---
language:
- en
license: apache-2.0
base_model: Qwen/Qwen3.5-9B
tags:
- qwen
- gptq
- quantized
- math
- causal-lm
library_name: transformers
pipeline_tag: text-generation
---

# Qwen3.5-9B-GPTQ-INT8

This model is a GPTQ-quantized version of `Qwen/Qwen3.5-9B` with a normalized text-only `config.json`.

## Quantization

- Method: GPTQ
- Bits: 8
- Group size: 128
- desc_act: False
- damp_percent: 0.1
- Calibration preset: math_qa_cot
- Calibration dataset: `zwhe99/DeepMath-103K` split `train`
- Max calibration samples: 128
- Max sequence length: 16384

## Reproduction

```bash
uv run python quantization/quantize_qwen35_9b_gptq.py \
  --model-name Qwen/Qwen3.5-9B \
  --output-dir /workspace/lowbit-math-reasoning/experiments/models/Qwen3.5-9B-GPTQ-INT8 \
  --dataset-name zwhe99/DeepMath-103K \
  --dataset-config '' \
  --dataset-split train \
  --calibration-preset math_qa_cot \
  --question-column question \
  --answer-column r1_solution_1 \
  --text-column r1_solution_1 \
  --max-calibration-samples 128 \
  --max-seq-len 16384 \
  --bits 8 \
  --group-size 128 \
  --damp-percent 0.1
```

The current quantization script rewrites `config.json` after `save_pretrained()` so the exported checkpoint uses the same text-only `qwen3_5_text` layout as the working INT4 checkpoint.

## Validation

This normalized-config checkpoint was re-evaluated on GSM8K and matched the original INT8 accuracy while improving throughput substantially.

- Original INT8: EM 0.96, 105.98 tok/s
- Fixed-config INT8: EM 0.96, 150.84 tok/s

## Notes

- This repository contains quantized weights only.
- The checkpoint is intended for text-only evaluation.
- `vLLM` loads this checkpoint as `gptq_marlin`.