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stabilityai/sd3.5-medium

At 2.5 billion parameters, with improved MMDiT-X architecture and training methods, this model is designed to run “out of the box” on consumer hardware, striking a balance between quality and ease of customization. It is capable of generating images ranging between 0.25 and 2 megapixel resolution.

At 2.5 billion parameters, with improved MMDiT-X architecture and training methods, this model is designed to run “out of the box” on consumer hardware, striking a balance between quality and ease of customization. It is capable of generating images ranging between 0.25 and 2 megapixel resolution.

Public
$0.03 / img
bf16
ProjectLicense

HTTP/cURL API

You can use cURL or any other http client to run inferences:

curl -X POST \
    -d '{"prompt": "A photo of an astronaut riding a horse on Mars.", "negative_prompt": ""}'  \
    -H "Authorization: bearer $DEEPINFRA_TOKEN"  \
    -H 'Content-Type: application/json'  \
    'https://api.deepinfra.com/v1/inference/stabilityai/sd3.5-medium'

which will give you back something similar to:

{
  "images": [
    "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAIAAACQd1PeAAAADElEQVQI12PQz3wAAAJDAXkkWn+MAAAAAElFTkSuQmCC"
  ],
  "nsfw_content_detected": [
    false
  ],
  "seed": 42,
  "request_id": null,
  "inference_status": {
    "status": "unknown",
    "runtime_ms": 0,
    "cost": 0.0,
    "tokens_generated": 0,
    "tokens_input": 0
  }
}

Input fields

promptstring

text prompt


negative_promptstring

negative text prompt


num_imagesinteger

number of images to generate

Default value: 1

Range: 1 ≤ num_images ≤ 4


num_inference_stepsinteger

number of denoising steps

Default value: 35

Range: 1 ≤ num_inference_steps ≤ 50


aspect_ratiostring

indirectly defines the width and height

Default value: "1:1"

Allowed values: 1:116:921:93:22:34:55:49:169:21


guidance_scalenumber

classifier-free guidance, higher means follow prompt more closely

Default value: 7

Range: 0 ≤ guidance_scale ≤ 20


seedinteger

random seed, empty means random

Range: 0 ≤ seed < 18446744073709552000


webhookfile

The webhook to call when inference is done, by default you will get the output in the response of your inference request

Input Schema

Output Schema