Ollama vs. llama.cpp vs. LM Studio: Which Local LLM Tool Should You Use?

What Ollama, llama.cpp, and LM Studio actually do differently, including a real hardware-acceleration gap between Ollama on Windows and Linux.

Anyone looking into running AI locally runs into the same three names: Ollama, llama.cpp, and LM Studio. They’re related, Ollama and LM Studio are both built on llama.cpp’s engine, but they’re not interchangeable. Which one fits depends on your OS and how much you want to touch a command line.

LM Studio: the one we ship by default

LM Studio is a real desktop app: browse models, download them, chat with them, no command line required. It ships preinstalled on every AI Workstation we build, Windows 11 Pro or Ubuntu Desktop, and it runs the same Vulkan/llama.cpp backend on both. Pick either OS and you get the same experience.

If you want to run a model today with the least amount of friction, this is it.

Ollama: the developer favorite, with an OS-specific catch

Ollama is command-line first, built for scripting and integration. Reach for it when you want to call a local model from your own code instead of chatting with it in a window. It’s genuinely good at that job.

Here’s the catch, and it’s a real one: Ollama’s hardware acceleration isn’t the same across operating systems. On Windows, it’s Vulkan only. On Linux, it gets native ROCm support, AMD’s own GPU compute stack, which the Windows build simply doesn’t have. This isn’t a setting you flip; it’s a difference baked into each build. If you’re planning to lean on Ollama and choosing between Windows and Ubuntu for your workstation, factor this in.

Ollama comes with our AI Tooling Package on every system we sell, either OS. Just know which backend you’re actually getting.

llama.cpp: the engine behind both

llama.cpp is the inference engine underneath both of the above. Run it directly and you get the most control and the newest features first, new model support usually lands here before it reaches Ollama or LM Studio. The tradeoff is a steeper learning curve: you’re closer to the command line and the raw model files.

Unlike Ollama, llama.cpp supports both Vulkan and ROCm/HIP on Windows and on Ubuntu; no OS-specific gap here. Want AMD ROCm acceleration on Windows specifically? Use llama.cpp, not Ollama.

So which one?

Want a chat interface, no command line, the same experience on either OS? Use LM Studio.

Want to script against a local model or integrate it into your own tools? Use Ollama (check the Windows-vs-Linux backend note above first).

Want maximum control, the earliest access to new models, and ROCm on Windows? Use llama.cpp directly.

Most people start with LM Studio, then add Ollama or llama.cpp once they actually need to automate something. That’s a normal path, starting simple doesn’t lock you out of the advanced tools later. All three run on the same hardware. This is a software choice, not a purchase decision.

A note on root access

Every system we sell comes with SSH and root or administrator access. Nothing’s locked down. Install any of these three, or anything else, without going through us. It’s your machine.

Whichever tool you pick, you still need the right hardware under it: see how much VRAM your model actually needs and what our 64GB and 128GB configs can run.