Models
Alibaba
Qwen Image Edit 2511

Alibaba

Qwen Image Edit 2511 AI Image Editing Model

Name: Qwen Image Edit 2511
Brand: Alibaba
Price: 0.03 USD
Availability: InStock

#3 Image-to-Image

Alibaba's Qwen image editing model for instruction-based image modifications and transformations

Example outputs coming soon

Try Model Benchmark examples

Input / Output

Text Image → Image

Active

Details

Model ID

qwen-image-edit-2511

Also known as: qwen-image-edit-plus-2511

Creator

Alibaba

Family

qwen

Ready to integrate?

Access qwen-image-edit-2511 via our unified API.

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Providers & Pricing (2)

Qwen Image Edit 2511 is available from 2 providers, with per-image pricing starting at $0.03 through Replicate.

Replicate

replicate/qwen-image-edit-2511

Provider Model ID: qwen/qwen-image-edit-2511

$0.030 /image

View pricing details

fal.ai

fal/qwen-image-edit-2511

Provider Model ID: fal-ai/qwen-image-edit-2511

$0.030 /megapixel

View pricing details

Provider Performance

Fastest generation through fal at 3,039ms median latency with 100.0% success rate.

Aggregated from real API requests over the last 30 days.

Generation Time

fal

p95: 5,485ms

replicate

p95: 17,217ms

Success Rate

fal

100.0%

564 / 564 requests

replicate

74.8%

1,156 / 1,545 requests

Time to First Byte

fal

3,041ms

p95: 5,529ms

replicate

3,603ms

p95: 16,266ms

Provider Rankings

#	Provider	p50 Gen Time	p95 Gen Time	Success Rate	TTFB (p50)
1	fal	3,039ms	5,485ms	100.0%	3,041ms
2	replicate	3,620ms	17,217ms	74.8%	3,603ms

Data updated every 15 minutes. Based on all API requests through Lumenfall over the last 30 days.

qwen-image-edit-plus-2511 API OpenAI-compatible

Integrate Qwen Image Edit 2511 through the Lumenfall API to perform instruction-based image editing and text-to-image generation using a single OpenAI-compatible endpoint. This interface allows developers to programmatically modify existing visual assets or create new high-fidelity images via standard HTTPS requests.

Base URL

https://api.lumenfall.ai/openai/v1

Model

qwen-image-edit-2511

Text to Image Generate

Create images from text descriptions

curl -X POST \

  https://api.lumenfall.ai/openai/v1/images/generations \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -H "Content-Type: application/json" \

  -d '{

    "model": "qwen-image-edit-2511",

    "prompt": "A serene mountain landscape at sunset",

    "size": "1024x1024"

}'

# Response:

# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

import OpenAI from 'openai';

const client = new OpenAI({

  apiKey: 'YOUR_API_KEY',

  baseURL: 'https://api.lumenfall.ai/openai/v1'

});

const response = await client.images.generate({

  model: 'qwen-image-edit-2511',

  prompt: 'A serene mountain landscape at sunset',

  size: '1024x1024'

});

// { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

console.log(response.data[0].url);

from openai import OpenAI

client = OpenAI(

    api_key="YOUR_API_KEY",

    base_url="https://api.lumenfall.ai/openai/v1"

response = client.images.generate(

    model="qwen-image-edit-2511",

    prompt="A serene mountain landscape at sunset",

    size="1024x1024"

# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

print(response.data[0].url)

Image Editing Edit

Transform existing images with text instructions

curl -X POST \

  https://api.lumenfall.ai/openai/v1/images/edits \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -F "model=qwen-image-edit-2511" \

  -F "[email protected]" \

  -F "prompt=Add a starry night sky to this image" \

  -F "size=1024x1024"

# Response:

# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

import OpenAI from 'openai';

import fs from 'fs';

const client = new OpenAI({

  apiKey: 'YOUR_API_KEY',

  baseURL: 'https://api.lumenfall.ai/openai/v1'

