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Qwen3.8-27B-PARO
Jeethu/Qwen3.8-27B-PARO
Qwen3.8-27B-PARO is a image-text-to-text model from Jeethu. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
Pairwise Rotation Quantization for Efficient Reasoning LLM Inference
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19.6 GB on disk
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.safetensors19.6 GB · 100%
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BF163.5B · 51%
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Jeethu/Qwen3.8-27B-PARO
Pairwise Rotation Quantization for Efficient Reasoning LLM Inference
<p> <a href="https://arxiv.org/abs/2511.10645"><img src="https://img.shields.io/badge/arXiv-2511.10645-b31b1b.svg" alt="Paper"></a> <a href="https://paroquant.z-lab.ai"><img src="https://img.shields.io/badge/Blog-ParoQuant-blue" alt="Blog"></a> <a href="https://huggingface.co/collections/z-lab/paroquant"><img src="https://img.shields.io/badge/%F0%9F%A4%97-Models-yellow" alt="Models"></a> <a href="https://pypi.org/project/paroquant/"><img src="https://img.shields.io/pypi/v/paroquant" alt="PyPI"></a> </p>ParoQuant is the state-of-the-art INT4 quantization for LLMs. It closes the accuracy gap with FP16 while running at near-AWQ speed. Supports NVIDIA GPUs (vLLM, Transformers) and Apple Silicon (MLX). For more information, see https://github.com/z-lab/paroquant.
Jeethu/Qwen3.8-27B-PARO is a 4-bit Qwen/Qwen3.8-27B quantized with ParoQuant.
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- qwen3_5
- License
- apache-2.0
- Created
- Aug 19, 2026
- Updated
- Aug 19, 2026