AI Pricing Calculators — Free, Up-to-Date 2026

Why eleven separate calculators instead of one?

Because AI pricing is not one bill — it is four. A team running a high-traffic chatbot, a team running an overnight batch classification job, a team embedding a knowledge base, and a team running a five-tool agent will see four wildly different invoice shapes from the same provider. A single combined calculator hides the levers; eleven scoped calculators surface them. Each tool below answers exactly one question.

If you are sizing a single workload

Start with the AI Prompt Cost Calculator. It walks the cost = (in ÷ 1M × in-price) + (out ÷ 1M × out-price) formula on real June-2026 prices, with worked examples for a one-off call and a 100,000-call batch. If you already know which provider you are comparing against, jump to the OpenAI API pricing breakdown or the Anthropic Claude pricing breakdown — both include cached-input rates, batch discounts, and worked monthly bills for the three workload shapes teams actually run.

If you are comparing providers head-to-head

The GPT vs Claude vs Gemini cost calculator is the only one that takes your monthly input/output token volume once and prints three apples-to-apples invoices. It is also the page to send to a finance lead who wants a single number rather than a token-economics lecture. Pair it with the LLM context window comparison if context length is a constraint — long-context modes carry premium rates on every provider and the cost cross-overs are not where intuition puts them.

If retrieval, fine-tuning, images, or agents are in scope

These are the four line items that blow up monthly bills past the naive token math. The embedding cost calculator includes the storage line nobody budgets for. The fine-tuning cost calculator shows the break-even volume where a fine-tuned smaller model beats a larger off-the-shelf one. The image generation calculator prices DALL·E 4, Midjourney v8, Stable Diffusion 4, and Imagen 4 at every resolution and quality tier. And the AI agent cost calculator is the one that surprises every founder — the 5–20x multiplier that turns a $0.02 prompt into a $0.40 task is not a rounding error.

If latency or throughput is the real constraint

Cost is only half the bill. The LLM rate limits page lists RPM, TPM, and concurrent-request ceilings on every tier of every provider — the tier you are on is the throughput ceiling you actually have, and the tier you need is rarely the one finance assumes. The output speed (tokens per second) table is the measurement most product teams should see before they pick a model — Haiku 4.5 streams roughly 4–6x faster than Opus 4.8, and that delta is the difference between a chat UX that feels instant and one that feels broken.

What we did not build a calculator for, and why

We did not build a self-hosted-inference calculator because the variable is GPU price-per-hour, which moves daily and depends on spot vs reserved capacity at your cloud — any calculator we shipped would be wrong by Wednesday. We did not build a vendor negotiation calculator because the leverage points (committed spend, support SLAs, custom rate cards) are not modelable from public pricing pages. And we did not build an "all-in TCO" calculator because the missing line is engineering hours, which is your number, not ours.

How to use this hub if you have ten minutes

Open the cross-provider calculator in one tab. Put in your best estimate of monthly input and output tokens. Look at the three invoices. If one is more than 2x another for the same workload, open the loser's pricing page (OpenAI, Anthropic) and check whether caching or batch can close the gap before you switch providers. Most of the time the cheaper provider on paper stays cheaper after discounts; sometimes the loser closes the gap and the right call is to stay where you are.