
Products
Melix
Local AI runtime engineered for Apple Silicon.
Melix runs machine learning inference entirely on-device — no cloud dependencies, no data leaving the machine. Fine-tune, benchmark, and serve models through an OpenAI-compatible API.
Key Features
Key features
The capabilities that matter in production: interfaces, controls, data flows, and operator workflows.

Product Context
What this product does, who it is for, and where it fits.
Melix runs machine learning inference entirely on-device — no cloud dependencies, no data leaving the machine. Fine-tune, benchmark, and serve models through an OpenAI-compatible API.
Implementation
Implementation details, integration guidance, and operating references.
Everything a team needs to evaluate adoption, integrate the product, and operate it responsibly.
Technical details
01MLX-powered local inference
Runs Apple MLX framework directly on Apple Silicon hardware for fast, energy-efficient on-device model execution.
02LoRA fine-tuning
Apply Low-Rank Adaptation to customize models locally without sending data to external training infrastructure.
03OpenAI-compatible HTTP API
Drop-in replacement for OpenAI API endpoints — existing tooling and coding agents work without modification.
04Service-first architecture
Runs as a persistent background service with gRPC and HTTP/SSE support, accessible to any local application.
Resources
01Homebrew Installation
Install and manage Melix via Homebrew. The formula handles runtime dependencies and service registration.
02CLI Reference
Automate model loading, benchmark execution, and adapter activation through the command-line interface.
03API Compatibility Guide
Configure existing OpenAI SDK clients to use Melix as a local backend with no code changes required.

CONTACT
Ready to run AI inference without cloud dependencies?
Melix keeps models, data, and inference on your machine — private, fast, and OpenAI-compatible.