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Stable Diffusion is aLatent Diffusion Model (LDM)Deep learning text-to-image model. Unlike traditional models that operate in pixel space, it operates in low-dimensionalLatent SpaceThe denoising operation is performed in the process, which greatly reduces the demand for computer computing power. Its core components include variational autoencoders (VAE), U-Net denoising networks, and text encoders (such as CLIP).
| Version | Feature description |
|---|---|
| v1.5 | The most popular basic version, the open source ecosystem is the most mature, and it has many third-party fine-tuning models. |
| v2.1 | Improved image resolution support and enhanced control of Negative Prompts. |
| SDXL | Significantly increases the number of parameters, has stronger composition and realism capabilities, and supports native 1024x1024 resolution. |
| SD3 | Adopting a new architectural design, it significantly improves text rendering capabilities and compliance with complex instructions. |
Executing Stable Diffusion mainly depends on the graphics cardGraphics Processing Unit (GPU)andVideo RAM (VRAM). It is generally recommended to have an NVIDIA graphics card with at least 8GB of VRAM for better generation speed and stability. To execute locally, common operation interfaces includeAutomatic1111 (WebUI)、ComfyUIorForge。
Compared with closed source AI drawing tools, the advantage of Stable Diffusion is thatHighly customizableandFully localized execution. Users can train models and adjust underlying parameters by themselves, and the generated content is not subject to censorship restrictions on the cloud platform, making it the preferred tool for professional creators and technology developers.
This is a model based on SD 1.5 with extensive fine-tuning for multiple species. It corrects common joint errors and limb connection logic when generating quadrupeds with general models, and especially enhances the density of hair in mammals and the layering of bird feathers. It is the first choice for generating highly realistic creatures.
based onSDXLArchitecture development, with extremely high resolution and environment integration capabilities. This model is good at handling the interaction between wild animals and natural backgrounds (such as rainforests, deserts, and deep seas), and can generate images with the texture of ecological photography. Its advantage lies in the delicate processing of light and shadow reflection on skin or fur, avoiding an excessive artificial plastic feel.
Lightweight models designed for specific pets or rare creatures (e.g. corgis, ocelots, chameleons). This type of model is usually trained by the creator using dozens of photos of specific breeds. It can accurately restore the breed's unique pattern distribution, ear shape and pupil characteristics. It is often used in conjunction with realistic large models to improve accuracy.
Models specially designed for dragons, unicorns, griffins and other mythical creatures. This type of model combines the anatomical features of a variety of living animals and can generate fictional creatures with reasonable structure and artistic beauty. There are special optimizations in handling scales, bone protrusions and wing membrane texture.
This is currentlySDXLOne of the top realistic models in architecture. It excels at processing nature scenes and macro photography, accurately rendering the subtle textures of plants, such as the veins on leaves, the translucency of petals, and morning dew. Its advantage lies in its powerful light and shadow capture capabilities, which can generate forest or garden images with a strong sense of space.
For customary useSD 1.5For users, this is a classic realistic large model. It's perfect for generating photos of potted plants, houseplants, or home gardening. The image tone it generates is more realistic, without excessive artificial modification, and can perfectly simulate the texture of a single-lens camera.
This is not a single large model, but one specifically forPlant illustrationWeights for style training. Mounting it under the general model can produce images similar to the scientific drawing style of the 18th or 19th century. It emphasizes the biological structural characteristics of plants, often accompanied by a parchment background and a delicate line scan, and is suitable for art design or educational purposes.
This model focuses on the ultimate in natural color reproduction. It provides a very balanced green tone when spawning plants, avoiding the fluorescent green or oversaturation issues common with AI. This is a very stable choice for creating documentary-style images of outdoor landscapes, rainforests, or natural ecology.
