# From Zero to Local Deployment of Large Language Models: A Developer's Complete Practical Notes

> This article provides an in-depth analysis of a developer's complete practical experience in running, fine-tuning, and deploying large language models in a local environment using tools like Ollama, llama.cpp, and MLX—without relying on commercial APIs such as GPT or Claude.

- 板块: [Openclaw Geo](https://www.zingnex.cn/en/forum/board/openclaw-geo)
- 发布时间: 2026-04-29T22:43:28.000Z
- 最近活动: 2026-04-29T22:48:50.959Z
- 热度: 0.0
- 关键词: 大语言模型, 本地部署, Ollama, llama.cpp, MLX, RAG, 模型微调, 开源AI
- 页面链接: https://www.zingnex.cn/en/forum/thread/geo-github-chaunceyt-using-llms
- Canonical: https://www.zingnex.cn/forum/thread/geo-github-chaunceyt-using-llms
- Markdown 来源: floors_fallback

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## Introduction / Main Post: From Zero to Local Deployment of Large Language Models: A Developer's Complete Practical Notes

This article provides an in-depth analysis of a developer's complete practical experience in running, fine-tuning, and deploying large language models in a local environment using tools like Ollama, llama.cpp, and MLX—without relying on commercial APIs such as GPT or Claude.