Ollama or LM Studio: Which One to Install First

Laptop screen split between a terminal and a chat app

Most people who start running models at home install either Ollama or LM Studio first. Both run the same kinds of open-weight models on your own machine, and both are free to download. The difference is how you work with them, and that decides which one to start with.

Ollama: a command-line tool with a local API

Ollama runs as a background server, and you drive it from the terminal. ollama pull qwen3:8b downloads a model, ollama run qwen3:8b starts a chat, and ollama ps shows what is loaded and whether it fits in your GPU. The same server answers HTTP requests on localhost:11434, which is what makes Ollama a good base for other tools: chat front ends, coding assistants and scripts can all point at that one address.

Settings live in environment variables. Ollama's FAQ says the default context window is 4096 tokens, and OLLAMA_CONTEXT_LENGTH raises it. That is easy to script and easy to forget, so note what you changed.

LM Studio: a desktop app with a model browser

LM Studio is a graphical app. Its docs list support for Apple Silicon Macs, x64 and ARM64 Windows PCs, and x64 Linux. You search for a model inside the app, pick a quant from a list of files, and chat in a window, with settings like context length in a side panel. On Apple Silicon Macs, LM Studio can run models in either llama.cpp's GGUF format or Apple's MLX format. It also has a local server with OpenAI-compatible endpoints, per its developer docs, so you can point other tools at it once you outgrow the chat window.

How to choose

Start with LM Studio if you want to see the files you are choosing between. The app shows each quant as a separate download, which makes the tradeoff between Q4 and Q8 concrete before you commit disk space. It also suits anyone who does not want to touch a terminal.

Start with Ollama if you plan to connect other software to it through the local API, switch models from a script, or keep one model running on a home server with no screen attached.

You do not have to choose forever. The two can sit on the same machine. Load a model in one of them at a time, since two runtimes holding models at once draw on the same VRAM.

Whichever you pick, size the model first

The app does not change how much memory a model needs. An 8B model at Q4 comes to about 6.8 GB by the llmhardware.io formula, which fits an 8 GB card at a short context. Ollama's library lists the qwen3:8b download at 5.2 GB; the difference is runtime overhead and context. A 14B model at Q4 comes to about 10.4 GB and wants a 12 GB card.

The LM Studio vs Ollama comparison goes deeper on features. Before you download anything big, run the numbers in the VRAM calculator.

Sources: LM Studio app and developer docs (lmstudio.ai/docs), Ollama CLI reference and FAQ (docs.ollama.com), Ollama model library.

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