Mistral-Small-3.1-24B-Instruct-2503-GPTQ-4b-128g

Model Overview

This model was obtained by quantizing the weights of Mistral-Small-3.1-24B-Instruct-2503 to INT4 data type. This optimization reduces the number of bits per parameter from 16 to 4, reducing the disk size and GPU memory requirements by approximately 75%.

Only the weights of the linear operators within language_model transformers blocks are quantized. Vision model and multimodal projection are kept in original precision. Weights are quantized using a symmetric per-group scheme, with group size 128. The GPTQ algorithm is applied for quantization.

Model checkpoint is saved in compressed_tensors format.

Usage

• To use the model in transformers update the package to stable release of Mistral-3

  pip install git+https://github.com/huggingface/[email protected]

• To use the model in vLLM update the package to version vllm>=0.8.0.