Running LLMs Locally with Ollama: Benefits, Limitations, and Hardware Reality
🚀 Introduction Large Language Models (LLMs) are everywhere — but most developers rely heavily on cloud providers like OpenAI, Anthropic, or Azure. But what if you could run models locally on your ...
Source: DEV Community
🚀 Introduction Large Language Models (LLMs) are everywhere — but most developers rely heavily on cloud providers like OpenAI, Anthropic, or Azure. But what if you could run models locally on your machine? That’s where Ollama comes in. In this article, I’ll explain: Why you should consider using Ollama When it makes sense The real limitations (especially GPU vs CPU) Lessons learned from using it in a Spring Boot project 🤖 What is Ollama? Ollama is a tool that allows you to run LLMs locally with a simple CLI/API. Example: ollama run llama3 Or via HTTP: POST http://localhost:11434/api/generate It abstracts away: Model downloads Runtime configuration Inference execution 💡 Why Use Ollama? 1. 💰 Zero Cost for Development No API calls → no billing → perfect for: Local testing Prototyping Feature validation 2. 🔒 Privacy & Data Control Your data never leaves your machine: Great for sensitive use cases Useful for regulated environments 3. ⚡ Offline Capability You can run LLMs: Without in
