Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking
Paper • 2601.04720 • Published • 59
How to use Zeknes/Qwen3-VL-Reranker-8B-MLX-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Qwen3-VL-Reranker-8B-MLX-4bit Zeknes/Qwen3-VL-Reranker-8B-MLX-4bit
This is the MLX 4-bit quantized version of Qwen/Qwen3-VL-Reranker-8B, optimized for Apple Silicon (Mac / iPad / iPhone) inference using the MLX framework.
| Config | Value |
|---|---|
| Bits | 4 |
| Group Size | 64 |
| Quantization Mode | Affine |
| Dtype | bfloat16 |
pip install mlx-lm transformers
mlx-lm
from mlx_lm import load
model, tokenizer = load("Zeknes/Qwen3-VL-Reranker-8B-MLX-4bit")
For full usage examples (multimodal reranking, vLLM), please refer to the original model page: Qwen3-VL-Reranker-8B
@article{qwen3vlembedding,
title={Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking},
author={Li, Mingxin and Zhang, Yanzhao and Long, Dingkun and Chen Keqin and Song, Sibo and Bai, Shuai and Yang, Zhibo and Xie, Pengjun and Yang, An and Liu, Dayiheng and Zhou, Jingren and Lin, Junyang},
journal={arXiv preprint arXiv:2601.04720},
year={2026}
}
4-bit