# Swift Mlx Lm

MLX Swift LM - Run LLMs and VLMs on Apple Silicon using MLX.

- Repository: https://github.com/kellyvv/PhoneClaw (1286 stars)
- Category: Mobile
- 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-lm -g -a claude-code -y`
Codex: `npx skills add kellyvv/PhoneClaw --skill swift-mlx-lm -g -a codex -y`
Cursor: `npx skills add kellyvv/PhoneClaw --skill swift-mlx-lm -g -a cursor -y`
Gemini CLI: `npx skills add kellyvv/PhoneClaw --skill swift-mlx-lm -g -a gemini-cli -y`

## Description

MLX Swift LM - Run LLMs and VLMs on Apple Silicon using MLX. Covers local inference, streaming, wired memory coordination, tool calling, LoRA fine-tuning, embeddings, and model porting.

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

# mlx-swift-lm Skill

## 1. Overview & Triggers

mlx-swift-lm is a Swift package for running Large Language Models (LLMs) and Vision-Language Models (VLMs) on Apple Silicon using MLX. It supports local inference, streaming generation, wired-memory coordination, tool calling, LoRA/DoRA fine-tuning, and embeddings.

### When to Use This Skill
- Running LLM/VLM inference on macOS/iOS with Apple Silicon
- Streaming text generation from local models
- Coordinating concurrent inference with wired-memory policies and tickets
- Tool calling / function calling with models
- LoRA adapter training and fine-tuning
- Text embeddings for RAG/semantic search
- Porting model architectures from Python MLX-LM to Swift

### Architecture Overview
```
MLXLMCommon     - Core infra (ModelContainer, ChatSession, Evaluate, KVCache, wired memory helpers)
MLXLLM          - Text-only LLM support (Llama, Qwen, Gemma, Phi, DeepSeek, etc.)
MLXVLM          - Vision-Language Models (Qwen-VL, PaliGemma, Gemma3, etc.)
MLXEmbedders    - Embedding models and pooling utilities
```

## 2. Key File Reference

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