Count tokens and estimate cost for prompts before you send them, from the command line or as a CI budget gate.
Prompt templates grow, a few-shot example gets added, a retrieved context
balloons, and suddenly every call costs more than you thought. tokenmeter
gives you the exact token count and a dollar estimate up front, for a single
prompt or a whole directory of templates.
$ tokenmeter count prompts/system.txt --model gpt-4o
input in tok out tok cost (USD)
prompts/system.txt 812 0 $0.002030
$ tokenmeter count prompts/ --model gpt-4o-mini --json$ pip install tokenmeter-cli # from PyPI, once released
$ pip install git+https://github.com/jmweb-org/tokenmeter # latest, available nowToken counting is exact for the supported OpenAI encodings via tiktoken.
$ tokenmeter count system.txt -m gpt-4o # one file
$ tokenmeter count prompts/ -m gpt-4o-mini # every text file in a directory
$ cat prompt.txt | tokenmeter count - -m gpt-4o # standard input
$ tokenmeter count p.txt --output-tokens 500 # include an assumed completion
$ tokenmeter models # list models and pricesFail a build when a prompt set would cost more than you allow:
$ tokenmeter budget prompts/ --model gpt-4o --max-cost 0.05- run: tokenmeter budget prompts/ --model gpt-4o --max-cost 0.05Counts are real tokens. Cost multiplies tokens by a per-model rate from a small,
dated price table (tokenmeter models prints it with its "as of" date). By
default only input tokens are counted; pass --output-tokens N to add an
assumed completion length to the estimate. Prices change, so treat the dollar
figures as estimates and update the table when they move.
| Code | Meaning |
|---|---|
| 0 | Counted; under budget (or count was used) |
| 1 | budget estimate exceeded --max-cost |
| 2 | An input was missing, or the model is unknown |
MIT. See LICENSE.