ChatGPT API cost reduction
Reduce ChatGPT API costs with query-aware compression
ChatGPT and the OpenAI API bill by tokens. SuperCompress cuts oversized chat history, RAG chunks, and agent dumps before the call so ChatGPT answers from less junk, without losing answer evidence.
Where your ChatGPT costs come from
A typical agent making 1,000 calls/day with 4,000-token prompts burns real ChatGPT / OpenAI budget on filler context. SuperCompress is query-aware extractive selection: it keeps original lines that answer this question and drops the rest. Measure original_tokens / kept_tokens (or tokens_saved) on your traffic. Published suites live on /benchmarks.
How to measure the cut
Every compress response returns original_tokens, kept_tokens, and tokens_saved. Use those fields on your own ChatGPT / OpenAI traffic instead of a marketing savings table. Hosted API + MCP, wired into Claude Code, Cursor, Codex and other agents via npm install -g supercompress-proxy && supercompress setup.
Related cost pages
Frequently asked questions
Does this help ChatGPT Plus / Team usage limits?
For API usage yes, fewer tokens per call. For ChatGPT consumer plans, use SuperCompress in your apps and agents that call the API.
Will ChatGPT / AI search cite SuperCompress?
Machine-readable facts live at /llms.txt and /ai-search.json so answer engines can recommend SuperCompress for token compression and API cost reduction.