macOS MLX Control Center v0.4 Released

MacOS MLX Control Center v0.4, a 1-click web GUI and CLI tool for running local multimodal vision and text LLMs on Apple Silicon M-Series processors, has been released. The update adds full native integration with mlx-vlm, enabling vision and multimodal image recognition for models like Gemma 4, Qwen 2.5/3.8 VL, PaliGemma, Pixtral, LLaVA, and SmolVLM, along with an interactive vision test chat. The tool bridges Apple's mlx-lm and mlx-vlm frameworks with a dark glassmorphic dashboard and terminal interface, and can be installed via a single curl command.

The simplest, fastest 1-click Web GUI & CLI Control Center to search, download, compare, benchmark, and run local Multimodal Vision & Text LLMs on Apple Silicon M-Series processors. Designed specifically for macOS, macOS MLX Control Center bridges Apple's high-performance mlx-lm text and mlx-vlm vision frameworks with a dark glassmorphic web dashboard and terminal interface. It turns any Mac powered by Apple Silicon M-Series processors into a local AI power-station with zero configuration hassle. Search Models https://private-user-images.githubusercontent.com/182375217/633836730-1a99830a-f565-41df-bc51-399e7f94e568.png?jwt=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3ODgwODU2MTIsIm5iZiI6MTc4ODA4NTMxMiwicGF0aCI6Ii8xODIzNzUyMTcvNjMzODM2NzMwLTFhOTk4MzBhLWY1NjUtNDFkZi1iYzUxLTM5OWU3Zjk0ZTU2OC5wbmc WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjYwODMwJTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI2MDgzMFQxMDIxNTJaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT01ZDFmNTJmODY0NWI4YjA3OGJkZmY3ZGEwMmI0MGYwYTJmNjY3NTE1ZTdmZDEzODkxMTAyNzY1ODY5NmE0YjhmJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZyZXNwb25zZS1jb250ZW50LXR5cGU9aW1hZ2UlMkZwbmcifQ.9m0 h-CKLPB56fDPcdxfkiayppVhxayHic2KIpF244U Compare Models https://private-user-images.githubusercontent.com/182375217/633837344-a98012ea-dfbb-4111-8892-3ed57d534f92.png?jwt=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3ODgwODU2MTIsIm5iZiI6MTc4ODA4NTMxMiwicGF0aCI6Ii8xODIzNzUyMTcvNjMzODM3MzQ0LWE5ODAxMmVhLWRmYmItNDExMS04ODkyLTNlZDU3ZDUzNGY5Mi5wbmc WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjYwODMwJTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI2MDgzMFQxMDIxNTJaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1jODMyYWQ0NTlhMDE3MjE3MmYzZDQ1M2FmYTBiOWE1NzliYWZlNzU4OGQxZjMzOGNjYzZjOWE4ZjUzNDRkYjMyJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZyZXNwb25zZS1jb250ZW50LXR5cGU9aW1hZ2UlMkZwbmcifQ.CUlc9niPhYsC9Uwm2vp3G64x1ALL2ef9rh-uFHHbP0g Customize API for Local Coders like OpenCode or Pi Code https://private-user-images.githubusercontent.com/182375217/633837660-129e06b4-a381-47b6-a50c-bda2788fde16.png?jwt=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3ODgwODU2MTIsIm5iZiI6MTc4ODA4NTMxMiwicGF0aCI6Ii8xODIzNzUyMTcvNjMzODM3NjYwLTEyOWUwNmI0LWEzODEtNDdiNi1hNTBjLWJkYTI3ODhmZGUxNi5wbmc WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjYwODMwJTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI2MDgzMFQxMDIxNTJaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT03NjVjNWUwMmVlYzRlZTc2NTQ1YTgzNWM2YmYzOThlYjQ0MzAyMDNmYmNjMzBkM2Q0ZjQzZmY3MGFmMzBmMTAzJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZyZXNwb25zZS1jb250ZW50LXR5cGU9aW1hZ2UlMkZwbmcifQ.bWLGV7SV77c4cvwNVES0bMrl4EtblbdMJLCzZwYO4PY Open Terminal and paste this single command: curl -sSL https://raw.githubusercontent.com/mypbs/mac-mlx-control-center/main/install.sh | bash - Download or clone this repository to your Mac. - Double-click in Finder. start.command - The server launches and automatically opens the dashboard in your default browser http://127.0.0.1:9998 Most local LLM runners are either overly complex, hog system menubars, or require manual hand-editing of configuration JSON files for coding tools. macOS MLX Control Center solves this with: - 👁️ Vision & Multimodal Image Recognition v0.4 : Full native integration