Estimate Monthly OpenAI Costs

Estimating monthly OpenAI API costs requires more than knowing how many users your application has.

How the estimate is calculated

Start by estimating five values:

1. Requests per user 2. Monthly active users 3. Average input tokens per request 4. Average output tokens per request 5. Price of the selected model

What can change the total

Suppose an application has 10,000 monthly users, each making 20 AI requests.

That produces:

Plan with a realistic usage example

200,000 requests per month

If each request averages 2,000 input tokens, monthly input usage becomes:

Practical checks before you proceed

400 million tokens

If responses average 500 output tokens:

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100 million output tokens

For the original GPT-5 API pricing of $1.25 per million input tokens and $10 per million output tokens, the simplified estimate is:

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Input = 400 × $1.25 = $500

Output = 100 × $10 = $1,000

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Estimated model cost = $1,500/month

Real costs can differ because of cached input, tools, different models, processing modes, retries, and changing pricing.

Practical checks before you proceed

You should also budget for non-model infrastructure such as databases, vector search, application servers, logging, monitoring, storage, and third-party services.

For an early startup, build three scenarios: low usage, expected usage, and high usage.

Practical checks before you proceed

This helps you understand how costs scale before traffic arrives.

Finally, monitor real token consumption from launch. Estimates are useful for planning, but production behavior is the best source for future budgets.