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| license: apache-2.0 |
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| # Model Card for LoopTool-32B |
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| <!-- Provide a quick summary of what the model is/does. --> |
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| ## Model Details |
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| ### Model Description |
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| <!-- Provide a longer summary of what this model is. --> |
| The LoopTool-32B model is derived from iterative fine-tuning of Qwen3-32B, with a particular emphasis on enhancing the model’s capabilities in tool invocation. |
| - **Developed by:** SJTU, Xiaohongshu |
| - **Model type:** Causal Language Models |
| - **Finetuned from model Qwen3-32B:** https://huggingface.co/Qwen/Qwen3-32B |
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| ### Model Sources |
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| <!-- Provide the basic links for the model. --> |
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| - **Repository:** https://github.com/Rednote-ExperienceAI-Lab/LoopTool |
| - **Paper:** https://arxiv.org/abs/2511.09148 |
| - **Dataset(Partial)** https://huggingface.co/datasets/zhuiguang-ning/LoopTool-23k |
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| ### Model Performance |
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| **The Main Result in BFCL-v3** |
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| | | Overall | Non-Live | Live | Multi-Turn | |
| | :----------: | ------- | -------- | :---: | ---------- | |
| | Qwen3-8B | 66.34 | 88.81 | 78.54 | 33.00 | |
| | LoopTool-8B | 74.93 | 89.52 | 84.72 | 50.88 | |
| | Qwen3-32B | 69.25 | 88.90 | 77.83 | 43.12 | |
| | LoopTool-32B | 79.32 | 91.83 | 88.58 | 57.75 | |
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| **The Main Result in ACEBench (English)** |
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| | | Overall | Normal | Special | Agent | |
| | :----------: | ------- | ------ | :-----: | ----- | |
| | Qwen3-8B | 67.1 | 70.9 | 78.0 | 34.2 | |
| | LoopTool-8B | 73.4 | 78.0 | 80.7 | 43.3 | |
| | Qwen3-32B | 72.2 | 77.3 | 76.0 | 46.7 | |
| | Kimi-K2-0711 | 77.4 | 78.9 | 81.3 | 65.0 | |
| | LoopTool-32B (OpenSource-1st) | 77.5 | 80.5 | 78.7 | 64.1 | |
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| ## Citation |
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| <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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| If you find our work helpful, feel free to give us a cite. |
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| ``` |
| @misc{zhang2025looptool, |
| title={LoopTool: Closing the Data-Training Loop for Robust LLM Tool Calls}, |
| author={Kangning Zhang and Wenxiang Jiao and Kounianhua Du and Yuan Lu and Weiwen Liu and Weinan Zhang and Lei Zhang and Yong Yu}, |
| year={2025}, |
| eprint={2511.09148}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL}, |
| url={https://arxiv.org/abs/2511.09148}, |
| } |
| ``` |