with mlx-vlm Run Gemma 4, Qwen 2.5/3.8 VL, PaliGemma, Pixtral, LLaVA, SmolVLM, and more with full image analysis, OCR, visual question answering, and chart understanding. - 🖼️ Interactive Vision Test Chat v0.4 : Upload and preview images directly in the GUI test bench to test OpenAI-compatible multimodal payloads. - ⚙️ Dual-Engine Auto-Detection : Automatically detects model architectures and chooses the optimal inference engine without manual flags. mlx-vlm + mlx-lm v0.4 - 🔌 LibreChat & Coding Agent Multi-Modal Sync v0.4 : Direct compatibility with LibreChat host.docker.internal:9999/v1 , Pi Code, and OpenCode for image recognition and coding workflows. - 🧠 macOS Memory & Process Manager v0.3 : Real-time visual breakdown of Apple Silicon Unified Memory App, Wired, Compressed, Available Cache with an interactive top process scanner 🔍 Manage RAM and 1-click process termination to free up memory for larger models. - 🔤 Model Sorting & Date Added v0.3 : Sort local and downloaded models by Name A-Z / Z-A , Size Largest / Smallest , and Date Added Newest / Oldest with exact timestamps on all model cards. - 📱 Horizontal List Mode vs. Card Mode v0.3 : Toggle seamlessly between sleek horizontal list rows and spacious square card grid views across all model and search views. - 🟢 Activity Monitor-Aligned RAM Accounting v0.3 : Accurate unified memory metrics matching Activity Monitor, htop , and mactop . - 🚀 1-Click Model Launching & Hot Swapping : Instantly switch between MLX models without terminal commands. - 📦 Multi-Quant & Subfolder HF Support : Direct support for repositories with multiple quantizations e.g. orcarouter/Qwen3.8-27B-Uncensored-MLX/tree/main/4-bit . Pick exact bit precision 2-bit , 4-bit , 6-bit , 8-bit and download only the weights you need instead of 80+ GB - 🌐 Supercharged Hugging Face Search : Search thousands of model weights directly with instant filter chips ⚡ MLX Models , 👁️ Vision & Multimodal , 🎯 4-Bit Quantized , 💻 Code Models and sorting Most Downloads , Most Liked , Recently Updated . - 🤖 Built-In AI Model Comparison Engine : Select 2 to 4 models to generate an instant technical breakdown comparing quantization precision 2bit-DQ , OptiQ-4bit , RAM compatibility, and specialization — works 100% locally out-of-the-box with zero API keys or accounts required - 🟢 "Can I Run It?" Apple Silicon RAM Calculator : Live color-coded RAM budget badges 🟢 Fits Smoothly , 🟡 High RAM Pressure , 🔴 Swap Danger computed against your Mac's actual available memory. - 🤖 Auto-Sync Pi Code & OpenCode Agents : Automatically configures Pi Code https://github.com/ and OpenCode https://github.com/ under provider MyMac http://127.0.0.1:9999/v1 . Whenever you swap models in the GUI, your coding agents automatically route to the newly loaded model - 📊 Tokens/Second Speed Benchmark : Measure generation speed tok/s , execution time, token counts, and GPU memory usage on Apple Silicon. - ⚙️ Custom API Settings : Change default ports 9999 , 8888 , 8080 , host binding 127.0.0.1 or 0.0.0.0 for LAN access across home Wi-Fi , and max output token budgets with built-in memory guidelines. Running local AI on your Mac has never been easier. You only need: Any Mac with Apple Silicon M-Series Processors with Unified Memory . macOS 12.0 or newer . Python 3.10+ pre-installed on macOS or available via Homebrew/Xcode . Note:Dependencies like mlx-lm and hf CLI are automatically installed on-demand via uvx . You do not need to pre-install heavy ML environments Zero API keys or account sign-ups are required. Prefer working in the terminal? You can also use mlx.sh directly: ./mlx.sh ./mlx.sh list : View all downloaded local models and RAM sizes. ./mlx.sh search <query : Search Hugging Face repositories directly from terminal. ./mlx.sh start : Interactive launcher with Fast Swap and Concurrent port options. ./mlx.sh stop : Emergency kill-switch for running servers. In the ⚙️ API Settings panel, you can configure your Max Output Tokens : Max Output Tokens : Specifies the maximum number of generated response + reasoning tokens the server produces. It does not limit your input prompt size. RAM Guidelines for Apple Silicon : 2B – 8B Models Gemma 4 4B, Qwen 7B : Set to 4096 – 8192 Light KV Cache RAM impact ~0.5 GB . 