});

const response = await client.images.edit({

  model: 'qwen-image-edit-2511',

  image: fs.createReadStream('source.png'),

  prompt: 'Add a starry night sky to this image',

  size: '1024x1024'

});

// { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

console.log(response.data[0].url);

from openai import OpenAI

client = OpenAI(

    api_key="YOUR_API_KEY",

    base_url="https://api.lumenfall.ai/openai/v1"

response = client.images.edit(

    model="qwen-image-edit-2511",

    image=open("source.png", "rb"),

    prompt="Add a starry night sky to this image",

    size="1024x1024"

# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

print(response.data[0].url)

Full API Reference Authentication, endpoints, and more

Benchmarks

Qwen Image Edit 2511 currently holds the #2 rank in the Image Editing arena with an Elo rating of 1230. This position makes it one of the top-performing models globally for instruction-based image modifications and transformations.

Lumenfall Arena

Image Editing · 1229 Elo

Share Rank View Leaderboard →

Competition Results

Man and Car in California

Image Editing

Edit instruction

“Make a photo of the man driving the car down the California coastline”

Source

Result

Best for

All categories

Photorealism

Edit · of 16 · 56.3% wins

Gallery

View all 2 images

Qwen Image Edit 2511 FAQ

How much does Qwen Image Edit 2511 cost?

Qwen Image Edit 2511 starts at $0.03 per image through Lumenfall. Pricing varies by provider. Lumenfall does not add any markup to provider pricing.

How do I use Qwen Image Edit 2511 via API?

You can use Qwen Image Edit 2511 through Lumenfall's OpenAI-compatible API. Send requests to the unified endpoint with model ID "qwen-image-edit-2511". Code examples are available in Python, JavaScript, and cURL.

Which providers offer Qwen Image Edit 2511?

Qwen Image Edit 2511 is available through Replicate and fal.ai on Lumenfall. Lumenfall automatically routes requests to the best available provider.

Overview

Qwen Image Edit 2511 is a specialized vision-language model developed by Alibaba designed for instruction-based image modification. Unlike standard text-to-image models that generate images from scratch, this model takes an existing image and a natural language prompt as input to perform precise transformations. It is distinctive for its ability to follow complex editing instructions while maintaining the spatial consistency and identity of the original subject.

Strengths

Instruction Following: Translates nuanced natural language commands into specific visual changes, such as “make the sky a sunset” or “replace the coffee cup with a glass of orange juice.”
Subject Preservation: Maintains the high-level features and structural integrity of the base image, ensuring that modified elements blend realistically with the unchanged surroundings.
Style and Texture Transfer: Excels at altering the artistic style or material properties of an image while keeping the underlying geometry intact.
Localized Editing: Demonstrates the ability to target specific regions for modification without requiring the user to provide manual masks or pixel-perfect coordinates.

Limitations

Heavy Morphological Changes: While effective at replacement and style shifts, it may struggle with extreme structural changes that fundamentally alter the perspective or anatomy of the primary subject.
Text Rendering: Like many diffusion-based architectures, it may produce illegible or inconsistent text when asked to add specific typography to an image.
Prompt Sensitivity: Drastic changes in the prompt can occasionally lead to unintended global shifts in color or lighting that stray from the original image’s mood.

Technical Background

Qwen Image Edit 2511 belongs to the broader Qwen family of models, leveraging a multi-modal architecture that bridges visual encoders with a generative backbone. It is trained on large-scale datasets of paired images (before and after) and their corresponding textual descriptions to learn the relationship between linguistic instructions and visual deltas. This approach allows the model to treat image editing as a conditional generation task, focusing on the residuals between the source and target states.

Best For

This model is ideal for creative asset iteration, rapid prototyping of social media content, and product visualization where specific attributes must be toggled (e.g., changing background environments or colors). It is also well-suited for developers building photo editing tools that require a natural language interface.

Qwen Image Edit 2511 is available for integration and testing through Lumenfall’s unified API and playground, allowing you to benchmark its editing precision against other generative vision models in your workflow.