LM Studio vs Ollama: which should you use to run LLMs locally?

LM Studio and Ollama both run open language models on your own computer, free for local use, and both can serve them to other apps through an OpenAI-compatible API. The short version: LM Studio is a polished desktop app built around a chat window and an in-app Hugging Face model browser, free at home and at work but not open source. Ollama is open source (MIT), built around a command line and its own model library, with a simple desktop app on macOS and Windows. Pick LM Studio if you want to explore models in a GUI; pick Ollama if you want something to script, run on a server or put in Docker.

Everything below was checked on each project’s official site, docs and GitHub as of November 2026. Both change quickly, so check the links before you rely on a detail.

LM Studio vs Ollama at a glance

	LM Studio	Ollama
What it is	Desktop app with a chat interface and a programmable API	Open-source tool to run and build with open models
Mac	Apple silicon only, macOS 14 or later	Apple M series (GPU) or Intel (CPU only), macOS 14 or later
Windows / Linux	Yes / yes	Yes / yes, plus a Docker image
Interface	Full GUI app; lms command line; headless mode	Desktop app on macOS and Windows; command line on all
License	Proprietary app (free); CLI, SDKs and MLX engine are MIT	Open source, MIT
Price for local use	Free, including at work	Free; local use is unlimited
Model formats	GGUF (llama.cpp) everywhere; MLX on Apple silicon	MLX engine on Apple silicon; GGUF via llama.cpp
Where models come from	Built-in Hugging Face search and downloader	The Ollama library (ollama pull), or import a GGUF
API	OpenAI-compatible (and Anthropic-compatible)	Own API plus an OpenAI-compatible subset
Port	1234 in the docs’ examples	11434 by default
Serve to other devices	“Serve on Local Network” setting	Set OLLAMA_HOST
iPhone / iPad	Locally AI by LM Studio	No official app
Paid extras	Cloud models in paid plans	Cloud models in paid plans

Sources: LM Studio docs, LM Studio system requirements, Ollama docs, Ollama on GitHub.

What each one is

LM Studio is a desktop app for downloading, running and chatting with LLMs on your computer. You search Hugging Face from inside the app, download a model, load it and chat. The same app runs a local API server, and it comes with a command-line tool (lms) and a headless version (llmster) for machines without a screen. Its homepage now also promotes LM Studio Bionic, an agent app; the classic LM Studio app is still a separate free download.

Ollama started as a command-line tool and server: ollama run llama3.2 downloads a model from the Ollama library and starts a chat in your terminal. Since July 2025 it also has a desktop app for macOS and Windows (Ollama blog), but its core is still the background server that other apps talk to. The code is open source under the MIT license.

Platforms and requirements

• Mac. LM Studio needs Apple silicon (M1 or later) and macOS 14 or later; Intel Macs aren’t supported. Ollama also needs macOS 14 or later, and runs on Apple M-series Macs with GPU acceleration or on Intel Macs on the CPU only.
• Windows. LM Studio supports x64 (with AVX2) and ARM. Ollama supports Windows 10 22H2 or later.
• Linux. Both run on Linux. Ollama also ships a Docker image, which makes it the usual choice for servers. Its desktop app is announced for macOS and Windows only; on Linux you run ollama serve.

Price and license

Both are free for running models on your own hardware.

• LM Studio has been free “at home and at work” since July 2025 (LM Studio blog). The app itself is proprietary; its CLI, its JavaScript and Python SDKs and its MLX engine are open source under MIT. As of November 2026, paid plans add cloud models: Bionic+ at $20 a month and Pro at $100 a month (pricing).
• Ollama is MIT-licensed open source. Running models on your own hardware is unlimited and free; as of November 2026, paid plans for its cloud models are Pro at $20 a month, Max at $100 a month and Team at $500 a month (pricing). Cloud models can be switched off entirely with OLLAMA_NO_CLOUD=1.

Models and engines: GGUF and MLX

Both now run the two main local formats.

• GGUF, the format of llama.cpp, runs on almost any hardware. LM Studio uses llama.cpp on every platform; Ollama added GGUF compatibility through llama.cpp in version 0.30 (June 2026).
• MLX, Apple’s machine learning framework, is built for Apple silicon. LM Studio runs MLX models on Apple silicon Macs, and Ollama on Apple silicon has been built on MLX since 2026 (Ollama blog). Our explainer What is MLX? covers why it suits Macs.