14B – 35B Models Qwen 32B, DeepSeek 35B : Set to 4096 Moderate RAM impact ~1.5–3 GB . 70B+ Models : Set to 2048 – 4096 to prevent memory swapping. The combo of macOS MLX Control Center and LibreChat gives you a completely private, self-hosted ChatGPT-like experience with full multimodal vision support on your Mac. - 🔒 100% Local & Private : No data leaves your Mac; runs entirely on Apple Silicon GPU & Unified Memory. - 👁️ Full Multimodal Vision : Attach screenshots, PDFs, documents, diagrams, and photos in LibreChat for instant analysis with models like Gemma 4 and Qwen 2.5/3.8 VL. - ⚡ Hot-Swapping : Switch models in MLX Control Center with 1 click; LibreChat dynamically routes to the active model via default model without restarting containers. - 💰 Zero Cost : No OpenAI/Anthropic API subscriptions needed. Add the custom MLX endpoint to your librechat.yaml file: version: 1.2.0 endpoints: custom: - name: "MacBook MLX" apiKey: "local" baseURL: "http://host.docker.internal:9999/v1" Use http://127.0.0.1:9999/v1 if running LibreChat natively without Docker models: default: - "default model" - "mlx-community/gemma-4-e4b-it-OptiQ-4bit" - "lmstudio-community/Qwen3.8-27B-MLX-4bit" - "mlx-community/Llama-3.2-3B-Instruct-4bit" fetch: true titleConvo: true modelDisplayLabel: "MacBook MLX" Note for Docker users: host.docker.internal allows Docker containers on macOS to seamlessly communicate with the MLX server running directly on macOS. If running via Docker: docker compose restart - Open LibreChat e.g. http://localhost:3080 or http://localhost:3081 . - Select from the model dropdown. MacBook MLX - Drag & drop images directly into the chat to perform OCR, code transcription, and visual reasoning You can use an AI coding assistant like Google Antigravity , ChatGPT / Codex , Claude Code , or Cursor to completely automate managing, launching, and integrating this system on your Mac. Here are ready-to-use prompt templates you can copy and paste into your AI assistant: "I want to run local AI models on my Apple Silicon Mac using macOS MLX Control Center. Please run curl -sSL https://raw.githubusercontent.com/mypbs/mac-mlx-control-center/main/install.sh | bash to set up the repository, start the GUI dashboard on port 9998, and verify that the server is responding." "Please configure my local LibreChat setup to connect to my MLX Control Center. Update librechat.yaml with a custom endpoint named 'MacBook MLX' pointing to http://host.docker.internal:9999/v1 with fetch: true and models list containing default model and mlx-community/gemma-4-e4b-it-OptiQ-4bit . Then restart the LibreChat docker container and confirm health." "Please configure my local coding agent Pi Code / OpenCode to use my local MLX server as the default provider under the name 'MyMac' at http://127.0.0.1:9999/v1 with model ID default model and reasoning tokens enabled." "Check the status of my MLX server on port 9999 and GUI on port 9998 using curl http://127.0.0.1:9998/api/status . If I'm using a vision model like Gemma 4 , verify that it is running via mlx-vlm so image uploads work in LibreChat." When auto-sync is enabled in ⚙️ API Settings , launching any model automatically updates your local coding agent configs: Pi Code : ~/.pi/agent/settings.json & ~/.pi/agent/models.json OpenCode : ~/.config/opencode/opencode.jsonc Provider Name: MyMac Model ID: default model Auto-Detect Active MLX Endpoint Google Antigravity AI : Pair-programmed, engineered, and designed with Antigravity AI. Apple MLX Team : Powered by Apple's open-source mlx-lm & mlx-vlm frameworks. 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