Developers run LLMs locally to cut costs and boost privacy

Developers are increasingly adopting local Large Language Models (LLMs) to reduce costs, enhance privacy, and enable offline access. Tools like Ollama simplify the process of running models such as Llama 3 and Qwen2.5-coder directly on personal computers. This setup is particularly beneficial for coding assistance, refactoring, and general AI chat functionalities, with integrations available for IDEs like VS Code through extensions such as Continue.dev. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Enables developers to reduce AI API expenses and gain more control over their AI tools.

RANK_REASON The article describes how to use existing tools to run LLMs locally, focusing on practical application rather than a new release.

Read on dev.to — LLM tag →

• Claude API
• Continue.dev
• Cursor
• Large Language Models
• Llama 3
• Ollama
• OpenAI API
• Qwen2.5-coder
• VS Code

• product
• infra