---
title: Prompt compression tools compared
url: https://compresr.ai/compare/prompt-compression-tools
description: Prompt compression tools in 2026 compared: LLMLingua-2, LongLLMLingua, scaledown, Token Company, and Compresr.
---

# Prompt compression tools in 2026, compared: LLMLingua-2, LongLLMLingua, scaledown, Token Company, and Compresr.

> Across prompt-compression tools, Compresr leads on matched-~2x accuracy on QMSum (59.6%) while being query-aware, hosted, and on-prem-ready.

> Human-readable page: https://compresr.ai/compare/prompt-compression-tools

## Matched ~2x accuracy (QMSum)
### QMSum: meeting-transcript QA
n = 272, single-shot long-document QA, gpt-5.4-mini answerer, gpt-5.4 judge, 2026-04

| Config | Accuracy | Compression ratio |
| --- | --- | --- |
| Full context (baseline) | 55.9% | 1.0x |
| Query-specific (light) (best) | 59.6% | 1.87x |
| High compression (below baseline, cost/latency) | 42.6% | 8.76x |

#### vs. other methods at matched ~2x ratio

| Method | QMSum accuracy | Ratio |
| --- | --- | --- |
| Compresr (latte_v1) (us) | 59.6% | ~1.87x |
| scaledown | 57.4% | ~2x |
| LongLLMLingua | 53.7% | ~3x |
| LLMLingua-2 | 50.7% | ~2x |
| Token Company (ttc) | 48.2% | ~2x |

## Accuracy vs. ratio: two separate claims
- The accuracy win lives at LIGHT (~2x) compression: FinanceBench 73%→77%, QMSum 55.9%→59.6% (single-shot long-document QA, not RAG, 2026-04).
- High ratios (~10x / ~90% reduction) are a COST + LATENCY claim only. Past ~2x, accuracy falls ~2pp per doubling and can drop below the full-context baseline (e.g. FinanceBench ~8.9x = 65%).
- These are never combined into a single "90% reduction at full accuracy" claim.

## Related machine surfaces
- [/compare/llmlingua.md](/compare/llmlingua.md)
- [/benchmarks.md: results](/benchmarks.md)

## Provenance
Compresr Inc. is a Y Combinator W26 company built by four EPFL-trained founders in San Francisco, California and Europe (Switzerland).
Contact: [compresr.ai/contact](https://compresr.ai/contact).