Styledrop or Mobile Diffusion? A Comprehensive Review

Generates branded images

Captures nuanced user styles

Uses less than 1% of parameters

Enhances image quality iteratively

Works with single style reference image

Outperforms expectations in style tuning

Appends natural language style descriptors

Generates consistently styled images

Can train with own brand assets

Combines well with DreamBooth

Offline working capability

Stable Diffusion v2.1 model

CoreML optimization

2x faster than competitors

Positive and negative prompts

Easy image sharing

Free to use

High privacy standards

No data collection

Acceptable performance on mobile

Requires style reference image

Less than 1% trainable parameters

Reliant on iterative training

Might need collaboration for training

Limited text-to-image style tuning

Inefficient for singe image rendering

Not diffusion-based

Need links to image assets

Large download size (4.5GB)

High battery use

Requires 5GB free storage

Crashes during high resource usage

May shutdown when multitasking

Generates heat leading to slowdown

Image generation may exceed 1 minute

Only supports select iPhone and iPad models

Requires iOS 16.2 or later

App becomes terminated when switched