# Ollama vs LM Studio: Which Local LLM Runner

> Ollama is a scriptable CLI and daemon; LM Studio is a desktop app with a model browser. Both run GGUF locally, so pick by workflow, not quality.

- Canonical: https://guides-ai.com/guides/ollama-vs-lm-studio/
- Plate 11.06 · Topic: Choosing tools (https://guides-ai.com/topics/choosing/)
- Published: 19 Oct 2026 · 3 min read
- Source site: guides-ai — https://guides-ai.com/

Short: pick **Ollama** if you want a scriptable command line and a background API to build on; pick **LM Studio** if you want a graphical app to browse, download, and chat with models without a terminal. Both run the same GGUF models locally, so this is a workflow choice, not a quality one.

## 1. Decide by how you work

Ollama is a command-line tool plus a background daemon: you run models in a terminal, and it exposes a local HTTP API for scripts and apps. LM Studio is a desktop application with a model browser, a chat pane, and buttons.

## 2. Compare install and first run

After install, Ollama is one command:

```bash
ollama run llama3.2
```

Pulls the model if needed and drops you into a chat prompt. LM Studio uses a GUI installer; you then search for a model in the app and click download. See [run Ollama on macOS or Linux](/guides/run-local-llm-ollama-macos-linux/) and [get started with LM Studio](/guides/run-llm-lm-studio/).

## 3. Note the shared model format

Both run [GGUF](/glossary/#gguf) models through llama.cpp; LM Studio additionally runs Apple's MLX models on Apple Silicon. A GGUF you downloaded for one runs in the other, so your [quantization](/glossary/#quantization) choice carries across.

## 4. Compare the built-in API

Both expose an OpenAI-compatible server, so the same client code talks to either by changing the base URL:

```text
Ollama:     http://localhost:11434/v1
LM Studio:  http://localhost:1234/v1
```

Point an OpenAI SDK at one of these (1234 is LM Studio's default in its examples). Ollama's daemon serves this API whenever it is running; LM Studio serves it once you start its server; see [call the Ollama API](/guides/call-ollama-api/).

## 5. Choose for headless and server use

Ollama runs as a service by default, which suits always-on serving on a headless box. LM Studio ships a headless mode too:

```bash
lms server start --port 1234
```

Starts the server from a terminal, no GUI. Both then behave like a local OpenAI endpoint.

**If it fails:**

- OpenAI SDK returns 404: you pointed at the root, not the `/v1` base path shown above.
- LM Studio server refuses connections: it is not started; toggle the server on or run `lms server start`.
- Ollama API unreachable from another machine: it binds to localhost; set `OLLAMA_HOST=0.0.0.0:11434` and restart. Feature details in the [LM Studio API docs](https://lmstudio.ai/docs/app/api).