▶ Interactive Lab

Quantization Calibration

See how calibration data choice affects quantized weight ranges.

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Calibration data should match production. Wrong domain = bad quantized model.

What you're seeing

Post-training quantization needs ~512-1000 sample inputs to find activation ranges. Calibration data should match production distribution.

Wrong calibration: ranges set too narrow → clipping → quality drop. Or too wide → wasted precision. Domain-fine-tuned models need domain calibration data.

★ KEY TAKEAWAY
Quantization calibration data must match production. Wrong domain = clipped or wasted ranges = quality drop.
▶ WHAT TO TRY
  • Switch between English / Code / Multilingual calibration.
  • See how activation range varies by domain.