Text to Image
Generates images from text prompts with a context window of up to 50,000 tokens for detailed instruction input.
Qwen
Qwen Image Edit Plus
Qwen Image Edit Plus is an image generation and editing model developed by Qwen, released in early 2026. It supports text-to-image generation, image-to-image editing, and ControlNet pose conditioning, making it suited for workflows that require precise control over output composition. The model accepts image URL arrays, numeric parameters, and seed values as inputs, enabling reproducible results across generation runs. The model is designed for tasks that involve modifying existing images based on text prompts as well as generating new images from scratch. Its ControlNet pose support allows users to guide human figure layouts using reference poses, which is useful for character-focused creative work. With a context window of 50,000 tokens, it can process detailed prompt instructions alongside image inputs.
Unknown
50,000 context
N/A output
Text to Image
Image to Image
ControlNet Pose
Seed Control
Multi-Image Input
Model Overview
High-signal model metadata in a structured two-column overview table.
Provider
The entity that provides this model.
Qwen
Input Context Window
The number of tokens supported by the input context window.
50,000
tokens
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
N/A
tokens
Open Source
Whether the model's code is available for public use.
No
Release Date
When the model was first released.
Unknown
Knowledge Cut-off Date
When the model's knowledge was last updated.
Unknown
API Providers
The providers that offer this model. This is not an exhaustive list.
Hugging Face
Modalities
Types of data this model can process.
Image
Text
What is Qwen Image Edit Plus
A fuller summary of positioning, capabilities, and source-specific details for Qwen Image Edit Plus.
Qwen Image Edit Plus is an image generation and editing model developed by Qwen, released in early 2026. It supports text-to-image generation, image-to-image editing, and ControlNet pose conditioning, making it suited for workflows that require precise control over output composition. The model accepts image URL arrays, numeric parameters, and seed values as inputs, enabling reproducible results across generation runs.
The model is designed for tasks that involve modifying existing images based on text prompts as well as generating new images from scratch. Its ControlNet pose support allows users to guide human figure layouts using reference poses, which is useful for character-focused creative work. With a context window of 50,000 tokens, it can process detailed prompt instructions alongside image inputs.
Capabilities
What Qwen Image Edit Plus supports
Image to Image
Edits or transforms existing images based on text guidance, accepting image URL arrays as direct input.
ControlNet Pose
Supports pose-conditioned generation using ControlNet, allowing human figure layouts to be guided by a reference pose image.
Seed Control
Accepts a seed value as input to produce reproducible image outputs across multiple generation runs.
Multi-Image Input
Accepts arrays of image URLs as input, enabling multi-image editing workflows in a single request.
Pricing for Qwen Image Edit Plus
Primary API pricing shown in the same “quick compare” spirit as the reference page.
Input tokens
N/A
Per million tokens
Output tokens
N/A
Per million tokens
API Access & Providers
Places where this model is available, based on the synced detail-page metadata.
Hugging Face
Configuration & Parameters
The configurable options currently documented for this model.
Images
Image URL ArrayThe images to edit. A maximum of 3 reference images can be uploaded.
Width
NumberHeight
NumberSeed
SeedA specific value that is used to guide the 'randomness' of the generation. -1 means a random seed will be used.
Supported Request Parameters
Parameters currently listed by OpenRouter or the local catalog for this model.
Resources & Documentation
Official model cards, release notes, docs, and other references synced from the source page.
Community discussion
What people think about Qwen Image Edit Plus
Qwen Image Edit Plus discussions are most active in r/StableDiffusion, r/comfyui, r/SECourses. Top Reddit threads cluster around benchmark and model-comparison threads.
The strongest match in this snapshot has 440 upvotes and 55 comments.
🚀 Update Next Scene V2 only 10 days after last version, now live on Hugging Face
👉 [https://huggingface.co/lovis93/next-scene-qwen-image-lora-2509](https://huggingface.co/lovis93/next-scene-qwen-image-lora-2509)
🎬 A LoRA made for Qwen Image Edit 2509 that lets you create seamless cinematic “next shots” — keeping the same characters, lighting, and mood.
I trained this new version on thousands of paired cinematic shots to make scene transitions smoother, more emotional, and real.
🧠 What’s new:
• Much stronger consistency across shots
• Better lighting and character preservation
• Smoother transitions and framing logic
• No more black bar artifacts
Built for storytellers using ComfyUI or any diffusers pipeline.
Just use “Next Scene:” and describe what happens next , the model keeps everything coherent.
you can test on comfyui or to try on [fal.ai](http://fal.ai), you can go here :
[https://fal.ai/models/fal-ai/qwen-image-edit-plus-lora](https://fal.ai/models/fal-ai/qwen-image-edit-plus-lora)
and use my lora link :
[https://huggingface.co/lovis93/next-scene-qwen-image-lora-2509/blob/main/next-scene\_lora-v2-3000.safetensors](https://huggingface.co/lovis93/next-scene-qwen-image-lora-2509/blob/main/next-scene_lora-v2-3000.safetensors)
start your prompt with "Next Scene:" and lets go !!
**Hello!**
I made a *simple* Workflow; it's basically two Qwen Edit 2509 together. It generates one output from 3 images, and then uses it with 2 more images to generate another output.
In one of the examples above, it loads 3 different women's portraits and makes a single output with these, then it takes that output as image1 from the second generator, and places them in the living room with the dresses in image3.
Since I only have an 8 GB CPU I'm using an 8 Steps LoRA. The results are not outstanding, but they are nice, you can disable the LoRA, and give it more steps if you have a greater CPU.
Download the [workflow here on Civitai](https://civitai.com/models/1998998/qwen-image-edit-plus-2509-8steps-multiedit)
As titled. see more in [https://budgetpixel.com/subscription](https://budgetpixel.com/subscription)
Used Kohya Musubi tuner for training. Kohya implemented it after we requested.
try this: [https://civitai.com/models/1983350/ultimate-qwen-image-edit-plus-2509](https://civitai.com/models/1983350/ultimate-qwen-image-edit-plus-2509)
FAQ
Common questions about Qwen Image Edit Plus
What is the context window for Qwen Image Edit Plus?
Qwen Image Edit Plus has a context window of 50,000 tokens, which allows for detailed text prompts alongside image inputs.
What input types does Qwen Image Edit Plus accept?
The model accepts image URL arrays, numeric parameters (such as width and height), and a seed value for reproducible generation.
What tasks is Qwen Image Edit Plus designed for?
It supports text-to-image generation, image-to-image editing, and ControlNet pose-conditioned generation, making it suitable for both creative generation and structured image editing workflows.
When was Qwen Image Edit Plus trained?
According to the model metadata, the training data has a cutoff of February 2026.
Do I need an API key to use Qwen Image Edit Plus on MindStudio?
No API key is required to use Qwen Image Edit Plus on MindStudio; access is managed through the MindStudio platform directly.
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