oMLX
What is oMLX?
oMLX is a native macOS inference server for running local AI models on Apple Silicon using Apple's MLX framework. It provides paged SSD KV caching to reduce time-to-first-token for coding agents, continuous batching for higher throughput, and OpenAI- and Anthropic-compatible APIs. oMLX supports LLM, vision-language, embedding, and reranker models, along with tool calling, MCP integration, multi-model serving, and a native menu bar application with a web dashboard.
How to use oMLX?
Download the signed macOS DMG and drag oMLX to the Applications folder, then configure the model directory, start the server, and download or select an MLX-format model. Alternatively, install from source with Python 3.10+ using the provided Git commands and run omlx serve with a model directory. Connect Claude Code, OpenClaw, Cursor, or other compatible clients through the OpenAI or Anthropic API endpoints.
oMLX's Core Features
Paged SSD KV caching for faster responses and reduced time-to-first-token
Continuous batching for concurrent request throughput
OpenAI-compatible and Anthropic-compatible APIs
Native macOS menu bar application
Web dashboard for model management, chat, and real-time metrics
Multi-model serving for LLM, VLM, embedding, and reranker models
Tool calling and MCP integration
Support for MLX-format models from Hugging Face
LRU model eviction when memory is limited
Automatic reuse of Hugging Face and LM Studio model caches
oMLX's Use Cases
Run local coding agents with faster responses on Apple Silicon Macs
Use Claude Code, OpenClaw, or Cursor with a local AI backend
Serve multiple local language and vision models through compatible APIs
Build applications using local OpenAI-compatible or Anthropic-compatible inference
Test tool calling and MCP workflows without relying on cloud inference
Run private local chat, embedding, reranking, and multimodal workloads
FAQ from oMLX
How is oMLX different from Ollama or LM Studio?
What hardware does oMLX require?
Does oMLX work with Claude Code, OpenClaw, and Cursor?
Do existing models need to be downloaded again?
What models are supported?
Does oMLX support tool calling?
How can oMLX be installed?
Is oMLX free to use?
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