Ollama vs LM Studio on Windows: which to use
Ollama and LM Studio are the two most popular ways to run AI models on your own PC. Both are free, both run the same open models — Llama, Qwen, Gemma, gpt-oss, DeepSeek and the rest — and both are built on the same engine, llama.cpp. The differences are in how you use them, and in a few settings that decide how fast a model runs.
Updated 9 November 2026
The difference in one line
LM Studio is a desktop app you work in: find a model, download it, choose its settings and chat. Ollama is a service that runs quietly in the background for other programs to use, with a simple chat window and a command line on top.
| Ollama | LM Studio | |
|---|---|---|
| Cost | Free and open source (MIT licence) | Free, at home and at work; the app is not open source |
| How you use it | A chat window, ollama run in a terminal, or other apps through it | A full desktop app: search, download, chat, documents |
| Where models come from | Its own library on ollama.com, or any GGUF file on Hugging Face | Any GGUF file on Hugging Face, from a search inside the app |
| Graphics cards | NVIDIA; AMD and Intel through ROCm or Vulkan | NVIDIA through CUDA; AMD and Intel through Vulkan |
| How much goes on the card | Decided for you, when the model loads | You choose, with the GPU Offload slider |
| Conversation length | Chosen by how much memory the card has (4K tokens under 24 GB); a slider in its settings changes it | Set for each model when it loads |
| For other apps | Always on, at localhost:11434 | When you start its server, at localhost:1234 |
Which is faster?
With the same model file, the same conversation length and all of it on the graphics card, they write at about the same speed: the same engine does the work. Where one is much faster than the other on your PC, one of these is nearly always the reason:
- Part of the model is on the processor in one of them. Ollama decides this itself and
does not say; in LM Studio it is the GPU Offload slider.
ollama psshows Ollama’s split, and Ollama using the CPU instead of the GPU and LM Studio not using the GPU cover the fixes. - A different conversation length. The card keeps room for the whole conversation, so a longer setting can push the model partly off the card.
- A different file. Ollama’s default tag for a model is usually Q4_K_M; in LM Studio you may have picked a bigger or smaller one. Which GGUF file to download explains the sizes.
- A different engine version or option, such as flash attention, which LM Studio lets you switch per model. Either can come out ahead after an update.
Which should you use?
- To chat with models and try different ones, LM Studio is the easier start: you see each model’s files and sizes, and every setting is in front of you.
- To give other apps a model — a coding assistant in your editor, Open WebUI, notes apps or your own scripts — Ollama is the usual choice: it starts with Windows, loads models when they are asked for and unloads them after a few minutes.
- To control exactly how a model runs, LM Studio shows more: how many layers go on the card, the conversation length and other options for each model.
You can install both. They keep their own copies of models, so a model downloaded in both takes the space twice. And with a model loaded in each at once, the two share the card’s memory, which can push both partly onto the processor.
What your PC needs for either
The model has to fit in memory, and runs fast only when all of it fits on the graphics card. 8 GB of graphics memory runs 8B models well, 16 GB runs gpt-oss 20B, and 24 GB runs 30B models. Can my PC run AI? shows every model for your parts, and Best GPU for local AI compares the cards.
How Bottleneck checks both
Bottleneck’s free app has a Check my local AI button on its AI models screen. With Ollama it times one short answer and reads exactly how much of the model is on the card; with LM Studio it watches while you ask something. Either way it says where the model is running and how fast it writes, next to what your PC should manage. Pro adds why it is slower, and the fix.