1. Tutorial Introduction

VibeThinker-1.5B is the first open-source large-scale model released by Weibo AI in November 2025. VibeThinker-1.5B's powerful capabilities don't rely on simply piling on parameters; instead, they stem from the SSP training concept proposed by Weibo's developers. This concept encourages the model to explore all possible solution paths during the learning phase, rather than solely focusing on accuracy. Subsequently, reinforcement learning is used for efficient policy optimization, precisely locking in the correct path and maximizing model performance. The related paper is titled "Tiny Model, Big Logic: Diversity-Driven Optimization Elicits Large-Model Reasoning Ability in VibeThinker-1.5B".

This tutorial uses a single RTX 5090 graphics card as the default resource, but a single RTX 4090 graphics card is also possible. Asking questions in English is recommended, as the model only supports English answers.

This model is recommended for solving competitive-style mathematical and algorithmic programming problems.

2. Effect display

3. Operation steps

1. Start the container

2. Usage steps

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.

Citation Information

The citation information for this project is as follows:

@misc{xu2025tinymodelbiglogic,
      title={Tiny Model, Big Logic: Diversity-Driven Optimization Elicits Large-Model Reasoning Ability in VibeThinker-1.5B}, 
      author={Sen Xu and Yi Zhou and Wei Wang and Jixin Min and Zhibin Yin and Yingwei Dai and Shixi Liu and Lianyu Pang and Yirong Chen and Junlin Zhang},
      year={2025},
      eprint={2511.06221},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2511.06221}, 
}