Comparison · Local AI & Hardware
Ollama vs LM Studio: which one should you use?
Short answer
Ollama is open source (MIT) and built around a command line, a background service and an API on port 11434: best for scripts, coding agents and servers. LM Studio is a free but closed-source desktop app, licensed for personal and internal business use, with a model browser, offline chat with documents and an API on port 1234. Both offer OpenAI- and Anthropic-compatible endpoints.
Prices, limits and features change often. We date every figure and link to its source: check the vendor's page before you buy or build. How we make money.
Ollama and LM Studio both run open models such as Qwen, Gemma, Llama and gpt-oss on your own computer, and both can serve them to other apps through an API. The real differences are in the license, the interface and how each one fits into your workflow. This comparison is built from each project's own documentation and terms, checked on October 1, 2026. We did not run speed benchmarks, and speed depends far more on your hardware and the model you pick than on the app.
The short version
| Ollama | LM Studio | |
|---|---|---|
| License | Open source (MIT) | Proprietary; free license for "personal and / or internal business purposes" |
| Main interface | Command line and a background service, plus a desktop app | Desktop app with chat, model browser and settings, plus a CLI (lms) |
| Local API | http://localhost:11434, with OpenAI- and Anthropic-compatible endpoints |
http://localhost:1234/v1, with OpenAI- and Anthropic-compatible endpoints |
| Models | Ollama library, by name and tag (some models also have MLX variants) | GGUF via llama.cpp on all systems; MLX on Apple Silicon; downloads from Hugging Face |
| Headless / server use | Built in (ollama serve, systemd service on Linux) |
llmster daemon, no GUI needed |
| Cloud option | Optional cloud models with an Ollama account | Not covered here |
Pick Ollama if you mostly want a model running in the background for scripts, coding agents or other apps, if you need an open-source license, or if you plan to run it on a server.
Pick LM Studio if you want a polished desktop app to browse, download and chat with models, attach documents and compare settings without a terminal.
License and price
This is the biggest practical difference. Ollama's code is released under the MIT license on GitHub, so you can use it, modify it and build it into products.
LM Studio is closed source. Its terms grant "a non-exclusive, non-transferable license to use the Software solely for Your personal and / or internal business purposes". The same terms forbid offering it to third parties "as an application service provider, or a software-as-a-service". In plain terms: you can use LM Studio for free at work, but you cannot resell it or run it as a service for customers. The terms also mention optional paid features (subscriptions or usage credits).
Ollama is free to run locally. Its cloud models are a separate, account-based service; Ollama's documentation says it does not use cloud prompts and responses to train models, and that cloud features can be disabled if you only want local models.
Platforms and hardware
| Ollama | LM Studio | |
|---|---|---|
| Windows | Windows 10 22H2 or newer; NVIDIA and AMD Radeon GPUs; installs without administrator rights | x64 with AVX2, or ARM (Snapdragon X Elite); 16 GB RAM and 4 GB of VRAM recommended |
| macOS | macOS Sonoma (14) or newer; Apple M-series (CPU and GPU) or Intel (CPU only) | macOS 14 or newer on Apple Silicon only; Intel Macs not supported |
| Linux | Install script or manual package; NVIDIA (CUDA), AMD (ROCm 7) and Vulkan | AppImage for x64 and ARM64; Ubuntu 20.04 or newer |
On GPUs, Ollama documents support for NVIDIA cards with compute capability 5.0 or newer, AMD cards through ROCm, Apple GPUs through Metal and other cards through Vulkan. If you are unsure whether your card has enough memory for a given model, use our VRAM calculator.
Everyday use
Ollama is built around a few commands: ollama pull qwen3:8b downloads a model, ollama run qwen3:8b opens a chat with it in the terminal, and ollama ps shows what is loaded and whether it runs fully on the GPU. Models come from the Ollama library by name and tag, with the download size listed on each page (for example, 5.2 GB for qwen3:8b and 14 GB for gpt-oss:20b). There is also a desktop app, and the command line can launch coding agents such as Claude Code, Codex or OpenCode (for example, ollama launch claude).
LM Studio is built around its window. The Discover tab searches and downloads models (from Hugging Face), the Chat tab loads one (with optional load settings) and starts a conversation, and you can attach documents to a conversation and query them entirely offline. It can also act as an MCP client, connecting local models to tools.
For developers
Both expose an API on your machine, so apps written for OpenAI's or Anthropic's API can talk to a local model by changing the base URL:
- Ollama:
http://localhost:11434/v1for OpenAI-style clients andhttp://localhost:11434for Anthropic-style clients. Ollama's documentation notes that it supports "a subset" of each API. - LM Studio:
http://localhost:1234/v1for OpenAI-style clients, plus an Anthropic-compatible endpoint, a REST API and official TypeScript and Python SDKs.
For servers and CI, Ollama runs as a regular service (ollama serve, or a systemd unit on Linux). LM Studio's equivalent is llmster, "LM Studio's core, packaged as a daemon for headless deployment", which does not need the desktop app.
Can you use both?
Yes. They listen on different ports (11434 and 1234), so they can run on the same computer. Each one downloads and stores its own models (Ollama keeps them in ~/.ollama on macOS and in %HOMEPATH%.ollama on Windows), so the same model installed in both takes up disk space twice.
