mirror of
https://github.com/Comfy-Org/ComfyUI_frontend.git
synced 2026-04-20 14:30:41 +00:00
bbd0a6b201
Migrate workflow_templates/site into the frontend monorepo as apps/hub so the hub can use @comfyorg/design-system and shared packages. Changes to existing files: - pnpm-workspace.yaml: add @astrojs/sitemap, @astrojs/vercel, lucide-vue-next - eslint.config.ts: add hub ignores and i18n/import rule overrides - .oxlintrc.json: add hub scripts to ignore patterns - knip.config.ts: add hub workspace config apps/hub adaptations from source: - Replace local cn() with @comfyorg/tailwind-utils (19 files) - Integrate @comfyorg/design-system/css/base.css in global.css - Make TEMPLATES_DIR configurable via HUB_TEMPLATES_DIR env var - Add HUB_SKIP_SYNC flag for builds without template data - Remove Vite 8-incompatible rollupOptions.output.manualChunks - Fix stylelint violations (modern color notation, number precision) - Gitignore generated content (thumbnails, synced templates, AI cache)
2.9 KiB
2.9 KiB
Stable Diffusion
Stable Diffusion is Stability AI's family of open-source image and video generation models, spanning multiple architectures from U-Net to diffusion transformers.
Model Variants
SDXL (Stable Diffusion XL)
- Stability AI's flagship text-to-image model (6.6B parameter U-Net)
- Native 1024x1024 resolution with flexible aspect ratios around 1MP
- Two text encoders (CLIP ViT-L + OpenCLIP ViT-bigG)
- Optional refiner model for second-stage detail enhancement
- Turbo and Lightning distilled variants for 1-4 step generation
- Largest ecosystem of LoRAs, fine-tunes, and community models
SD3.5 (Stable Diffusion 3.5)
- Diffusion transformer (DiT) architecture, successor to SDXL
- Three text encoders (CLIP ViT-L, OpenCLIP ViT-bigG, T5-XXL) for stronger prompt following
- Available in Large (8B) and Medium (2B) parameter sizes
- Improved text rendering and compositional accuracy over SDXL
- 4 workflow templates available
SD1.5 (Stable Diffusion 1.5)
- The classic 512x512 latent diffusion model
- Single CLIP ViT-L text encoder, 860M parameter U-Net
- Still widely used for its massive LoRA and checkpoint ecosystem
- Lower VRAM requirements make it accessible on consumer hardware
- 2 workflow templates available
SVD (Stable Video Diffusion)
- Image-to-video generation model based on Stable Diffusion
- Generates short video clips (14 or 25 frames) from a single image
- Related model for motion generation from static inputs
Stability API Products
- Reimagine: Stability's API-based image variation and transformation service
Key Features
- Excellent composition, layout, and photorealism (SDXL/SD3.5)
- Large open-source ecosystem with thousands of community fine-tunes
- Flexible aspect ratios and multi-resolution support
- Dual/triple CLIP text encoding for nuanced prompt interpretation
- Strong text rendering in SD3.5 via T5-XXL encoder
Hardware Requirements
- SD1.5: 4-6GB VRAM (fp16), runs on most consumer GPUs
- SDXL Base: 8GB VRAM minimum (fp16), 12GB recommended
- SDXL Base + Refiner: 16GB+ VRAM
- SD3.5 Medium: 8-12GB VRAM
- SD3.5 Large: 16-24GB VRAM (fp16), quantized versions for 12GB cards
Common Use Cases
- Photorealistic image generation
- Artistic illustrations and concept art
- Product photography and design
- Character and portrait generation
- LoRA-based custom style and subject training
- Image-to-video with SVD
Key Parameters
- steps: 20-40 for SDXL base, 15-25 for refiner, 28+ for SD3.5
- cfg_scale: 5-10 (7 default for SDXL), 3.5-7 for SD3.5
- sampler: DPM++ 2M Karras and Euler are popular for SDXL; Euler for SD3.5
- resolution: 1024x1024 native for SDXL/SD3.5, 512x512 for SD1.5
- clip_skip: Often set to 1-2; important for SD1.5 LoRA compatibility
- denoise_strength: 0.7-0.8 when using the SDXL refiner (img2img)
- negative_prompt: Supported in SDXL/SD1.5; not used in SD3.5 by default