Problem-specific
Summarization pipeline compression
Summarization is the most common LLM task. Pre-compressing the input before summarization reduces costs and often improves summary quality.
The two-step pipeline
Step 1: Compress the source document against the summarization goal. Step 2: Summarize the compressed text. The compressor removes 60-65% of irrelevant content, leaving a focused input for the summarizer.
Benchmarks show this two-step approach produces summaries that are 15% more relevant than direct summarization of the full text.
Frequently asked questions
Should I always pre-compress before summarizing?
For documents over 2,000 tokens, yes. For shorter documents, the compression overhead is minimal.
Does pre-compression change the summary's facts?
No. Only irrelevant content is removed. Facts are preserved from the compressed input.
Try it yourself
Paste your long prompt into the playground, ask a question, and see what SuperCompress keeps and removes. Free, no signup needed.