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AI models don’t read words — they read tokens, small chunks of text. Speed, cost and limits are all measured in tokens.

What is a token?

  • About 4 characters or ¾ of a word in English.
  • 100 tokens ≈ 75 words. A full page ≈ 500–700 tokens.
  • Code, numbers and non-English text often use more tokens per word.
  • Images, audio and PDFs are converted into tokens too.

The four kinds of tokens

Output is the expensive part. Asking for “a short answer” or “bullets only” saves more than trimming your question.

Context window

The context window is the most tokens a model can consider at once — history, files and its own answer combined.
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Aura keeps the last 40 turns of a conversation in view and trims older ones in blocks, keeping answers focused and caching effective. Very long prompts (over roughly 100k–272k tokens depending on the model) are billed at a higher tier by providers.

Reasoning effort

  • Low — quick factual answers.
  • Medium — Aura’s default for most chat.
  • High — complex analysis, math and code (Frontier High, Thinking).
More effort means better answers on hard problems, but more output tokens and time.

How this becomes credits

Aura converts real provider token costs into credits. That’s why:
  • A typical Orchestration message costs about ~20 credits (four models answer, then a comparison).
  • Long documents, high reasoning and long answers cost more.
  • Follow-ups in the same chat are often cheaper thanks to prompt caching.

Spend fewer tokens

  1. One topic per chat; start a new chat when the topic changes.
  2. State the format and length you want.
  3. Paste only the relevant part of long documents.
  4. Use Unlimited for everyday questions, Orchestration for high-stakes ones.
  5. Pick Frontier Low or Efficient unless you need High.
The model also reads the whole conversation, attached files and live search results — those are input tokens too.
Yes, providers bill reasoning as output. Aura keeps reasoning at medium by default to balance quality and cost.