The stable-diffusion model has several potential use cases for a technical audience. One possible application is in the field of content generation, where it could be used to create realistic images for various purposes such as advertising, graphic design, or virtual environments. Another use case could be in the field of entertainment, where the model could be utilized to generate visuals for video games or animated movies based on textual descriptions. Additionally, the stable-diffusion model could have applications in the development of AI-assisted design tools, allowing users to easily transform text-based ideas into visual representations. Overall, this AI model holds promise for a wide range of products and practical uses, leveraging its ability to generate high-quality, photo-realistic images from textual input.
- Cost per run
- Avg run time
- Nvidia A100 (40GB) GPU
|Stablelm Tuned Alpha 7b||$0.0207||96,399|
|Stablelm Base Alpha 3b||$?||215|
|Stablelm Base Alpha 7b||$?||532|
|Stable Diffusion Inpainting||$0.0069||15,376,702|
|Stable Diffusion Img2img||$0.0138||855,600|
You can use this area to play around with demo applications that incorporate the Stable Diffusion model. These demos are maintained and hosted externally by third-party creators. If you see an error, message me on Twitter.
Currently, there are no demos available for this model.
Summary of this model and related resources.
|Model Name||Stable Diffusion|
A latent text-to-image diffusion model capable of generating photo-realisti...Read more »
|Model Link||View on Replicate|
|API Spec||View on Replicate|
|Github Link||View on Github|
|Paper Link||View on Arxiv|
How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?
How much does it cost to run this model? How long, on average, does it take to complete a run?
|Cost per Run||$0.0897|
|Prediction Hardware||Nvidia A100 (40GB) GPU|
|Average Completion Time||39 seconds|