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infrastructure#llm📝 BlogAnalyzed: Jan 22, 2026 05:15

Supercharge Your AI: Easy Guide to Running Local LLMs with Cursor!

Published:Jan 22, 2026 00:08
1 min read
Zenn LLM

Analysis

This guide provides a fantastic, accessible pathway to running Large Language Models (LLMs) locally! It breaks down the process into easy-to-follow steps, leveraging the power of Cursor, LM Studio, and ngrok. The ability to run LLMs on your own hardware unlocks exciting possibilities for experimentation and privacy!
Reference

“This guide uses the model: zai-org/glm-4.6v-flash”

PermalinkZenn LLM
infrastructure#llm📝 BlogAnalyzed: Jan 11, 2026 00:00

Setting Up Local AI Chat: A Practical Guide

Published:Jan 10, 2026 23:49
1 min read
Qiita AI

Analysis

This article provides a practical guide for setting up a local LLM chat environment, which is valuable for developers and researchers wanting to experiment without relying on external APIs. The use of Ollama and OpenWebUI offers a relatively straightforward approach, but the article's limited scope ("動くところまで") suggests it might lack depth for advanced configurations or troubleshooting. Further investigation is warranted to evaluate performance and scalability.
Reference

“まずは「動くところまで」”

PermalinkQiita AI
product#llm📝 BlogAnalyzed: Jan 3, 2026 12:27

Exploring Local LLM Programming with Ollama: A Hands-On Review

Published:Jan 3, 2026 12:05
1 min read
Qiita LLM

Analysis

This article provides a practical, albeit brief, overview of setting up a local LLM programming environment using Ollama. While it lacks in-depth technical analysis, it offers a relatable experience for developers interested in experimenting with local LLMs. The value lies in its accessibility for beginners rather than advanced insights.

Key Takeaways

Reference

“LLMのアシストなしでのプログラミングはちょっと考えられなくなりましたね。”

PermalinkQiita LLM
Technology#LLM, Mac mini, Dify, Ollama📝 BlogAnalyzed: Jan 3, 2026 06:05

Building a Local LLM Environment with Dify and Ollama on M4 Mac mini (16GB)

Published:Jan 2, 2026 13:35
1 min read
Zenn LLM

Analysis

The article describes the process of setting up a local LLM environment using Dify and Ollama on an M4 Mac mini (16GB). The author, a former network engineer now in IT, aims to create a development environment for app publication and explores the limits of the system with a specific model (Llama 3.2 Vision). The focus is on the practical experience of a beginner, highlighting resource constraints.

Key Takeaways

Reference

“The author, a former network engineer, is new to Mac and IT, and is building the environment for app development.”

PermalinkZenn LLM