Beginner's guide
What is prompt compression?
Prompt compression is the practice of reducing the size of an LLM prompt before sending it to the model, while preserving the information needed to answer the user's question correctly.
Understanding prompt compression
Every time you send a prompt to an LLM, you pay for every token — including tokens that are irrelevant to your question. Prompt compression removes those irrelevant tokens before the API call, saving money without sacrificing answer quality.
Think of it like editing a report before sending it to your manager: you keep the important data and remove the filler. SuperCompress does this automatically, scoring each line of your prompt against your question and keeping only the lines most likely to contain the answer.
How it differs from other approaches
| Approach | What It Does | Extra Cost |
|---|---|---|
| Prompt compression | Selects relevant lines | ~60ms CPU |
| Summarization | Rewrites using another LLM | Full LLM call |
| Truncation | Keeps first N tokens | None |
| Caching | Reuses previous responses | Storage |
Frequently asked questions
Is prompt compression the same as token compression?
Yes, they refer to the same concept — reducing the token count of prompts sent to LLMs.
Do I need to change my LLM provider?
No. Compression is provider-agnostic. It works with OpenAI, Anthropic, Google, and self-hosted models.
Try it yourself
Paste your long prompt into the playground, ask a question, and see what SuperCompress keeps and removes. Free, no signup needed.