mlx-serve

What is mlx-serve?

mlx-serve vs Similar AI Tools

	mlx-serve	Wolbarg	LibArgus	Osaurus
Pricing Model	Free	Free	Free	Free
Free Credits
Key Features	Local inference on Apple Silicon with native Metal acceleration Speculative decoding (Prompt Lookup Decoding, drafter models, MTP) for up to 2x faster generation Image generation (Krea-2-Turbo, FLUX.2) and photo editing from text instructions	Local-first storage with no hosted vector SaaS required Semantic recall via natural language queries Multi-agent safe concurrent writes	Zero-allocation inference with Project Panama FFM API Unified runtime for LLM, ASR, TTS, and multimodal models Process-global backend to eliminate VRAM fragmentation	Local AI models run entirely on Mac Reads, writes, and executes on files Autonomous agents with voice control
Pros	Faster than LM Studio and Ollama on identical models Completely local and private – no data leaves your Mac	Local-first and privacy-focused Semantic search by meaning	Zero-allocation design for high performance in Java Unified API across multiple model types (text, vision, audio)	Full privacy – data never leaves device Works offline without internet
Cons	Mac-only (requires Apple Silicon) Some advanced features (e.g., DeepSeek V4) need high memory (96 GB+)	Requires an embedding API service (OpenAI-compatible) Limited to TypeScript/JavaScript environments	Requires Java 22+ and Project Panama (not yet standard in all JVMs) Build process may be complex for beginners due to native compilation	Requires Apple Silicon (M1 or later) Only supports macOS 15.5+
Best For	Mac users who want private, high-performance local AI Developers building AI agents and coding assistants	Developers building multi-agent AI systems Teams needing persistent, shared agent memory	Java developers building AI applications with low memory overhead Projects needing on-premise, high-throughput inference for LLMs and multimodal models	Privacy-conscious users Developers working with sensitive code

How to use mlx-serve?

1. 1Download the MLX Core app from GitHub Releases or install via Homebrew.
2. 2Launch the app and use the Model Browser to download any supported model.
3. 3Start chatting in the built-in interface or connect external apps via the OpenAI/Anthropic compatible API.
4. 4Use the ⌃Space launcher for quick access, or configure voice and Telegram bot for remote control.

mlx-serve Key Features

• Local inference on Apple Silicon with native Metal acceleration
• Speculative decoding (Prompt Lookup Decoding, drafter models, MTP) for up to 2x faster generation
• Image generation (Krea-2-Turbo, FLUX.2) and photo editing from text instructions
• Video generation (LTX-Video 2.3) with synced audio and talking characters
• Voice cloning and text-to-speech (Qwen3-TTS) from a few seconds of audio
• Agent mode with 10 built-in tools (shell, file, search, browse, etc.) and MCP server support
• Agent Sandbox using Apple Virtualization for isolated command execution
• Ollama-compatible API for drop-in replacement of Ollama apps
• Claude Code integration for local coding agents
• KV-cache quantization and continuous batching for multiple concurrent chats

mlx-serve Use Cases

• Running local LLMs for private AI assistance without internet
• Developing and testing AI agents with sandboxed tool execution
• Replacing cloud APIs for coding agents (Claude Code, Cursor, Continue)
• Generating images, video, and audio on-device for creative projects
• Building custom AI assistants with voice control and scheduling

mlx-serve Pricing & Free Credits

mlx-serve currently operates on a Free model.

mlx-serve Pros & Cons

What is mlx-serve best for?

• Mac users who want private, high-performance local AI
• Developers building AI agents and coding assistants
• Content creators needing offline image/video/audio generation
• Privacy-conscious individuals and organizations

mlx-serve FAQ