metadata
license: cc-by-nc-4.0
tags:
- mobile-o
- multimodal
- unified-model
- ios
- coreml
- mlx
- on-device
- mobile
- edge-ai
pipeline_tag: image-text-to-text
Mobile-O-0.5B-iOS
Optimized MLX & CoreML Components for On-Device Deployment
📌 Overview
This repository contains the optimized MLX and CoreML model components of Mobile-O-0.5B for native iOS deployment. These components power the Mobile-O iOS app, enabling fully on-device multimodal understanding and image generation with no cloud dependency.
📱 On-Device Performance
| Spec | Detail |
|---|---|
| ⚡ Image Generation | ~3 seconds |
| 👁️ Visual Understanding | ~0.4 seconds |
| 💾 Memory Footprint | < 2GB |
| 📱 Compatible Devices | iPhone (A17+ / M-series) |
| 🔒 Cloud Dependency | None — fully on-device |
📦 Contents
This repo includes optimized model components in both MLX and CoreML formats:
| Component | Format | Description |
|---|---|---|
| VLM | MLX / CoreML | FastVLM-0.5B (FastViT + Qwen2-0.5B) |
| Diffusion Decoder | MLX / CoreML | SANA-600M-512 (Linear DiT + VAE) |
| MCP | MLX / CoreML | Mobile Conditioning Projector (~2.4M params) |
🚀 Usage
With the iOS App
- Clone the Mobile-O repo
- Navigate to the
Mobile-O-App/directory - Download this model repo into the app's model directory
- Build and run in Xcode
git clone https://github.com/Amshaker/Mobile-O.git
cd Mobile-O/Mobile-O-App
Refer to the Mobile-O-App README for detailed setup instructions.
Download Models
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="Amshaker/Mobile-O-0.5B-iOS",
repo_type="model",
local_dir="ios_models"
)
🔗 Related Resources
| Resource | Link |
|---|---|
| 🤗 Mobile-O-0.5B | PyTorch Model |
| 🤗 Mobile-O-1.5B | PyTorch Model |
| 📱 iOS App Source Code | Mobile-O-App |
| 🤗 Training Datasets | Collection |
📄 Citation
@article{shaker2026mobileo,
title={Mobile-O: Unified Multimodal Understanding and Generation on Mobile Device},
author={Shaker, Abdelrahman and Heakl, Ahmed and Muhammad, Jaseel and Thawkar, Ritesh and Thawakar, Omkar and Li, Senmao and Cholakkal, Hisham and Reid, Ian and Xing, Eric P. and Khan, Salman and Khan, Fahad Shahbaz},
journal={arXiv preprint arXiv:XXXX.XXXXX},
year={2026}
}
⚖️ License
Released under CC BY-NC 4.0. For research purposes only.