Gemini token counter & Google AI cost calculator

How Gemini counts tokens

Gemini tokenises with its own vocabulary, sitting between OpenAI's and Anthropic's in how aggressively it merges — this calculator models the gap at about five percent above the OpenAI baseline for English prose.

The counter above is an estimate, not Google's own merge table. It models the behaviour that actually drives the number — a leading space merging into the word after it, digits grouping, characters outside the Latin range costing several times more — which is close enough to size a prompt and budget a workload, and deliberately not close enough to reconcile an invoice against.

Gemini charges more per token once the prompt gets long

This is the single most important thing on this page, and neither OpenAI nor Anthropic does it — only xAI prices the same way. Google prices its Pro model in tiers: prompts up to a threshold bill at the headline rate, and prompts above it bill higher — for the same model, the same request, the same output. Because Gemini's selling point is a very large context window, the workloads people choose it for are exactly the ones that cross the line. A cost estimate built on the headline rate can therefore be badly wrong in the one direction that hurts, and it goes wrong precisely when you are doing the thing the model is best at. The table marks which model this applies to; treat its figure as the floor for a long prompt, not the price. Grok is priced on the same two-tier basis, so if long prompts are your workload those two are the pair to compare.

What the 3 Gemini models cost

Take one representative call — a 2,000-token prompt and a 600-token reply, which is roughly two pages in and one page out — and run it 100 times a day.

Flash models are dramatically cheaper than Pro and, for summarising, extraction and classification, usually indistinguishable in output quality. If your workload is long-input and short-output — feeding a big document and asking one question of it — Flash on Gemini is among the cheapest ways to do it anywhere, provided you check whether the prompt crosses the long-prompt tier.

Which Gemini model to use

Flash unless you have a reason. The Flash tier is priced for volume and is strong at the long-input, short-output work that suits a large context window — summarising, extracting, answering questions about a document you have just handed it. Pro is for genuine reasoning depth, and it is the model with the long-prompt pricing tier, so it is also the one where a big context bites twice. Price the Flash version of your workload first; quite often it is the answer.

Context windows

The Gemini models here run from 1M tokens to 1M. That window is shared: your prompt, every earlier turn in the conversation, and the reply all have to fit inside it together. The table above marks a model in red when the text you have pasted plus the reply length you set would not fit — which is usually how people discover that a window is not as generous as the headline number suggests.

Questions

How many tokens is 1,000 words in Gemini?

Roughly 1,350 for ordinary English — slightly above the same text on GPT and slightly below Claude. As always the ratio moves with content: source code and non-Latin scripts cost considerably more per character.

Does Gemini's big context window make it cheaper?

It makes it possible, not cheap. A million-token window means you can send a whole book; you are still billed for every token of it on every call, and on the Pro model a prompt that long bills at the higher long-prompt rate. The window is a capability limit, not a pricing one.

Is Google AI Studio free?

AI Studio has a free tier with rate limits, which is genuinely free for experimenting. Production use through the API is billed per token at the rates in the table. This calculator prices the paid API, which is what you will be on if the thing you are building works.

Why do two Gemini models show a note?

One is priced in tiers, so its headline rate only applies below a prompt-length threshold. The other is on a promotional rate with a published end date. Both are shown against the model in the table rather than buried here, because both change what you would actually pay.

Counting for a different provider

The same text costs a different number of tokens on every family, so if you are comparing providers, compare on your own text rather than on a rule of thumb.

Rates are USD per million tokens, published list price, checked 2026-08-31. Batch and cached-input discounts are not applied. Confirm against Google before committing a budget.