Question 1

Which tokenizer does Zhipu use?

Accepted Answer

Zhipu uses its own tokenizer, which is not publicly available to run in a browser. This counter estimates counts with OpenAI's cl100k_base encoding, which is typically within roughly 10 to 20 percent of the real count for English text.

Question 2

Are these Zhipu token counts exact or estimated?

Accepted Answer

Estimated. Zhipu has not released its tokenizer for browser use, so this tool approximates counts with OpenAI's cl100k_base encoding. Estimates are usually close for English text but can drift for code, JSON, and non-English languages. Estimated counts are marked with a tilde (~).

Question 3

How is Zhipu API cost calculated?

Accepted Answer

Cost equals tokens divided by one million, multiplied by the model's per-million-token rate. Each Zhipu model has separate input and output rates, and this page shows both: what your text would cost as a prompt (input) and what the same number of tokens would cost as a response (output).

Question 4

Why do token counts matter for Zhipu API costs?

Accepted Answer

Zhipu bills API usage per token, not per word or character. A token is roughly 4 characters or about three quarters of a word in English. Knowing the token count of your prompts lets you predict spend, stay inside context windows, and compare Zhipu models like GLM-5.2, GLM-5.1 and GLM-5 Turbo before you commit.

Model	Tokens	Input Cost	Output Cost
GLM-5.2	—	—	—
GLM-5.1	—	—	—
GLM-5 Turbo	—	—	—
GLM-5	—	—	—
GLM-4.7	—	—	—
GLM-4.7-flash	—	—	—

Model	Input /1M	Output /1M	Context
GLM-5.2	$1.40	$4.40	1.0M
GLM-5.1	$1.40	$4.40	200K
GLM-5 Turbo	$1.20	$4.00	200K
GLM-5	$1.00	$3.20	128K
GLM-4.7	$0.600	$2.20	200K
GLM-4.7-flash	$0.070	$0.400	200K

Zhipu Token Counter

Zhipu Model Pricing

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