Text-to-Image Generation
Converts natural language text prompts into visual images. Accepts descriptive input up to 77 tokens in length.
Stable Image Core is a text-to-image generation model developed by Stability AI, designed to convert natural language descriptions into detailed visual imagery. It accepts text prompts of up to 77 tokens and produces images across a range of styles and subjects. The model is available through both the Stability AI API and AWS Bedrock, giving developers flexibility in how they integrate it into their workflows. Stable Image Core is well suited for use cases such as creative content generation, marketing visuals, concept art, and rapid visual prototyping. Its availability on AWS Bedrock means it can be incorporated into cloud-based applications without managing underlying infrastructure. The model serves as an accessible entry point into Stability AI's image generation ecosystem, balancing output quality with ease of deployment.
High-signal model metadata in a structured two-column overview table.
The entity that provides this model.
The number of tokens supported by the input context window.
The number of tokens that can be generated by the model in a single request.
Whether the model's code is available for public use.
When the model was first released.
When the model's knowledge was last updated.
The providers that offer this model. This is not an exhaustive list.
Types of data this model can process.
A fuller summary of positioning, capabilities, and source-specific details for Stable Image Core.
Stable Image Core is a text-to-image generation model developed by Stability AI, designed to convert natural language descriptions into detailed visual imagery. It accepts text prompts of up to 77 tokens and produces images across a range of styles and subjects. The model is available through both the Stability AI API and AWS Bedrock, giving developers flexibility in how they integrate it into their workflows.
Stable Image Core is well suited for use cases such as creative content generation, marketing visuals, concept art, and rapid visual prototyping. Its availability on AWS Bedrock means it can be incorporated into cloud-based applications without managing underlying infrastructure. The model serves as an accessible entry point into Stability AI's image generation ecosystem, balancing output quality with ease of deployment.
Converts natural language text prompts into visual images. Accepts descriptive input up to 77 tokens in length.
Accepts free-form text descriptions as the primary input for image generation. Prompt length is capped at 77 tokens.
Supports selectable style options that influence the visual aesthetic of generated images. Configured via dropdown select inputs.
Accepts a numeric seed value to make image generation reproducible. Using the same seed and prompt produces consistent outputs.
Available through both the Stability AI API and AWS Bedrock for flexible deployment. AWS Bedrock integration removes the need to manage underlying model infrastructure.
Primary API pricing shown in the same “quick compare” spirit as the reference page.
Places where this model is available, based on the synced detail-page metadata.
The configurable options currently documented for this model.
Guides the image model towards a particular style.
A blurb of text describing what you do not wish to see in the output image.
A specific value that is used to guide the 'randomness' of the generation. Omit this parameter or pass 0 to use a random seed.
Parameters currently listed by OpenRouter or the local catalog for this model.
Official model cards, release notes, docs, and other references synced from the source page.
Stable Image Core discussions are most active in r/StableDiffusion, r/aiArt. The strongest match in this snapshot has 67 upvotes and 41 comments.
I'm not very good at posting news, but since nobody shared yet.
They are releasing 3 models, on amazon bedrock, no news about weights yet.
the models are: **Stable Image Ultra, Stable Diffusion 3 Large and Stable Image Core**
1. Stable Image Ultra: Photorealistic, Large-Scale Output
* Ideal For: Ultra-realistic imagery for luxury brands and high-end campaigns.
* Use Case Example: A luxury brand uses Stable Image Ultra to create stunning visuals of its latest collection for magazine spreads, ensuring a premium feel that matches its high standards.
1. Stable Diffusion 3 Large: High-Quality, High-Quantity Creative Assets
* Ideal For: High-volume outputs like marketing campaigns and digital assets.
* Use Case Example: A game development team uses SD3 Large to create detailed environmental textures and character concepts, accelerating their creative pipeline.
1. Stable Image Core: Fast and Affordable
* Ideal For: Rapid content generation at scale. Optimized for speedy image generation.
* Use Case Example: An online retailer uses Stable Image Core to quickly generate product images for new arrivals, allowing it to list items faster and keep its catalog up-to-date.
More on: [https://stability.ai/news/stability-ais-top-3-text-to-image-models-now-available-in-amazon-bedrock](https://stability.ai/news/stability-ais-top-3-text-to-image-models-now-available-in-amazon-bedrock)
Hope to see this model weights any time.
I'm enjoying Flux alot thease days, and I really don't know what to expect from this model, I'm a little frustrated with the latest news I've had about stability, but I still recognize them for being one of those who started the movement.
https://preview.redd.it/ovfb72x424nd1.png?width=1996&format=png&auto=webp&s=a1cb233095c550bda3dcbaf694d1a06f06cc234c
Bedrock Robot
Stable Image Core supports a context window of 77 tokens, which is the maximum length for a text prompt submitted to the model.
The model is available through the Stability AI API directly and through AWS Bedrock, allowing it to be used in cloud-based applications and workflows.
The metadata for this model does not specify a training cutoff date. As an image generation model, it does not retrieve or reason over factual knowledge in the way a language model does.
The model accepts text prompts, seed values for reproducibility, and multiple select inputs that control parameters such as output style and image configuration.
It is designed for use cases including creative content generation, marketing visuals, concept art, and rapid visual prototyping, as described in the official model overview.
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