What will this actually cost per month? A method for pricing an LLM workload before you commit
You are picking a model for a feature that is about to ship. The provider pages give you a price per million tokens. Your product manager asks what the monthly bill will be. You do not have a good answer, because the price you were given is denominated in a unit nobody in the room thinks in. That gap is where most model-selection decisions get made badly. People pick on benchmark scores and…
To determine the monthly cost of using an LLM (Large Language Model) for a specific workload, follow these four steps:
1. Describe the workload in tokens:
- Count the tokens per call, including the system prompt, retrieved context, conversation history, and output tokens.
- Multiply the input tokens per call by the number of calls per day and then by the number of days per month.
2. Perform the arithmetic:
- Calculate the total input and output tokens per month.
- Use the pricing per million input tokens and per million output tokens provided by the model provider.
- Multiply the total input and output tokens by the respective prices to get the monthly cost for each.
3. Consider the escalation rates and actual completion costs:
- Account for the percentage of conversations that require retries or escalations to human support.
- Calculate the additional costs associated with these escalations, including the cost per escalation and human time spent.
- Determine the cost per completed task by adding the model spend and escalation costs.
4. Choose the appropriate tier based on the task type:
- Frontier tier: ideal for judgment work that requires high accuracy and cannot tolerate errors, such as architecture decisions or security-sensitive changes.
- Mid tier: suitable for routine operations, file edits, refactors, routine operations, and research where the escalation rate is low.
- Monitor the escalation rate and human time spent for each tier to identify the most cost-effective option.
By following these steps and using your own workload data, you can accurately estimate the monthly cost of using an LLM and make informed decisions based on your specific use case.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
