Reviewed November 10, 2026 · Privacy Needle editorial resources
Start with observable workload
A useful AI API budget begins with daily requests, average prompt tokens, average completion tokens and days used each month. Extrapolating from word count works for rough planning, but measured model token counts are preferable. Different languages, structured payloads and tools change tokenization.
Separate input and output
Most text model APIs publish separate prices per million tokens for inputs and outputs. Monthly input cost equals monthly input tokens multiplied by input price per million, divided by one million. Repeat for outputs and add the components.
Handle caching, batch and other modalities carefully
Provider caching mechanisms differ. Cache writes, cache hits, batch execution, tool use, images, search and audio may have independent charges. Do not compare image generation by applying text-only token prices.
Run sensitivity scenarios
Test a conservative, base and high-volume case. Include rate increases, retry traffic and longer prompts. For a prototype, a low-cost model can be attractive, but accuracy, latency, uptime and data handling requirements still affect total operational cost.
Keep sources current
See the official OpenAI, Anthropic and Google API pricing pages. For modeled costs, use our AI Token API Budget Optimizer.
These are educational estimates. They do not substitute for your provider’s current tariff or professional advice.