Prompt Compression

Reduce prompt token counts by 12-72% through intelligent rewriting that preserves every piece of data, every instruction, every number.

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Your prompts are longer than they need to be

The Problem

Natural language is verbose. 'I would really appreciate if you could please take the time to carefully explain what recursion means in the context of programming' is 30 tokens. The model needs 8. Every extra token costs money, and across thousands of requests per month, verbosity adds up fast.

The Solution

Tokonomy's compression engine rewrites prompts to be concise while preserving all semantic content. Not regex stripping or truncation. Intelligent rewriting that understands what matters and what's filler. You talk naturally. The model sees the tight version.

Before and After

Original Prompt (38 tokens)

I would really appreciate if you could please take the time to carefully and thoroughly explain to me what exactly the concept of recursion means in the context of computer programming

Compressed (12 tokens)

Explain recursion in programming with examples

Token savings: 68%

How It Works

Your request arrives at the Tokonomy proxy

The compression engine analyzes the prompt and rewrites it for conciseness

All data, numbers, instructions, and structured content are preserved

The compressed prompt is forwarded to the provider. You get the same response

Frequently Asked Questions

Will compression change what the model outputs?

At Low and Medium profiles, output quality is identical. High (72%) is aggressive and best tested on your specific workload first.

Does it compress system prompts too?

Yes. System prompts, user messages, and assistant messages in the conversation history are all compressed.

What about code in prompts?

Code blocks, JSON schemas, tool definitions, and structured data are never modified. Only natural language text is compressed.

Can I set my own compression target?

Yes. Choose Low (12%), Medium (40%), High (72%), Custom (1-100%), or Dynamic (auto-adjusts based on traffic volume).

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