1 million tokens
What does a million tokens actually hold? Convert any token count to words and see what fits inside.
Short answer
1 million tokens ≈ 750,000 English words — about 7–8 full-length novels.
Based on ~0.75 words per token for English prose. Code, tables, and non-English text hold fewer words per million tokens.
Estimated words
≈ 750,000
1.00M tokens × 0.75 words/token
| Tokens | Roughly equals |
|---|---|
| 1,000 tokens | 750 words — a couple of pages |
| 4,000 tokens | 3,000 words — a long article |
| 8,000 tokens | 6,000 words — a short story |
| 32,000 tokens | 24,000 words — a novella |
| 128,000 tokens | 96,000 words — a short novel |
| 200,000 tokens | 150,000 words — 2–3 novels |
| 1,000,000 tokens | 750,000 words — 7–8 novels |
Comparisons assume a ~100,000-word novel and ~500 words per page. Newer tokenizers and non-English text shift these numbers.
Roughly 750,000 English words. That is the widely used rule of thumb (0.75 words per token) for ordinary prose.
About 7–8 full-length novels, assuming ~100,000 words per novel. It is also roughly 1,500 printed pages at 500 words per page.
The word count is roughly comparable, but each model family uses its own tokenizer, so the exact word equivalent shifts a little. Newer tokenizers are generally more efficient, especially outside English.
Claude Fable 5.1, Opus 5, and Sonnet 5, several GPT-5.x models, and Gemini models all offer around 1M input tokens. Check the context window checker to compare exact windows.
It depends on the model. At $2.50 per million input tokens, 1M tokens costs $2.50; at $0.30 it costs $0.30. Use the token cost calculator for exact per-model pricing.
A large monorepo's source code, several novels, a full legal contract suite, or months of conversation history — in a single prompt.