What we did not test
We have not measured speed, memory use or output quality in either app, and we do not rank them. The comparison above is limited to what each project documents. If you have run both on the same hardware and found a difference worth reporting, tell us.
To get started with Ollama step by step, see how to run an LLM locally.
What we checked
- Ollama is released under the MIT license; install commands are curl -fsSL https://ollama.com/install.sh | sh on macOS and Linux and irm https://ollama.com/install.ps1 | iex on Windows. (Ollama (GitHub), )
- Ollama's CLI includes run, pull, ls, ps, stop, rm and launch (integrations such as Claude Code, Codex and OpenCode). (Ollama (GitHub docs), )
- LM Studio's license is limited to personal and/or internal business purposes and forbids software-as-a-service use; some features may be paid. (LM Studio, )
- Ollama supports a subset of the OpenAI API at http://localhost:11434/v1. (Ollama, )
- Ollama supports Anthropic-style clients at http://localhost:11434. (Ollama, )
- LM Studio's OpenAI-compatible server uses http://localhost:1234/v1. (LM Studio, )
- LM Studio offers OpenAI- and Anthropic-compatible endpoints, a REST API, TypeScript and Python SDKs and the headless llmster daemon. (LM Studio, )
- LM Studio runs GGUF models via llama.cpp and MLX models on Apple Silicon, searches models via Hugging Face, chats with documents offline and acts as an MCP client. (LM Studio, )
- LM Studio requires macOS 14 on Apple Silicon (Intel Macs unsupported), AVX2 on x64 Windows or Snapdragon X Elite, and Ubuntu 20.04 or newer on Linux; 16 GB RAM and 4 GB VRAM recommended on Windows. (LM Studio, )
- Ollama for Windows needs Windows 10 22H2 or newer, supports NVIDIA and AMD Radeon GPUs and installs without administrator rights; models are stored in %HOMEPATH%\.ollama. (Ollama, )
- Ollama for macOS needs Sonoma (14) or newer; Apple M-series use CPU and GPU, Intel Macs run on the CPU only; models are stored in ~/.ollama. (Ollama, )
- Ollama supports NVIDIA GPUs with compute capability 5.0+, AMD GPUs via ROCm, Apple GPUs via Metal and other GPUs via Vulkan. (Ollama, )
- Ollama does not use cloud prompts and responses to train models, and cloud features can be disabled. (Ollama, )
- Ollama download size of qwen3:8b: 5.2 GB. (Ollama, )
- Ollama download size of gpt-oss:20b: 14 GB. (Ollama, )
- LM Studio downloads models from the Discover tab and loads them in the Chat tab with optional load settings. (LM Studio, )
What may change
- Both apps release new versions often; features, ports and supported systems can change.
- LM Studio's terms and paid features can change; check the current terms before relying on them commercially.
- Ollama's cloud plans and limits are outside this comparison and change independently.
Frequently asked questions
Is LM Studio free for commercial use?
LM Studio's terms license it for personal and internal business purposes, so you can use it at work for free. The same terms forbid offering it to others as a hosted service or reselling it. Some features may be paid.
Is Ollama open source?
Yes. Ollama's code is published on GitHub under the MIT license. Its optional cloud models are a separate service that needs an Ollama account.
Which ports do Ollama and LM Studio use?
Ollama serves its API on http://localhost:11434 (OpenAI-style clients use /v1). LM Studio's OpenAI-compatible server uses http://localhost:1234/v1. Because the ports differ, both can run on the same computer.
Which one is faster?
We have not benchmarked them. Speed depends mostly on your GPU, the model and its quantization. Check whether a model fits your memory first with our VRAM calculator.
Sources
- ollama/ollama: README (install commands) and MIT license, Ollama (GitHub). Accessed October 1, 2026.
- Ollama CLI reference: run, pull, ls, ps, stop, rm, launch, Ollama (GitHub docs). Accessed October 1, 2026.
- Ollama: OpenAI compatibility, Ollama. Accessed October 1, 2026.
- Ollama: Anthropic compatibility, Ollama. Accessed October 1, 2026.
- Ollama cloud: models, usage and data handling, Ollama. Accessed October 1, 2026.
- Ollama on Windows: system requirements, install location and models, Ollama. Accessed October 1, 2026.
- Ollama on macOS: system requirements, Ollama. Accessed October 1, 2026.
- Ollama: hardware support (NVIDIA, AMD ROCm, Apple Metal, Vulkan), Ollama. Accessed October 1, 2026.
- Ollama library: qwen3 (tags and download sizes), Ollama. Accessed October 1, 2026.
- LM Studio app terms of use, LM Studio. Accessed October 1, 2026.
- LM Studio documentation, LM Studio. Accessed October 1, 2026.
- LM Studio developer docs: local server and OpenAI-compatible API, LM Studio. Accessed October 1, 2026.
- LM Studio: OpenAI compatibility endpoints, LM Studio. Accessed October 1, 2026.
- LM Studio: system requirements, LM Studio. Accessed October 1, 2026.
- Ollama library: gpt-oss (tags and download sizes), Ollama. Accessed October 1, 2026.
- LM Studio: get started (download and load a model), LM Studio. Accessed October 1, 2026.
Spotted an error or an outdated price? Tell us and we will fix it.
Change history
- : First published, from each project's documentation, terms and repository.
Next review: .