usamaehsan/qwen-image-edit-2511-nunchaku

Qwen-Image-Edit-2511 Lightning, Nunchaku SVDQ INT4 (official nunchaku 1.2.1 + 2511 shim)

Public

24 runs

Run usamaehsan/qwen-image-edit-2511-nunchaku with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

Input schema

The fields you can use to run this model with an API. If you don't give a value for a field its default value will be used.

Field	Type	Default value	Description
prompt	string		Edit instruction
image	array		Reference image(s) as data: URIs
width	integer	Min: 256 Max: 1536	Output width, /16
height	integer	Min: 256 Max: 1536	Output height, /16
num_inference_steps	integer	0 Max: 12	0 = backend default (fp8: 4, nunchaku: 8)
ref_size	integer	1024 Min: 256 Max: 1536	Side of the square area the reference is resized to for the VAE (its tokens join the transformer sequence). Stock: 1024
cond_size	integer	384 Min: 128 Max: 768	Side of the area the reference is resized to for the text encoder's vision tower. Stock: 384
attention	None	native	None
seed	integer		None
output_format	None	jpg	None
output_quality	integer	90 Min: 1 Max: 100	None

{
  "type": "object",
  "title": "Input",
  "required": [
    "prompt",
    "image"
  ],
  "properties": {
    "seed": {
      "type": "integer",
      "title": "Seed",
      "x-order": 8
    },
    "image": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "title": "Image",
      "x-order": 1,
      "description": "Reference image(s) as data: URIs"
    },
    "width": {
      "type": "integer",
      "title": "Width",
      "maximum": 1536,
      "minimum": 256,
      "x-order": 2,
      "description": "Output width, /16"
    },
    "height": {
      "type": "integer",
      "title": "Height",
      "maximum": 1536,
      "minimum": 256,
      "x-order": 3,
      "description": "Output height, /16"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "x-order": 0,
      "description": "Edit instruction"
    },
    "ref_size": {
      "type": "integer",
      "title": "Ref Size",
      "default": 1024,
      "maximum": 1536,
      "minimum": 256,
      "x-order": 5,
      "description": "Side of the square area the reference is resized to for the VAE (its tokens join the transformer sequence). Stock: 1024"
    },
    "attention": {
      "enum": [
        "native",
        "sage"
      ],
      "type": "string",
      "title": "attention",
      "description": "An enumeration.",
      "default": "native",
      "x-order": 7
    },
    "cond_size": {
      "type": "integer",
      "title": "Cond Size",
      "default": 384,
      "maximum": 768,
      "minimum": 128,
      "x-order": 6,
      "description": "Side of the area the reference is resized to for the text encoder's vision tower. Stock: 384"
    },
    "output_format": {
      "enum": [
        "webp",
        "jpg",
        "png"
      ],
      "type": "string",
      "title": "output_format",
      "description": "An enumeration.",
      "default": "jpg",
      "x-order": 9
    },
    "output_quality": {
      "type": "integer",
      "title": "Output Quality",
      "default": 90,
      "maximum": 100,
      "minimum": 1,
      "x-order": 10
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 0,
      "maximum": 12,
      "minimum": 0,
      "x-order": 4,
      "description": "0 = backend default (fp8: 4, nunchaku: 8)"
    }
  }
}

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema

{
  "type": "string",
  "title": "Output",
  "format": "uri"
}