Local Diffusion

Run the latest diffusion models directly on your mobile device.

Local Diffusion is a Flutter application that brings Diffusion models to Android, powered by the amazing stable-diffusion.cpp

Download

Download and install the latest .apk from the GitHub Releases page:

✨ Key Features

• 📱 Truly Local Inference: Generate images entirely on your Android device.

• 🚀 Broad Model Compatibility:

  • Supports a wide range of architectures: SD1.x, SD2.x, SDXL, SD3/SD3.5, Flux/Flux-schnell, SD-Turbo, SDXL-Turbo, and more.

  • Load models directly from popular sources like Hugging Face and Civitai.

  • Works with common model formats: .safetensors and .ckpt.

• ⚡ On-the-Fly Quantization: Automatically quantize full-precision models during loading to save memory and potentially increase speed. Supported formats: q8_0, q6_k, q5_0, q5_1, q5_1k, q4_0, q4_1, q4_k, q3_k, q2_k.

• 🏎️ Performance Optimizations:

  • Flash Attention: Reduces memory usage during inference

  • TAESD: Significantly speeds up the image decoding process.

  • VAE Tiling: Reduces memory consumption during the VAE decoding stage, crucial for larger images on memory-constrained devices.

• 🎨 Advanced Generation Capabilities:

  • ControlNet: Guide image generation with precise control (includes Scribble-to-Image).

  • PhotoMaker: Generate custom portraits from reference images.

  • Img2Img: Generate images based on an initial input image.

  • Inpainting/Outpainting: Modify specific parts of an image or expand its canvas.

  • LoRA Support: Apply Low-Rank Adaptations to customize model outputs.

  • Negative Prompts: Specify what you don't want to see in the image.

  • Token Weighting: Emphasize or de-emphasize specific parts of your prompt.

  • Multiple Sampling Methods: Euler A, Euler, Heun, DPM2, DPM++ 2M, DPM++ 2M v2, DPM++ 2S a, LCM, TCD, DDIM

• 💻 GPU Acceleration (Experimental):

  • Vulkan: Currently performs ~2x slower than CPU. Performance improvements are planned.

  • OpenCL: Only supports Adreno 7xx GPUs for now. Optimized for Q4_0 quantization; also supports Q8_0 and FP16. Operations or devices outside these specifics may fall back to CPU execution.

📊 Memory Usage

Peak Memory Usage in MB

Benchmark settings: TAE + Flash Attention + VAE Tiling + only Clip_L Q8_0 for DiT/MMDiT architecture (Clip_G and T5_XXL were skipped)

Model	Resolution	Q2_K (MB)	Q4_0 (MB)	Q8_0 (MB)	fp16 (MB)
SD 1.5	256x256	1431	1461	1648	1997
	512x512	1870	1900	2087	2436
	768x768	4001	4031	4218	4567
SDXL	256x256	1868	2450	3889	6586
	512x512	2228	2810	4249	6946
	768x768	2228	2810	4249	6946
	1024x1024	2228	2810	4249	6946
SD 2.1	256x256	1510	1593	1892	2452
	512x512	1870	1953	2252	2812
	768x768	1870	1953	2252	2812
SD3.5 Medium	256x256	1790	2315	3433	5420
	512x512	2150	2675	3793	5780
	768x768	2289	2814	3932	5919
	1024x1024	3437	3962	5080	7067
SD3.5 Large	256x256	4630	5027	8848	-
	512x512	4990	5387	9208	-
	768x768	4990	5387	9208	-
	1024x1024	7271	7668	11489	-
FLUX.1	256x256	4168	6813	12456	-
	512x512	4528	7173	12816	-
	768x768	4551	7196	12839	-
	1024x1024	4889	7534	13177	-

🗺️ Roadmap

• iOS Support

• Performance Improvements

🛠️ Building

Ensure you have the Flutter SDK and Android development environment set up.

Run in Debug/Release Mode

flutter run

Release

flutter run --release

Build Release APK

  `flutter build apk --release`

The output APK will be located at build/app/outputs/flutter-apk/app-release.apk.

Credits

• Core Engine: stable-diffusion.cpp by leejet

• UI Components: shadcn/ui & flutter-shadcn-ui by nank1ro