vLLM+Open WebUI Deployment QwenLong-L1-32B

1. Tutorial Introduction

QwenLong-L1-32B is a long text reasoning model released by Tongyi Lab and Alibaba Group on May 26, 2025. This model is the first long text reasoning model based on reinforcement learning (RL) training. It focuses on solving the problems of poor memory and logical confusion that traditional large models encounter when processing ultra-long contexts (such as 120,000 tokens). It breaks through the contextual limitations of traditional large models and provides low-cost, high-performance solutions for high-precision scenarios such as finance and law. The relevant paper results are "QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning".

This tutorial uses dual-card RTX A6000 resources.

2. Project Examples

3. Operation steps

1. After starting the container, click the API address to enter the Web interface

If "Model" is not displayed, it means the model is being initialized. Since the model is large, please wait about 2-3 minutes and refresh the page.

2. After entering the webpage, you can start a conversation with the model

How to use

4. Discussion

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Citation Information

Thanks to Github user xxxjjjyyy1  Deployment of this tutorial. The reference information of this project is as follows:

@article{wan2025qwenlongl1,
  title={QwenLong-L1: : Towards Long-Context Large Reasoning Models with Reinforcement Learning},
  author={Fanqi Wan, Weizhou Shen, Shengyi Liao, Yingcheng Shi, Chenliang Li, Ziyi Yang, Ji Zhang, Fei Huang, Jingren Zhou, Ming Yan},
  journal={arXiv preprint arXiv:2505.17667},
  year={2025}
}