> ## Documentation Index
> Fetch the complete documentation index at: https://phaseo.app/docs/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
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# Quantization Methods

> How quantization methods differ from numeric formats, and why method choice matters.

Numeric format (`FP8`, `INT8`, `INT4`) tells you precision.

Quantization method tells you **how** that precision was applied.

## Why methods matter

Two `INT4` variants can behave very differently because method choices affect:

* Accuracy retention
* Runtime compatibility
* Memory layout and serving performance
* Calibration requirements

## Common method families

| Method family | Typical purpose | Notes |
| - | - | - |
| `AWQ` | Preserve key activation-sensitive weights | Common for practical inference quality/efficiency balance |
| `GPTQ` | Post-training quantization with error minimization | Popular for compact local inference variants |
| `GGUF` | Packaging format used by llama.cpp ecosystems | Often combined with different quantization levels (`Q4`, `Q5`, etc.) |
| `EXL2` | Aggressive low-bit variants in ExLlama ecosystems | High throughput focus with architecture/runtime constraints |

## Method vs format example

`INT4` is the precision target.\
`AWQ INT4` and `GPTQ INT4` are different realizations of that target.

## Practical guidance

1. Pick runtime first (what you can deploy reliably).
2. Filter to method families that runtime supports.
3. Benchmark multiple quantization methods for the same precision target.
4. Track failure modes, not just average benchmark scores.

## Evaluation checklist

* Structured output correctness
* Long-context faithfulness
* Tool call reliability
* Safety/moderation behavior
* Tail latency under load


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