Comparison

Ollama vs. LM Studio vs. llama.cpp vs. MLX: which should you use?

By Claudio A. G. M. Filho · Updated October 21, 2026

These tools offer different routes to local language models. The overview below is based on their documentation, not an independent performance comparison. Model compatibility, licensing, and memory requirements still need checking for the selected version.

LM Studio

A free desktop app for discovering, downloading and chatting with models, with an OpenAI-compatible local server. On Apple Silicon it offers an MLX engine alongside llama.cpp. MacModelFit has not benchmarked it against the other tools.

Ollama

A CLI and API many local-model applications integrate with. Since v0.40 it picks MLX automatically on Apple Silicon for supported architectures. See our Ollama setup guide.

llama.cpp

The engine underneath much of the ecosystem, and the origin of the GGUF format. Install with Homebrew and serve a model straight from Hugging Face:

brew install llama.cpp
llama-server -hf ggml-org/gemma-3-1b-it-GGUF

MLX / mlx-lm

Apple's open-source framework, with Python APIs and LoRA fine-tuning support. See our MLX guide.

Choose by the workflow

• Just want to chat privately: LM Studio.
• Want local models inside your tools and agents: Ollama.
• Want to tinker, benchmark, or run exotic quantizations: llama.cpp.
• Building or fine-tuning in Python: mlx-lm.

Speed differs by model, quantization and chip; we don't quote cross-tool speed rankings without a controlled, sourced test. Measure on your own Mac with the same prompt in each.