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System Designer

Business · 3 minutes

GPUs, tokens and fallbacks

Serving AI answers is slow and expensive, so cache, limit, and have a fallback.

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Serving AI answers is slow and expensive, so cache, limit, and have a fallback.

Costly answers

A chatbot answer needs a GPU, a chip that costs a few dollars an hour to rent (approx.) and can serve only a few conversations at once. Answers are measured in tokens, roughly three quarters of a word. Longer answers take longer and cost more, and the number of GPUs you can get is limited.

Smaller and cached

Repeated answers can skip generation. Count the uncached tokens and capacity needed to drain the batch before choosing longer answers.

Try the idea

A GPU shortage hits at noon. Add a fallback and remember repeated questions.

Key numbers

One GPU
≈ $2 to $4 an hour. rented, approx.
A short answer
≈ 300 tokens. about 225 words, approx.
Model response time
≈ 2 to 10 s. approx.

Check your reasoning

Think through these questions before opening the lesson. In the game you can test the idea and compare your reasoning.

  • Why is AI serving expensive?
  • A semantic cache helps when:
  • What is a good plan for a GPU shortage?

The key point

Cache, cap and fall back; GPUs are the scarcest part of the system.

Practise this idea

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