinely need whole-codebase or whole-document reasoning; otherwise a smaller, cheaper model is often the better choice.
How many tokens is a page of text?
A paperback page holds roughly 300 words, which is about 400 tokens at 0.75 words per token. A dense A4 page of single-spaced text runs closer to 500 words, or around 670 tokens.