Two ways to run AI models locally — terminal power vs. desktop polish.
Our pick
It depends on the job
Both are free to start, so pick by what you need most:
by Ollama
Ollama lets you download and run large language models like Llama 3, Mistral, Phi, and Gemma directly on your computer. No cloud, no API costs, full privacy. One command to install, one command to run. The REST API is OpenAI-compatible so any client just works.
by LM Studio
LM Studio gives you a polished desktop app for discovering, downloading, and running open-source LLMs locally. Unlike Ollama (terminal-first), LM Studio has a full chat UI and model browser built in. Download from Hugging Face, chat directly in the app, and expose a local OpenAI-compatible API for your tools.
| Feature | Ollama | LM Studio |
|---|---|---|
| Vendor | Ollama | LM Studio |
| Category | ML Platforms | ML Platforms |
| Free tier | Yes | Yes |
| Starting price | Free | Free |
| Strengths | Completely free forever, Full privacy — data never leaves your machine, 500+ model library via one-liner install | Clean GUI — no terminal commands needed, Built-in chat interface for testing models directly, Easy model discovery and download from Hugging Face |
| Weaknesses | Requires 8GB+ RAM for small models, 16GB+ for large, No built-in chat UI | Heavier app footprint than terminal-based Ollama, Some models require NVIDIA GPU for good performance |
The one number that matters is memory: the model has to fit in your GPU's VRAM (or a Mac's unified memory). Speed comes second. Figures are for the 4-bit models Ollama and LM Studio download by default.
| Model size | Examples | Memory needed | Runs well on |
|---|---|---|---|
| 3B-4B | Llama 3.2 3B, Gemma 3 4B, Qwen3 4B | ~3 GB | Any recent laptop, 8 GB Mac |
| 7B-8B | Llama 3.1 8B, Qwen3 8B, Mistral 7B | ~5-6 GB | 8 GB GPU minimum, 12-16 GB comfortable; 16 GB Mac |
| 12B-14B | Gemma 3 12B, Qwen3 14B, Phi-4 | ~9-10 GB | 16 GB GPU; 24 GB Mac |
| 24B-32B | Mistral Small 24B, Gemma 3 27B, Qwen3 32B | ~16-20 GB | 24 GB GPU; Mac with 32-48 GB |
| 70B | Llama 3.3 70B | ~40-43 GB | Two 24 GB GPUs; Mac with 64 GB+; 128 GB mini PC |
Best value GPU
NVIDIA GeForce RTX 5060 Ti 16GB
16 GB VRAM · runs 7B-14B models fully on the GPU
The cheapest current card with 16 GB of video memory. Make sure it is the 16 GB version, not the 8 GB one.
Easiest setup
Apple Mac mini with 24 GB or more
Unified memory doubles as GPU memory · quiet · low power
On Apple silicon the GPU uses the main memory, so a 24 GB Mac mini runs 14B models comfortably. Buy the memory up front: it cannot be upgraded later. 16 GB models are fine only for 8B and smaller.
24 GB on a budget
NVIDIA GeForce RTX 3090 24GB
24 GB VRAM · runs 24B-32B models at 4-bit
The classic local-AI card: 24 GB for less than a new 24 GB+ card. Mostly sold renewed or used, so check the seller and the return window. Needs a 750 W+ power supply.
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