Sold by: Stability AI
Deployed on AWS
The early beta for Stability AI’s foundation model for image generation, targeting medium resolution (512px) for fast image generation.
Overview
Stable Diffusion XL Beta 0.8 is the first public release of the evolution of the Stable Diffusion series of models. Calibrated for 512px native image generation at square aspect ratios, SDXL Beta 0.8 is capable of enhanced image composition targeting a variety of realistic and artistic stiles.
Highlights
- A new era in image generation: The largest image generation model to date and the first based on a new SDXL architecture, using 3.1B parameters to enable next-level photorealism and legible text even from simple prompts
- A preview of the new foundation model for images: SDXL Beta 0.8 is an intermediate step from the older, faster Stable Diffusion series, and the more powerful SDXL series. This version is useful for those who do not need the highest quality and flexibility, but still want to upgrade from SD 1.X or 2.X
Details
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Latest version
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost |
|---|---|---|
ml.g4dn.12xlarge Inference (Batch) Recommended | Model inference on the ml.g4dn.12xlarge instance type, batch mode | $0.00/host/hour |
ml.g5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.g5.xlarge instance type, real-time mode | $0.00/host/hour |
inference.count.m.i.c Inference Pricing | inference.count.m.i.c Inference Pricing | $0.00/request |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
This is the first release of SDXL Beta on AWS Marketplace.
Additional details
Inputs
- Summary
This model accepts JSON input aligned with the Stability REST API as well as protocol buffers aligned with the Stability GRPC API . You can also use the Stability SDK to deploy and interact with the model.
- Limitations for input type
- Input images must be base64 encoded in JSON or supplied via protobuf.
- Input MIME type
- application/json, application/x-protobuf
{
"cfg_scale": 7,
"height": 512,
"width": 512,
"steps": 50,
"seed": 42,
"text_prompts": [
{
"text": "A photograph of fresh pizza with basil and tomatoes, from a traditional oven",
"weight": 1
}]
}
https://platform.stability.ai
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
height | The height of the image in pixels. Must be in increments of 64 and one side must not exceed 512. | Default value: 512
Type: Integer
Minimum: 128
Maximum: 896 | No |
width | The width of the image in pixels. Must be in increments of 64 and one side must not exceed 512. | Default value: 512
Type: Integer
Minimum: 128
Maximum: 896 | No |
text_prompts | An array of text prompts to use for generation.
Given a text prompt with the text A lighthouse on a cliff and a weight of 0.5, it would be represented as:
"text_prompts": [
{
"text": "A lighthouse on a cliff",
"weight": 0.5
}
] | Type: FreeText
Limitations: Structured JSON array of prompts. | Yes |
cfg_scale | How strictly the diffusion process adheres to the prompt text (higher values keep your image closer to your prompt) | Default value: 7
Type: Integer
Minimum: 0
Maximum: 35 | No |
sampler | Which sampler to use for the diffusion process. If this value is omitted we'll automatically select an appropriate sampler for you. | Default value: auto
Type: Categorical
Allowed values: DDIM,DDPM,K_DPMPP_SDE,K_DPMPP_2M,K_DPMPP_2S_ANCESTRAL,K_DPM_2,K_DPM_2_ANCESTRAL,K_EULER,K_EULER_ANCESTRAL,K_HEUN,K_LMS | No |
seed | Random noise seed (omit this option or use 0 for a random seed) | Default value: 0
Type: Integer
Minimum: 0 | No |
style_preset | Pass in a style preset to guide the image model towards a particular style. This list of style presets is subject to change. | Default value: none
Type: Categorical
Allowed values: enhance,anime,photographic,digital-art,comic-book,fantasy-art,line-art,analog-film,neon-punk,isometric,low-poly,origami,modeling-compound,cinematic,3d-model,pixel-art,tile-texture | No |
steps | Number of diffusion steps to run. | Default value: 30
Type: Integer
Minimum: 10
Maximum: 150 | No |
Resources
Vendor resources
Support
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