What does Quantization quality recovery mean in inference serving?
Quantization quality recovery is the measured retention of task performance after a model moves to lower precision. Recovery is evaluated against the same unquantized baseline, task set, and scoring method. Teams run representative evaluations before and after quantization, then compare scores with uncertainty and failure cases visible. They accept a serving configuration only when quality and performance meet the stated workload criteria.
