---
base_model: meta-llama/Llama-3.1-8B-Instruct
tags: [quantization, safety, gptq, simulated-quantization]
---

# Llama-3.1-8B-Instruct-c1sim

> ⚠️ **Quantized without GPTQ activation reordering** (`actorder=None`). This is kept for
> the record, not for use. On Llama-3.1-8B the same recipe with `actorder="weight"` moves
> 4-bit GSM8K from **0.0121 to 0.8143** and refusal from **0.000 to 0.908**. Prefer the
> sibling repo without `-noactorder` in its name.

Checkpoint from the *Safety-Aware Configuration-Conditioned LoRA* study.

| field | value |
| --- | --- |
| scheme | `W8A16` |
| method | `gptq-simulated` |
| weight bits | `8` |
| group size | `128` |
| symmetric | `True` |
| **actorder** | `<not recorded — predates the flag>` |
| simulated | `True` |
| calibration | `512 × 2048 tok, C4` |
| calibration sha256 | `b5736155d5b24bf5eb15faae0eb4a742aea4a9d0532db9684085a49750606e19` |

## Simulated quantization

Weights are rounded onto the low-bit grid and stored **densely in bf16**. vLLM 0.11's
`WNA16_SUPPORTED_TYPES_MAP` is `{4: uint4b8, 8: uint8b128}`, so 2- and 3-bit have no
kernel and cannot be executed natively at all. This is weight-exact, **not** kernel-exact:
you get the accuracy of low-bit quantization with none of the memory or latency benefit,
and the file is the size of the bf16 original.

Reports, metrics and per-prompt judge verdicts:
[`Jeesup/safety-quant-phase1`](https://huggingface.co/datasets/Jeesup/safety-quant-phase1)