MLX Server

A high-performance inference server for MLX models, providing an OpenAI-compatible API for running large language models on Apple Silicon.

Features

• OpenAI-Compatible API - Drop-in replacement for OpenAI API calls
• Streaming Support - Server-Sent Events for real-time token streaming
• Tool Calling - Support for function calls (OpenAI-compatible format)
• Multi-Model Support - LLM and VLM model support

Requirements

• macOS 14.0+ (Sonoma or later)
• Apple Silicon (M1, M2, M3, M4)
• Xcode 15+ for building
• At least 8GB of unified memory

Installation

Building from Source

# Clone the repository
cd mlx-server

# Build in release mode
xcodebuild -scheme mlx-server -configuration Release

# The binary and metallib will be in the Xcode derived data build products

Quick Start

# Run with a local MLX model
./.build/arm64-apple-macosx/release/mlx-server \
  --model "/path/to/your/model" \
  --port 8080

Command-Line Options

Option	Default	Description
-m, --model	Required	Path to model directory or HuggingFace model ID
--port	8080	HTTP server port
--ctx-size	4096	Context window size
--api-key	""	API key for authentication (optional)

API Endpoints

Chat Completions

curl -X POST http://localhost:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "model",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Hello, how are you?"}
    ],
    "temperature": 0.7,
    "max_tokens": 100
  }'

Streaming Response

curl -X POST http://localhost:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "model",
    "messages": [{"role": "user", "content": "Tell me a story."}],
    "stream": true
  }'

Cancel Active Generation

curl -X POST http://localhost:8080/v1/cancel

List Models

curl http://localhost:8080/v1/models

Health Check

curl http://localhost:8080/health

Project Structure

mlx-server/
├── Sources/
│   └── MLXServer/
│       ├── MLXServerCommand.swift    # CLI entry point
│       ├── ModelRunner.swift          # Core inference engine
│       ├── Server.swift               # HTTP server & API handlers
│       ├── OpenAITypes.swift          # API type definitions
│       └── Logger.swift               # Logging utilities
├── Package.swift                      # Swift package manifest
└── README.md                          # This file

Architecture

Core Components

1. ModelRunner - Manages model loading and inference (streaming and non-streaming)
2. MLXHTTPServer - HTTP server with OpenAI-compatible endpoints
3. ActiveGenerations - Tracks and manages cancellable generation tasks

Notes

• The server binds to 127.0.0.1 (localhost only) for security
• Client disconnects automatically cancel the active generation
• VLM (vision-language models) are supported via image/video URL inputs

Troubleshooting

Model Loading Fails

Ensure the model directory contains:

• config.json - Model configuration
• tokenizer.json - Tokenizer vocabulary
• model.safetensors or model.safetensors.index.json - Model weights
• Optional: generation_config.json, chat_template.jinja

Port Already in Use

Change the port:

--port 8081

Benchmarking

Use the mlx-lm server benchmark script to measure throughput and latency:

python server_benchmark.py --url http://localhost:8080/v1/chat/completions --model model

License

This project is part of Jan - an open-source desktop AI application.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

Resources

• MLX Swift
• MLX Swift LM
• OpenAI Chat Completions API