Qwen Image Edit 2511

edit

fal-ai/qwen-image-edit-2511/lora

Qwen's 2511 image editor with LoRA loading.

Prompt-driven editing of one or more input images on Qwen Image Edit 2511, with up to three LoRAs merged in. The catalog has no matching Qwen edit trainer, so this endpoint consumes edit LoRAs trained elsewhere.

Open in fal playground ↗Official API docs ↗

Parameters

Schema facts from the fal API; the notes are ours.

Required

promptstringrequired

The text description of what to generate.

Tip: If your LoRA used a trigger word, include it. Describe the scene around the subject normally.

Raw schema description

The prompt to edit the image with.

image_urlslistrequired

Input images for editing. The edit LoRA decides how they are transformed.

Raw schema description

The URLs of the images to edit.

Optional

negative_promptstring

What the model should avoid generating.

Raw schema description

The negative prompt to generate an image from.

image_sizeobject

Output resolution, as a preset name or explicit width and height.

Raw schema description

The size of the generated image. If None, uses the input image dimensions.

num_inference_stepsintegerdefault: 281 – 50

Number of denoising steps per image. More steps, more refinement, more latency.

Tip: Defaults are tuned per model. Cutting steps in half is the quickest way to trade quality for speed.

Raw schema description

The number of inference steps to perform.

guidance_scalenumberdefault: 4.51 – 20

How strictly generation follows the prompt (classifier-free guidance).

In the atelier: How tightly you hold the painter to the brief. Too tight and the work gets stiff and oversaturated; too loose and he wanders.

Tip: Stay near the endpoint default. Adjust in steps of 0.5.

Raw schema description

The guidance scale to use for the image generation.

seedinteger

Random seed. Same seed plus same inputs gives a nearly identical image.

Tip: Fix the seed when comparing LoRA scales or parameters, so the only thing changing is the thing you are testing.

Raw schema description

The same seed and the same prompt given to the same version of the model will output the same image every time.

sync_modebooleandefault: false

Returns media as a data URI instead of a hosted URL, and skips storing it.

Tip: Useful for privacy; awkward for big files. Most workflows leave it off.

Raw schema description

If `True`, the media will be returned as a data URI.

num_imagesintegerdefault: 11 – 4

How many images to generate in one call.

Raw schema description

The number of images to generate.

enable_safety_checkerbooleandefault: true

Runs a safety filter on outputs.

Raw schema description

If set to true, the safety checker will be enabled.

output_formatenumdefault: pngjpeg | png | webp

File format of the result: jpeg, png or webp.

Raw schema description

The format of the generated image.

accelerationenumdefault: regularnone | regular | high

Speed and cost preset for the generation backend.

Tip: 'regular' balances quality and latency. Use higher acceleration for drafts and iteration.

Raw schema description

The acceleration level to use.

loraslistdefault: []

List of LoRA weights to load, each with a path (URL or HF repo) and a scale.

In the atelier: Which bracelets the painter wears for this painting, and how hard he leans on each.

Tip: Order does not matter; scales do. Start every LoRA at 1.0 and adjust one at a time.

Watch out: Stacking three strong LoRAs usually degrades all of them. Lower each scale when combining.

Raw schema description

The LoRAs to use for the image generation. You can use up to 3 LoRAs and they will be merged together to generate the final image.

Call it

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/qwen-image-edit-2511/lora", {
  input: {
    "prompt": "turn the sketch into a finished painting",
    "image_urls": [
      "https://your-cdn.com/input.jpg"
    ],
    "loras": [
      {
        "path": "https://your-cdn.com/lora.safetensors",
        "scale": 1
      }
    ]
  },
  logs: true,
});
console.log(result.data);