Quick answer

Ollama and LM Studio both run open-weight models (Llama, Qwen, DeepSeek, Gemma, Mistral) on your own computer for free and in private. Ollama is a command-line tool with an OpenAI-compatible local API that developers plug into other software. LM Studio is a desktop app with a model browser and chat window for people who never want to see a terminal. Same models underneath. Pick Ollama for integrations, LM Studio for a private chat app — or use both.

Running AI locally used to mean compiling code and fighting drivers. In 2026 it means installing one of two free programs. The choice between them is less about capability — they run the same model files — and more about who you are and what you want the model for.

Ollama

  • Install, then type one command to download and run a model
  • Exposes a local API that Continue, Open WebUI, Brave Leo, scripts, and your own apps can call as if it were OpenAI
  • Open source, runs on Mac, Windows, and Linux, and as a server on a home machine others can reach
  • Minimal built-in chat interface — it expects you to bring a front end
  • Best for developers, home-lab users, and anyone wiring a local model into other tools

LM Studio

  • Graphical model browser that tells you whether a model will fit your hardware before you download it
  • Polished chat window with system prompts, presets, and local document chat
  • Also exposes an OpenAI-compatible local server if you want it
  • Closed source; free for personal use, commercial use by arrangement
  • Best for non-developers, students, and anyone who wants a private ChatGPT-like app

What hardware you actually need

The model size decides everything. A 7 to 9 billion parameter model in compressed form runs acceptably on a laptop with 16 GB of RAM or any Apple silicon Mac, and is fine for summarising, drafting, and simple coding help. A 27 to 32 billion parameter model needs 32 GB or more, or a GPU with 24 GB of memory, and starts to feel like a 2024 frontier model. Anything larger is workstation territory. Neither tool changes this; they only make it easy to find out.

Honest limits of local AI

  • A laptop model is far below Claude Opus or GPT-6 on hard reasoning and long agentic tasks
  • Speed drops sharply once a model spills out of GPU or unified memory
  • You are the sysadmin: updates, disk space, and model choices are your job
  • Privacy is the win — nothing leaves the machine — but only if the front end you connect is also local

Most people who try local AI end up hybrid: a local model for private or high-volume drafting, a cloud model for the hard stuff. Perplexity now does this automatically on Mac; Ollama and LM Studio let you do it deliberately.

Related reading

What Is a Local LLM? Perplexity Hybrid Compute — Local Plus Cloud What Is Model Quantization? Open-Source AI in Mid-2026

Bottom line

Developers: Ollama. Everyone else: LM Studio. Both are free, both run the same models, and both are limited by your hardware rather than by the software. Install LM Studio first to see what your machine can handle, then add Ollama when you want other tools to use the model you chose.