Comparison guide
SuperCompress vs LLMLingua
LLMLingua uses a smaller LLM (Llama 2-7B) to compress prompts. SuperCompress uses a tiny 5K-parameter policy that runs on CPU with ~60ms latency.
Architecture differences
| Factor | LLMLingua | SuperCompress |
|---|---|---|
| Model size | 7B parameters | ~5K parameters |
| Hardware | GPU recommended | Runs on CPU |
| Latency | 500ms+ on GPU | ~60ms on CPU |
| Integration | Requires model download | pip install |
| Oracle recall | ~95% | 100% |
When to use each
LLMLingua works well when you have GPU access and need aggressive compression. SuperCompress is better for CPU-only deployments, serverless functions, and real-time applications where latency matters.
Frequently asked questions
Does SuperCompress need a GPU?
No. It runs on CPU with ~60ms latency.
Can I use both in my pipeline?
Yes. They are complementary approaches.
Try it yourself
Paste your long prompt into the playground, ask a question, and see what SuperCompress keeps and removes. Free, no signup needed.