A diffusion app starts with a description and makes media. That is a different shape from a classifier. A classifier answers what is already in a picture. A diffusion model makes a picture from a prompt, or in Wan's case a video.
Stable Diffusion family
The catalog lists sd-1.5, sd-2.1, and sd-3.5-medium. They are Stable Diffusion family presets for text-to-image work. If the feature is a prompt that should create an image, this is the first family group to look at.
FLUX.2 Klein
flux2-klein-4b is the catalog's FLUX.2 Klein preset. Its listed job is also text to image. Keep this clear: this is still the path for making a new image, even though the family name is different from Stable Diffusion.
Wan
wan-t2v-1.3b is the Wan text-to-video preset. Choose this when the output is moving frames, not one still image. The job changes from prompt-to-image into prompt-to-video.
The image-model lesson shows the broader shape difference. The ClothingCNN course shows a model that labels an existing image, not one that draws a new one. From the metal to the model follows the chosen generation recipe into the work the chip actually runs.
Next, look at those utility vision jobs, from labels to cut-outs and depth.
Key concepts
diffusionturns a prompt into new media, not a label for an existing image.- Still-image presets include
sd-1.5,sd-2.1,sd-3.5-medium, andflux2-klein-4b. wan-t2v-1.3bis the Wan text-to-video preset.- Classification describes what is already in a picture. Diffusion draws new pixels or frames.
Takeaways
- You can pick
diffusionwhen the app must create media from a prompt. - You can choose a still-image preset or
wan-t2v-1.3bfor moving frames. - You can say when utility vision fits better than diffusion for an existing photo.