Runtime comparison - verified
MLX-LM vs llama.cpp
MLX-LM (Apple (ml-explore)) and llama.cpp (ggml-org), compared field by field from their official docs as of October 18, 2026. Their docs differ on 10 feature points, listed below; the table also shows versions, install methods and links.
Key differences
- Interface: MLX-LM lists Python library and llama.cpp does not; llama.cpp lists Docker and MLX-LM does not.
- Platforms: llama.cpp lists Windows and MLX-LM does not.
- Backends: llama.cpp lists ROCm, Vulkan, SYCL, NPU and Other and MLX-LM does not.
- Model formats: MLX-LM lists MLX and llama.cpp does not; llama.cpp lists GGUF and MLX-LM does not.
- Anthropic-compatible API: MLX-LM does not state it in its docs; llama.cpp documents it.
- Tool calling: MLX-LM does not state it in its docs; llama.cpp documents it.
- Structured outputs: MLX-LM does not state it in its docs; llama.cpp documents it.
- Vision (image input): MLX-LM does not state it in its docs; llama.cpp documents it.
- Multi-GPU: MLX-LM does not state it in its docs; llama.cpp documents it.
- MCP client: MLX-LM does not state it in its docs; llama.cpp documents it.
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 | MLX-LM | llama.cpp |
|---|---|---|
| VendorDiffers | Apple (ml-explore) | ggml-org |
| License | MIT | MIT |
| Open source | Yes | Yes |
| Latest releaseDiffers | v0.32.2 | v0.7.0 |
| Release dateDiffers | October 16, 2026 | October 15, 2026 |
| InterfaceDiffers | CLI, Server, Python library | CLI, Server, Docker |
| PlatformsDiffers | macOS, Linux | macOS, Windows, Linux |
| BackendsDiffers | Metal, CUDA, CPU | CPU, CUDA, ROCm, Metal, Vulkan, SYCL, NPU, Other |
| Model formatsDiffers | MLX | GGUF |
| OpenAI-compatible API | Yeshttp://localhost:8080/v1 (mlx_lm.server listens on port 8080 of localhost; the HTTP API is described as similar to the OpenAI chat API and is not recommended for production) | 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 APIDiffers | Not stated | Yes |
| Tool callingDiffers | Not stated | Yes |
| Structured outputsDiffers | Not stated | Yes |
| Vision (image input)Differs | Not stated | Yes |
| Multi-GPUDiffers | Not stated | Yes |
| MCP clientDiffers | Not stated | Yes |
| Install methods listedDiffers | macos (Apple silicon, pip); macos (Apple silicon, conda) | macOS / Linux (curl); Windows (PowerShell); macOS / Linux (Homebrew); Windows (Winget) |
| Run exampleDiffers | mlx_lm.server --model mlx-community/Mistral-7B-Instruct-v0.3-4bit | llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF |
| Audience, per the vendorDiffers | A Python package for generating text and fine-tuning large language models on Apple silicon with MLX, offering a CLI, a Python API and a basic local HTTP server. | 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 | github.com/ml-explore/mlx-lm | github.com/ggml-org/llama.cpp |
| Source repositoryDiffers | github.com/ml-explore/mlx-lm | github.com/ggml-org/llama.cpp |
Install both
Copied verbatim from the page linked under each command.
MLX-LM
macos (Apple silicon, conda)
conda install -c conda-forge mlx-lmSource: github.com/ml-explore/mlx-lm
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 MLX-LM and llama.cpp?
Going by their official docs: Interface: MLX-LM lists Python library and llama.cpp does not; llama.cpp lists Docker and MLX-LM does not. Platforms: llama.cpp lists Windows and MLX-LM does not. Backends: llama.cpp lists ROCm, Vulkan, SYCL, NPU and Other and MLX-LM does not. Model formats: MLX-LM lists MLX and llama.cpp does not; llama.cpp lists GGUF and MLX-LM does not. The table lists 6 more.
Do MLX-LM and llama.cpp both have an OpenAI-compatible API?
MLX-LM: yes. http://localhost:8080/v1 (mlx_lm.server listens on port 8080 of localhost; the HTTP API is described as similar to the OpenAI chat API and is not recommended for production). 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 MLX-LM and llama.cpp run on?
MLX-LM: macOS, Linux. llama.cpp: macOS, Windows, Linux. Both list macOS and Linux.
Are MLX-LM and llama.cpp open source?
MLX-LM is open source (MIT). llama.cpp is open source (MIT).
Do MLX-LM and llama.cpp support tool calling and MCP?
Tool calling: MLX-LM not stated, llama.cpp yes. MCP client: MLX-LM not stated, llama.cpp yes. "Not stated" means the docs do not say.
What are the latest versions of MLX-LM and llama.cpp?
As of October 18, 2026: MLX-LM v0.32.2 (October 16, 2026) and llama.cpp v0.7.0 (October 15, 2026).
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