LOCAL AI SOFTWARE
Ollama vs LM Studio
Both run downloadable AI models locally. Ollama is especially attractive as a lightweight runtime and API; LM Studio puts model discovery, loading and chat into a desktop graphical app.
| Question | Ollama | LM Studio |
|---|---|---|
| Primary feel | Runtime, CLI, desktop app and local API | Desktop model manager and chat app |
| Model discovery | Ollama model library | Search and download interface |
| Local API | Yes | Yes, including OpenAI-like endpoints |
| Good for beginners? | Yes | Yes, particularly if you prefer a graphical workflow |
Choose Ollama when the runtime is the centre
Ollama is a natural fit when other software needs to call a local model or when you plan to pair it with Open WebUI.
Choose LM Studio when you want a desktop workspace
LM Studio lets you search for models, download them, load them into memory and chat in one app. It can also serve local models through API endpoints.
Hardware support differs
LM Studio currently supports Apple Silicon Macs, Windows x64 and ARM systems, and Linux x64/ARM64. Its current requirements recommend 16 GB or more RAM, and on Windows recommend at least 4 GB dedicated VRAM.
The model still matters more than the app
Compare the same model, quantisation and context when judging memory or speed.
Next: work out how much VRAM you need or use the memory calculator.
Sources: LM Studio system requirements and Ollama documentation.