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Home/Glossary/Outlier channels

Quantization

Outlier channels

What it is

Outlier channels contain values whose magnitudes are much larger than most peer channels. When one tensor scale preserves those extremes, fewer useful levels remain for ordinary values.

Why it moves cost and latency

Outliers explain why one scale for an entire tensor can lose important resolution. Channelwise scales, protected channels, or wider precision can isolate their effect.

What it looks like in practice

Quantizers inspect activation and weight distributions before choosing scale granularity. Teams verify that outlier handling improves task quality without adding unsupported layouts or excessive kernel work.

Where we measured it

  • Measured channelwise dynamic scaling->
  • Measured staged channelwise scaling->
  • Measured H100 channelwise packages->

Related terms

  • Channelwise quantization->
  • AWQ->
  • Eight-bit integer quantization->
  • Calibration data->
  • Mixed-precision serving->

Questions this definition answers

What does Outlier channels mean in inference serving?

Outlier channels contain values whose magnitudes are much larger than most peer channels. When one tensor scale preserves those extremes, fewer useful levels remain for ordinary values. Quantizers inspect activation and weight distributions before choosing scale granularity. Teams verify that outlier handling improves task quality without adding unsupported layouts or excessive kernel work.

Why can Outlier channels move cost or latency?

Outliers explain why one scale for an entire tensor can lose important resolution. Channelwise scales, protected channels, or wider precision can isolate their effect.

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