Guide · AI Cost Meter

1 Million Tokens, Visualized

LLM pricing is quoted per million tokens — but "a million tokens" is an abstract unit. Here is what it actually looks like in words, pages, and books, plus what it costs across the major APIs.

The one-line answer

1 million tokens ≈ 750,000 words ≈ 1,500 single-spaced pages ≈ about 10 average novels. The math comes from OpenAI's widely cited rule of thumb: 1 token covers roughly 0.75 words of English text (equivalently, ~4 characters).

1M tokens in units you can picture

Words (English)~750,000
Characters~4,000,000
Single-spaced pages (~500 words / page)~1,500
Double-spaced pages (~250 words / page)~3,000
Average novels (~80,000 words)~9–10
Harry Potter and the Sorcerer's Stone (~77k words)~9.7 copies
The Great Gatsby (~47k words)~16 copies
The King James Bible (~783k words)~1 full Bible
Spoken audio at 150 wpm~83 hours

Estimates round to the nearest useful figure. Exact token counts vary by tokenizer (OpenAI's tiktoken, Anthropic's tokenizer, Gemini's SentencePiece), by language (non-English text often tokenizes 2–3× denser), and by content type (code and JSON pack more tokens per character than prose).

What does 1 million tokens cost?

Prices below are per 1M tokens (USD), so this is literally the per-million-token sticker price for each model — input vs. output.

Model1M input1M output
Gemini 1.5 Flash$0.075$0.30
GPT-4o mini$0.15$0.60
Gemini 1.5 Pro$1.25$5.00
GPT-4o$2.50$10.00
Claude 3.5 Sonnet$3.00$15.00
Claude Opus 4.8$5.00$25.00

Read this way: feeding all 10 novels into GPT-4o as input costs $2.50; asking it to generate 10 novels back costs $10. Same amount of text, 4× the price — because output tokens are compute-heavier than input tokens.

Where the 0.75 words / token rule comes from

Modern LLMs use byte-pair encoding (BPE) or SentencePiece tokenizers. Common English words like "the", "and", "of" are usually a single token. Longer or rarer words split into pieces — "tokenization" typically breaks into "token" + "ization". Averaged over natural English prose, this comes out to ~0.75 words per token, or ~4 characters per token. That is the heuristic OpenAI publishes and what this site's calculator uses.

Content types that drift from the average:

  • Code and JSON tokenize denser — braces, quotes, and identifiers eat tokens fast. Budget ~30% more tokens than the same character count of prose.
  • Non-English languages (especially CJK, Arabic, Hindi) can be 2–3× denser per character. A 1,000-word Japanese document may consume more tokens than a 1,000-word English one.
  • System prompts repeat on every call. A 2,000-token system prompt hit 500,000 times a month = 1 billion tokens before the user even types.

Budgeting rule of thumb

When you see a monthly cost quote like "$50 / month on GPT-4o", translate it back to human units:

  • $50 on GPT-4o input ≈ 20M tokens ≈ 15M words ≈ ~200 novels of context read per month.
  • $50 on GPT-4o output ≈ 5M tokens ≈ 3.75M words ≈ ~50 novels generated per month.
  • $50 on Gemini 1.5 Flash input ≈ 666M tokens ≈ ~6,600 novels — two orders of magnitude more text for the same dollar.

Try it on your own text

Paste any prompt into the calculator and it will show the token count and monthly cost across every major model — 100% client-side, nothing uploaded.

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