The bigger difference is where models come from. LM Studio searches Hugging Face directly, so almost any GGUF or MLX upload is a few clicks away. Ollama pulls from its own curated library by name (ollama pull qwen3), which is simpler but narrower; other GGUF files can be imported with a Modelfile.

Local server and API

This is where both shine, and why many people run them even if they never use their chat windows.

• LM Studio serves OpenAI-compatible endpoints (and Anthropic-compatible ones). Its docs use port 1234 in their examples. To let other devices on your network use it, turn on Serve on Local Network in the server settings (docs).
• Ollama has its own API plus a subset of the OpenAI API at http://localhost:11434/v1/. By default it listens only on 127.0.0.1:11434; to reach it from another device, set the OLLAMA_HOST environment variable (on a Mac running the Ollama app: launchctl setenv OLLAMA_HOST "0.0.0.0:11434", then restart Ollama) (Ollama FAQ).

Both support vision models, tool calling and structured output through their APIs.

Features beyond chat

• Documents. LM Studio lets you attach documents to a chat and work with them offline (retrieval, or RAG). The Ollama app supports dragging in text files and PDFs.
• MCP. LM Studio has a built-in MCP client, so local models can use MCP tools. We found no built-in MCP client documented for Ollama.
• Headless use. LM Studio has llmster and lms; Ollama has ollama serve and Docker.
• Phone. LM Studio’s iPhone and iPad app, Locally AI by LM Studio, runs models on the phone with MLX and connects to LM Studio on your computer through LM Link (App Store). Ollama has no official mobile app; you use a third-party client (see Ollama GUI apps).

Privacy

Both are local by design. LM Studio’s docs say that nothing you enter when chatting leaves your device (docs). Ollama’s FAQ says it doesn’t see your prompts or data when you run locally (FAQ). Their optional cloud models are different: those requests go to their servers, under the zero-data-retention policies each describes.

Use either one from your iPhone with Modelbase

Both tools can serve a model to your phone. Modelbase, our free app for iPhone, iPad and Mac, connects to any OpenAI-compatible server, and its setup screen names Ollama and LM Studio as examples:

1. On your computer, make the server reachable: turn on Serve on Local Network in LM Studio, or set OLLAMA_HOST for Ollama as above.
2. In Modelbase, open the model picker, tap Manage models, then + and Custom Server.
3. Enter your computer’s address on your network, for example http://192.168.1.20:11434 for Ollama or port 1234 for LM Studio. Modelbase adds the /v1 path itself. An API key is optional.
4. Tap Test Connection. The server’s models appear under Models on This Server; save, and pick one in the model picker.

Plain http works only on your own network; outside it, the server needs https. The model runs on your computer, so your messages go to it, and nowhere else. When you’re away from home, Modelbase still has its own models that run on the phone itself (how that works).

Which should you choose?

Choose LM Studio if you want a desktop app to browse, download and compare models from Hugging Face, chat with documents, or use MCP tools, and you’re on an Apple silicon Mac, Windows or Linux.

Choose Ollama if you want open source, a server for scripts and other apps, Docker or a Linux box, or an Intel Mac (CPU only).

Use both if you like. Many people browse and test in LM Studio and run Ollama as an always-on server. They don’t conflict as long as they use different ports.

FAQ

Is LM Studio free for commercial use?

Yes. Since July 2025, LM Studio is free to use at home and at work. Its paid plans (as of November 2026) are for cloud models, not for using the app.

Is Ollama open source?

Yes. Ollama is open source under the MIT license, on GitHub.

Is Ollama safe and private?

When it runs models locally, Ollama says it doesn’t see your prompts or data. By default it listens only on your own computer (127.0.0.1); opening it to your network with OLLAMA_HOST means other devices on that network can use it too, so only do that on a network you trust.

Which is faster, LM Studio or Ollama?

It depends on the model, the format and your hardware, and both use the same kinds of engines (llama.cpp and MLX on Apple silicon), so there’s no general winner. Try the same model in both on your machine.

Do LM Studio and Ollama work on Intel Macs?

Ollama does, on the CPU only. LM Studio requires Apple silicon.

Can I use LM Studio or Ollama on my iPhone?

Not directly: both run on computers. LM Studio’s own iPhone app, Locally AI, connects to it; for Ollama, use a client app. Modelbase connects to either as a custom server, and also runs models on the iPhone itself.