LLM API Cost & Inference Hub

How LLM API costs work

LLM API costs are driven by tokens, not by requests alone. Every call to a language model sends input tokens and receives output tokens, and providers charge different rates for each direction. Output tokens usually cost several times more than input tokens, because generating text is sequential work while reading a prompt can be processed in parallel. That single asymmetry shapes almost every budgeting decision on this hub.

Start with the LLM API Cost Calculator when you need a monthly number. Enter your average input and output tokens per request, your daily volume, and a model rate, and it returns a per-request, daily, and monthly estimate. Use it before committing to a model, before quoting a customer, or before scaling a feature that calls a model on every user action.

Use the LLM Pricing Comparison next when the question is which model, not how much in total. It places frontier and budget models side by side on the same token counts, so the trade-off between capability and cost becomes visible instead of guessed. A cheaper model is only a saving if it still completes the task reliably; a stronger model is only worth its premium if the extra quality changes an outcome you care about.

Then use the Prompt Caching Savings Calculator for workloads that repeat large prompts. When the same system instructions, documents, or examples are sent again and again, caching can discount the repeated portion substantially. The calculator models cache hit rates and write costs, so you can see whether caching helps your workload or whether your prompts change too often for it to matter.

Three habits keep API budgets honest. First, measure your real token counts instead of assuming them; retrieved context and long system prompts often dwarf the user's message. Second, separate one-time setup costs from recurring inference costs, because only the second grows with usage. Third, re-check provider rates before launch and after any pricing change, since the rates in these tools are editable precisely because they move.

Everything on this hub runs in your browser. No prompt text, token counts, or budget figures leave your device, and every result shows the formula behind it so you can verify the arithmetic by hand.

Calculators in this Cluster

Explore the specialized tools within the LLM API Cost & Inference Hub cluster to model request pricing, multi-model tier tradeoffs, and prompt caching discounts:

Complementary Cross-Cluster Tools

For precise prompt sizing or organizational financial forecasting, these adjacent calculators directly inform LLM API budgeting: