FAQ It Till You Make It: Fixing LLM Quantization by Teaching Models Their Own Family History
Compression sounds simple until the model starts forgetting how to think. A deployment team takes a large language model, squeezes its weights into lower precision, saves memory, improves serving economics, and expects the model to behave like a slightly thinner version of itself. Then INT4 arrives with a polite smile and removes just enough reasoning ability to make the business case awkward. The model still answers. It still looks fluent. It just becomes less reliable exactly where the product needed it to stay sharp. ...