Runtime comparison
Ollama vs MLX LM
Ollama is a MIT-licensed runtime for Linux · macOS · Windows running on CUDA · Metal · CPU · ROCm; MLX LM is MIT-licensed for macOS on Metal. Ollama rates easier to set up (5/5 vs 4/5 in our sourced ratings). Pick Ollama for getting a model running fastest; pick MLX LM for maximum control over how the model runs.
| Spec | Ollama | MLX LM |
|---|---|---|
| License | MIT | MIT |
| Operating systems | Linux · macOS · Windows | macOS |
| GPU backends | CUDA · Metal · CPU · ROCm | Metal |
| Install | binary | pip |
| Ease of use | 5/5 | 4/5 |
| Quant formats | gguf | mlx |
| Engine | llama.cpp | mlx |
| GitHub stars | 175,773 | 6,236 |
| Latest version | v0.31.2 | v0.31.3 |
| Graphical app (GUI) | No | No |
| Server mode | Yes | Yes |
| OpenAI-compatible API | Yes | Yes |
| CPU offload | Yes | No |
| Multi-GPU | Yes | No |
| Speculative decoding | Yes | No |
| LoRA support | Yes | Yes |
| KV-cache quantization | Yes | Yes |
Which should you use?
Ollama
Best for getting a model running fastest. Command line and server, installs in one line, runs on CUDA · Metal · CPU · ROCm.
Full Ollama guide →MLX LM
Best for maximum control over how the model runs. Command line and server, runs on Metal.
Full MLX LM guide →Neither runtime changes whether a model fits — that is your memory and quantization. Check your hardware first, then pick the runtime.
Sources: Ollama github.com/ollama/ollama (as of 2026-07-11); MLX LM github.com/ml-explore/mlx-lm (as of 2026-07-08).