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MAX REED
MAX REED

Posted on • Originally published at techolyze.com

How to Run Open-Source LLMs Offline in 2025

Running large language models (LLMs) offline is now easy, free, and private — not just for researchers. If you're a developer, student, or privacy-focused user, offline LLMs let you use ChatGPT-level AI without APIs or internet.

🚀 Why Run LLMs Offline?

  • Full privacy — no data leaves your device
  • Zero cost — no tokens or rate limits
  • Customization — run any model, your way
  • Offline access — ideal for secure setups

🧠 Best Open-Source LLMs (2025)

Model Size Features
LLaMA 3 8B / 70B High-quality, versatile, Meta-supported
Mistral 7B 7B Fast, open license, multilingual
Phi-3 3.8B / 14B Tiny yet strong (Microsoft)
Gemma 2B / 7B Lightweight, clean tuning (Google)
TinyLlama 1.1B Works on low-end machines

Most support GGUF format for quantized offline performance.


💻 Requirements (Min Setup)

  • CPU: Intel i5+ / Ryzen 5+
  • RAM: 8–16GB
  • Disk: 5–20 GB per model
  • GPU (optional): 6GB+ VRAM or Apple M-series

⚡ Quickest Setup: Ollama

Ollama is the simplest CLI tool for offline LLMs.

Install:

curl -fsSL https://ollama.com/install.sh | sh
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Run a model:

ollama run mistral
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✅ Works with llama3, phi3, gemma, and more.

You can also connect it to LangChain or Flowise for full local AI agents.


🧑‍💻 No-Code Option: LM Studio

LM Studio lets you use AI models in a local app.

  • Drag & drop .gguf models
  • Offline chat interface
  • Perfect for non-dev users

🔄 Advanced: Build Offline AI Assistant

  • 🧠 Ollama – runs the model
  • 🧩 LangChain – connects tools, memory
  • 🗂️ Chroma / Weaviate – local vector DB
  • 📦 Tauri / Electron – wrap it as a desktop app

⚙️ Performance Tips

  • Use quantized models (Q4_0, Q6_K)
  • Prefer Mistral or Phi-3 for CPU speed
  • Use Apple M2/M3 for best native runs
  • Avoid >13B models without 32GB+ RAM or GPU

🔐 Privacy Wins

  • ❌ No sign-in, tracking, or cloud logs
  • ✅ Safe for legal, enterprise, or research use
  • ✅ Great for air-gapped environments

🧠 Who Should Use This?

  • Developers building private tools
  • Students experimenting with AI
  • Writers or researchers needing offline chat
  • Indie hackers avoiding API costs

In 2025, with tools like Ollama and LM Studio, offline AI isn’t just practical — it’s powerful.
Read full detail article here :Ultimate guide to set-up Llm offline in 2025

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