Token Pricing Explained: Calculate Your AI Costs
Understand LLM token economics with worked examples, hidden cost drivers, and how to budget embeddings and retrieval - not just chat.
Token pricing is the core unit economics of LLM usage, but teams need per-workflow visibility to budget effectively.
Core concepts
Costs come from input tokens (prompt/context) and output tokens (model responses), with retrieval-heavy workflows increasing input usage.
Practical budgeting
Set caps per template, separate sandbox from production spend, and review expensive runs weekly.
Hidden costs
Embeddings, storage, retries, tool calls, and governance overhead can exceed naive token-only estimates.
Conclusion
Translate token usage into business outcomes (time saved, incidents prevented) to align finance and operations.
Meer weten over AI?
Neem contact op voor een gratis intakegesprek en ontdek hoe AI jouw bedrijf kan helpen.
