Runtime comparison - verified
LM Studio vs llama.cpp
LM Studio (Element Labs, Inc.) and llama.cpp (ggml-org), compared field by field from their official docs as of October 18, 2026. Their docs differ on 5 feature points, listed below; the table also shows versions, install methods and links.
Key differences
- License: llama.cpp is open source (MIT); LM Studio is not (LM Studio Terms of Use for the app, MIT for the lms CLI).
- Interface: LM Studio lists Desktop app and llama.cpp does not; llama.cpp lists Docker and LM Studio does not.
- Backends: llama.cpp lists SYCL, NPU and Other and LM Studio does not.
- Model formats: LM Studio lists MLX and llama.cpp does not.
- Source: llama.cpp has a public repository; LM Studio lists none.
Generated from the fields below that differ. Versions, dates and links are left to the table.
Side by side
Every field we track, with the source linked on each value. Rows marked Differs are where the two runtimes' docs differ.
| Field | LM Studio | llama.cpp |
|---|---|---|
| VendorDiffers | Element Labs, Inc. | ggml-org |
| LicenseDiffers | LM Studio Terms of Use for the app, MIT for the lms CLI | MIT |
| Open sourceDiffers | No | Yes |
| Latest releaseDiffers | 0.4.26 | v0.7.0 |
| Release dateDiffers | October 13, 2026 | October 15, 2026 |
| InterfaceDiffers | Desktop app, CLI, Server | CLI, Server, Docker |
| Platforms | macOS, Windows, Linux | macOS, Windows, Linux |
| BackendsDiffers | CPU, CUDA, Vulkan, ROCm, Metal | CPU, CUDA, ROCm, Metal, Vulkan, SYCL, NPU, Other |
| Model formatsDiffers | GGUF, MLX | GGUF |
| OpenAI-compatible API | Yeshttp://localhost:1234/v1 | Yesllama-server listens on http://127.0.0.1:9931 by default (--host 127.0.0.1, --port 9931); OpenAI-compatible routes are under /v1 |
| Anthropic-compatible API | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured outputs | Yes | Yes |
| Vision (image input) | Yes | Yes |
| Multi-GPU | Yes | Yes |
| MCP client | Yes | Yes |
| Install methods listedDiffers | macOS / Linux (llmster headless daemon); Windows (llmster headless daemon) | macOS / Linux (curl); Windows (PowerShell); macOS / Linux (Homebrew); Windows (Winget) |
| Run exampleDiffers | lms load openai/gpt-oss-20b | llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF |
| Audience, per the vendorDiffers | People who want a desktop app with a chat interface for downloading and running GGUF and MLX models locally, plus a local OpenAI-compatible server and a headless daemon (llmster) for servers and CI. | Developers who want a dependency-free C/C++ inference engine, with a CLI and an OpenAI-compatible server, for running GGUF models on a wide range of CPUs and GPUs locally or in the cloud. |
| HomepageDiffers | lmstudio.ai | github.com/ggml-org/llama.cpp |
| Source repositoryDiffers | None listed | github.com/ggml-org/llama.cpp |
Install both
Copied verbatim from the page linked under each command.
LM Studio
macOS / Linux (llmster headless daemon)
curl -fsSL https://lmstudio.ai/install.sh | bashSource: lmstudio.ai/download
Windows (llmster headless daemon)
irm https://lmstudio.ai/install.ps1 | iexSource: lmstudio.ai/download
llama.cpp
macOS / Linux (curl)
curl -LsSf https://llama.app/install.sh | shSource: github.com/ggml-org/llama.cpp
Windows (PowerShell)
irm https://llama.app/install.ps1 | iexSource: github.com/ggml-org/llama.cpp
macOS / Linux (Homebrew)
brew install llama.cppSource: github.com/ggml-org/llama.cpp/blob/master/docs/install.md
Windows (Winget)
winget install llama.cppSource: github.com/ggml-org/llama.cpp/blob/master/docs/install.md
FAQ
What is the difference between LM Studio and llama.cpp?
Going by their official docs: License: llama.cpp is open source (MIT); LM Studio is not (LM Studio Terms of Use for the app, MIT for the lms CLI). Interface: LM Studio lists Desktop app and llama.cpp does not; llama.cpp lists Docker and LM Studio does not. Backends: llama.cpp lists SYCL, NPU and Other and LM Studio does not. Model formats: LM Studio lists MLX and llama.cpp does not. The table lists 1 more.
Do LM Studio and llama.cpp both have an OpenAI-compatible API?
LM Studio: yes. http://localhost:1234/v1. llama.cpp: yes. llama-server listens on http://127.0.0.1:9931 by default (--host 127.0.0.1, --port 9931); OpenAI-compatible routes are under /v1.
Which platforms do LM Studio and llama.cpp run on?
LM Studio: macOS, Windows, Linux. llama.cpp: macOS, Windows, Linux. Both list macOS, Windows and Linux.
Are LM Studio and llama.cpp open source?
LM Studio is not open source (LM Studio Terms of Use for the app, MIT for the lms CLI). llama.cpp is open source (MIT).
Do LM Studio and llama.cpp support tool calling and MCP?
Tool calling: LM Studio yes, llama.cpp yes. MCP client: LM Studio yes, llama.cpp yes. "Not stated" means the docs do not say.
What are the latest versions of LM Studio and llama.cpp?
As of October 18, 2026: LM Studio 0.4.26 (October 13, 2026) and llama.cpp v0.7.0 (October 15, 2026).
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