What the AI prompt compressor does
Language models bill by the token, and most prompts are padded with words the model ignores anyway. This free prompt compressor rewrites a prompt to say the same thing in fewer tokens — stripping politeness filler, redundant role-setting, and repeated context — then shows the before/after token count and the estimated cost saving across GPT, Claude, and Gemini pricing. It runs in your browser; no signup, nothing sent to a server.
How to compress a prompt
- Paste your prompt into the box above.
- The tool tokenizes it and trims the filler it can safely remove.
- Copy the compressed version and check the token drop and the cost per 1,000 calls.
Why compressing prompts saves real money
Token savings compound with volume. A system prompt that runs on every API call — say 600 tokens trimmed to 380 — saves 220 input tokens per request. Across a million calls that is 220M tokens, a real monthly line item before you even count the latency win from a shorter prompt. Compression is one of the cheapest LLM-cost levers because it changes nothing about your model or infrastructure — only the words you send.
What it removes (and what it keeps)
- Removes: politeness filler ("please", "I would like you to"), duplicated instructions, and verbose phrasing ("in order to" → "to").
- Keeps: the task, constraints, examples, and output-format instructions — the parts that actually steer the model. Compression should shrink tokens, not meaning.
