Diffusion model
A diffusion model is the type of AI that powers most modern image generators. It learns to turn random noise into a coherent image by reversing a step-by-step noising process.
Diffusion models are the engine behind today's leading image generators. The core idea is simple: during training, the model watches images get progressively corrupted with noise, and it learns to predict and remove that noise. To generate, you run the process in reverse - start from pure noise and let the model clean it up into a picture.
How it works
- Forward process: real images are gradually destroyed by adding noise until nothing recognizable remains.
- Reverse process: the trained model removes noise step by step, guided by your prompt, until a clean image emerges.
- Latent diffusion: most modern models run this in compressed latent space (via a VAE) so it is fast enough for everyday use.
Why it matters
Almost every control you touch maps onto this process: the sampler and steps govern how the noise is removed, the CFG scale governs how strongly your prompt steers it, and the seed sets the starting noise. Understanding diffusion makes every other setting click into place.
Try it in the generator
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Related terms
- Latent spaceLatent space is the compressed, abstract representation a diffusion model works in. Instead of manipulating millions of pixels, the model generates in this smaller space and then decodes it into an image.
- VAEA VAE (Variational Autoencoder) is the component that converts images between full-resolution pixels and the compressed latent space a diffusion model works in - encoding on the way in and decoding on the way out.
- DenoisingDenoising is the core operation of a diffusion model: at each step it predicts and removes a little noise, gradually turning a random field into a clear image.
- SamplerA sampler is the algorithm that decides how noise is removed at each step of generation. Different samplers reach the final image by different paths, trading off speed, detail and consistency.
- CheckpointA checkpoint is a saved AI model file containing the full set of trained weights. It is the complete "brain" that generates images - swapping checkpoints changes the entire look and capability.