# Swift Mlx

MLX Swift - High-performance ML framework for Apple Silicon with lazy evaluation...

- Repository: https://github.com/kellyvv/PhoneClaw (1286 stars)
- Category: Data and ML
- License: Apache-2.0
- Last updated: 2026-08-06
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add kellyvv/PhoneClaw --skill swift-mlx -g -a claude-code -y`
Codex: `npx skills add kellyvv/PhoneClaw --skill swift-mlx -g -a codex -y`
Cursor: `npx skills add kellyvv/PhoneClaw --skill swift-mlx -g -a cursor -y`
Gemini CLI: `npx skills add kellyvv/PhoneClaw --skill swift-mlx -g -a gemini-cli -y`

## Description

MLX Swift - High-performance ML framework for Apple Silicon with lazy evaluation, automatic differentiation, and unified memory

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# MLX Swift Framework

MLX Swift is Apple's high-performance machine learning framework designed specifically for Apple Silicon. It provides NumPy-like array operations with lazy evaluation, automatic differentiation, and unified CPU/GPU memory.

## When to Use This Skill

- Array operations on Apple Silicon (MLXArray)
- Building neural networks (MLXNN)
- Training models with automatic differentiation
- Custom Metal kernels via MLXFast
- Performance optimization with JIT compilation

## Architecture Overview

```
MLXOptimizers (Adam, AdamW, SGD, etc.)
       ↓
MLXNN (Layers, Modules, Losses)
       ↓
MLX (Arrays, Ops, Transforms, FFT, Linalg, Random)
       ↓
Cmlx (C/C++ bindings, Metal GPU)
```

## Key File Reference

| Purpose | File Path |
|---------|-----------|
| Core array | Source/MLX/MLXArray.swift |
| Operations | Source/MLX/Ops.swift |
| Transforms | Source/MLX/Transforms.swift |
| Factory methods | Source/MLX/Factory.swift |
| Neural layers | Source/MLXNN/*.swift |
| Optimizers | Source/MLXOptimizers/Optimizers.swift |
| Fast ops | Source/MLX/MLXFast.swift |
| Custom kernels | Source/MLX/MLXFastKernel.swift |
| Wired memory coordinator | Source/MLX/WiredMemory.swift |
| GPU working-set helper | Source/MLX/GPU+Metal.swift |

## Quick Start

### Basic Array Creation

```swift
import MLX

// Create arrays
let a = MLXArray([1, 2, 3, 4])
let b = MLXArray(0 ..< 12, [3, 4])  // Shape [3, 4]
let c = MLXArray.zeros([2, 3])
let d = MLXArray.ones([4, 4], dtype: .float32)

// Random arrays (use MLXRandom namespace or free functions)
let uniform = MLXRandom.uniform(0.0 ..< 1.0, [3, 3])
let normal = MLXRandom.normal([100])
```

### Array Properties

```swift
let array = MLXArray(0 ..< 12, [3, 4])
array.shape    // [3, 4]
array.ndim     // 2
array.size     // 12
array.dtype    // .int64
array.count    // 3 (first dimension)
```

### Basic Operations

```swift
let a = MLXArray([1.0, 2.0, 3.0])
let b = MLXArray([4.0, 5.0, 6.0])

The rest: https://github.com/kellyvv/PhoneClaw/blob/HEAD/Packages/mlx-swift/skills/mlx-swift/SKILL.md