How does Gemini count tokens?

Gemini uses a SentencePiece tokenizer. For English text it averages close to 4 characters per token, similar to GPT models. Images are billed at a fixed token cost per image (about 258 tokens for a standard tile), and audio/video are counted per second.

How accurate is this estimator?

It is a calibrated heuristic, not the exact tokenizer. For English prose it is typically within 5-10% of Google's count_tokens result. For code, non-Latin scripts, or mixed media, verify with the official API.

How are images counted?

Gemini charges roughly 258 tokens per image tile for standard-resolution images. This tool multiplies your image count by that fixed rate and adds it to the text token estimate.

Is my text sent to Google?

No. The estimate runs entirely in your browser. Nothing you paste or enter is uploaded, stored, or logged.

Gemini Token Estimator

Gemini token estimator

Approximate how many tokens your prompt will use on Google’s Gemini models — 1.5 Pro, Flash, and Ultra — including a multimodal estimate when your request contains images. Gemini’s context windows are large (up to ~2M tokens on 1.5 Pro), but tokens still drive cost, so an estimate helps you budget batches before sending.

How the estimate works

Gemini tokenizes with a SentencePiece model. For English text it lands close to 4 characters per token, comparable to GPT, so this tool applies that ratio blended with a word-boundary heuristic. Images are added at Gemini’s fixed rate of roughly 258 tokens per standard image tile, multiplied by the number of images you enter. The result is a calibrated approximation, not the exact tokenizer count.

Tips and notes

Multimodal requests can be dominated by media: a handful of images often costs more tokens than several paragraphs of text.
Non-Latin scripts and code tokenize less efficiently — expect a higher real count than the English-tuned estimate.
For exact billing on large or repeated jobs, call Gemini’s count_tokens endpoint, which returns the precise total including media.