How much does it cost?
Words made simple
A few useful meanings before you read the explanation.
- Token
- A small piece of text processed by a model. It may be a whole word, part of a word, or punctuation.
- Embedding
- A list of numbers that represents the meaning of some content. Similar meanings can produce nearby lists of numbers.
- Agent
- An application that uses a model to choose its next action within defined limits. It can use tools and continue through several steps.
More words from this lesson
- Tenant
- A customer or organization whose data must stay separate from other customers in a shared application.
- Reranking
- Checking an initial set of search results again and putting the most useful ones nearer the top.
- Batching
- Processing several pieces of work together. It can improve efficiency, but waiting to fill a batch can add delay.
- Caching
- Keeping a result so it can be reused instead of calculated or fetched again. Cached data needs expiry and access controls appropriate to its use.
- Count every model/tool call, embedding/reranking, infrastructure, retries, and review workload.
- Optimize cost per successful task subject to quality and privacy constraints.
- Use context selection, templates, smaller models, caching, batching, and strict agent budgets where evaluated.
Budget policy: per-user/tenant limits, bounded step count, total tokens and deadline, overload behavior, and alerts for unusual call amplification.
Can you explain it without the notes?
How much does it cost?
Use your own words. Explain an example and one limitation before checking the explanation.
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Count every model/tool call, embedding/reranking, infrastructure, retries, and review workload. Optimize cost per successful task subject to quality and privacy constraints. Use context selection, templates, smaller models, caching, batching, and strict agent…
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Practice this conceptAdapted from 13_AI.MD · “11. How much does it cost?”. Examples are study fragments; framework behavior can depend on your version.