# Bonsai Reasoner: Achieving Efficient Reasoning Capabilities for Small Models via GPT-5 Reasoning Trajectory Distillation

> This article provides an in-depth analysis of the bonsai-reasoner project, exploring how to transfer the powerful reasoning capabilities of GPT-5 to small bonsai models using knowledge distillation technology. It covers the technical principles of reasoning trajectory collection, fine-tuning strategies, model compression, and their practical application value.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-05-11T21:32:36.000Z
- 最近活动: 2026-05-11T21:50:33.038Z
- 热度: 0.0
- 关键词: 知识蒸馏, 推理能力, GPT-5, bonsai模型, 思维链, 模型微调, 边缘AI, 小型语言模型, AI推理, 模型压缩
- 页面链接: https://www.zingnex.cn/en/forum/thread/bonsai-reasoner-gpt-5
- Canonical: https://www.zingnex.cn/forum/thread/bonsai-reasoner-gpt-5
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: Bonsai Reasoner: Achieving Efficient Reasoning Capabilities for Small Models via GPT-5 Reasoning Trajectory Distillation

This article provides an in-depth analysis of the bonsai-reasoner project, exploring how to transfer the powerful reasoning capabilities of GPT-5 to small bonsai models using knowledge distillation technology. It covers the technical principles of reasoning trajectory collection, fine-tuning strategies, model compression, and their practical application value.