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qwen/qwen-edit-2509/lora/fusion

Qwen Edit 2509 Fusion blends one to three images into coherent compositions with strong identity retention and ControlNet guidance.

The URLs of the images to edit.
The size of the generated image.
The number of inference steps to perform.
Higher values produce images that more closely follow the prompt.
The number of images to generate.
The format of the generated image.

Introduction To Qwen Edit 2509 Fusion

Qwen Edit 2509 Fusion image-to-image is the latest advance, built upon their robust 20-billion-parameter Qwen-Image foundation model. Released around September 2025, this Qwen Edit 2509 edition refines core strengths in image-to-image editing with multi-image blending, precise object transformation, and multilingual text control. You gain deeper structure supervision via integrated ControlNet, allowing depth, edge, and keypoint guidance for detailed accuracy. It delivers superior fidelity in faces, typography, and product branding, empowering creators to preserve identity across every edit while exploring new visual styles. Accessible through Model Studio, Hugging Face, and API endpoints, it brings professional-grade control into your creative workflow. Qwen Edit 2509 image-to-image tool helps you seamlessly transform single or multiple images into polished, brand-consistent visuals. Designed for designers, marketers, and visual creators, it generates realistic edits and multilingual text compositions that keep your artistic flow intact while refining every pixel.

What makes Qwen Edit 2509 Fusion stand out

Qwen Edit 2509 is a structure-preserving, image-to-image editor built for reliable fusion and precise single-image edits. The Qwen Edit 2509 dual-input design combines Qwen2.5-VL for semantic intent with a VAE encoder for appearance fidelity, enabling edits that respect composition, pose, and material response. The model handles 1–3 input images for person + person, person + product, and person + scene scenarios while safeguarding facial identity, product details, and scene typography. With native ControlNet conditioning (depth, edges, keypoints, sketch), Qwen Edit 2509 delivers controllable, believable outcomes from subtle corrections to full scene recompositions. The qwen-image qwen-image-edit-2509-fusion pipeline supports guidance scale, negative prompts, and configurable steps for Qwen Edit 2509 and dependable iteration. Qwen Edit 2509 streamlines production workflows; Qwen Edit 2509 maintains brand consistency across complex merges; and Qwen Edit 2509 supports predictable, repeatable results for enterprise teams. Key capabilities:

  • Multi-image fusion (1–3 refs): person + person, person + product, person + scene.
  • Identity consistency: preserves faces, product shape/graphics, and in-scene text style.
  • ControlNet conditioning: depth, edge, keypoints, and sketch for structure control.
  • Dual-input architecture: semantic alignment + appearance faithfulness.
  • Targeted edits: maintain layout, pose, and proportions; minimize unwanted drift.
  • Configurable guidance: guidance scale, negative prompt, and inference steps.
  • Flexible output: selectable image sizes and formats for production workflows.

Prompting guide for Qwen Edit 2509 Fusion

Provide 1–3 high-quality images for Qwen Edit 2509 and a clear instruction describing what to change and what to preserve. For single-image edits, specify protected elements (subject, pose, text) and desired adjustments (background swap, cleanup, relighting). For fusion, define relationships between inputs (who is the primary subject, how products integrate, where elements should appear). Use QwenImageEditPlusPipeline from Qwen/Qwen-Image-Edit-2509; control behavior via guidance_scale, num_inference_steps, negative_prompt, and image_size. Include ControlNet conditions (depth, edges, keypoints, sketch) when structural adherence is critical. Qwen Edit 2509 and the qwen-image qwen-image-edit-2509-fusion configuration are optimized for concise, constraint-first prompts. Qwen Edit 2509 benefits from explicit constraints and clear role assignment across inputs, and Qwen Edit 2509 accelerates iteration while preserving control. Examples:

  • Single image: Preserve subject and pose; replace background with a modern office; keep brand logo unchanged.
  • Localized change: Remove power lines; do not alter the sky color or building edges.
  • Typography: Replace storefront sign with ACME in white sans-serif; match perspective and material.
  • Fusion (person + product): Place the red sneakers the model is holding on the floor, front-left; keep model’s face identity.
  • Fusion (person + scene): Insert subject into a sunlit cafe interior; match lighting and table height.
  • ControlNet pose: Keep the original pose from keypoints; change outfit to denim jacket; neutral studio background. Pro tips:
  • State constraints first: what to preserve, then what to change.
  • Use spatial terms: background only, left of subject, upper-right quadrant.
  • Provide clean, on-topic references; crop irrelevant regions.
  • Start with moderate guidance_scale and 20–30 steps; iterate in small increments.
  • Use negative_prompt to exclude artifacts (blurry text, extra fingers, warped logos).

Related Playgrounds

Frequently Asked Questions

What is Qwen Edit 2509 and what does it do?

Qwen Edit 2509 is a next-generation image editing (image-to-image) model developed by Alibaba’s Qwen research team. It enables users to transform, combine, and enhance images while preserving subject consistency and visual fidelity across complex edits.

What key features make Qwen Edit 2509 stand out?

Qwen Edit 2509 offers advanced image-to-image editing with support for up to three input images, ControlNet integration for depth and edge control, and powerful multilingual text editing. Its standout features include high structural fidelity, superior face retention, and natural multi-image blending.

How can I access or use Qwen Edit 2509?

You can access Qwen Edit 2509 through Runcomfy’s AI playground or platforms like Alibaba Model Studio, Hugging Face, or ModelScope. The image-to-image model is available via API or through web interfaces that support both desktop and mobile browsers.

Is Qwen Edit 2509 free to use?

Qwen Edit 2509 operates on a credit-based system in Runcomfy’s AI playground. New users receive trial credits at signup, but continued use requires purchasing or earning additional credits. This helps maintain high-quality cloud access for all image-to-image processing tasks.

Who should use Qwen Edit 2509?

Qwen Edit 2509 is designed for content creators, designers, digital marketers, photographers, and AI artists who leverage image-to-image editing for realistic transformations, product visuals, or multilingual text overlays within images.

What benefits does Qwen Edit 2509 offer over other image edit models?

Compared to other models, Qwen Edit 2509 delivers superior consistency, especially in faces and branded visuals. Its image-to-image architecture incorporates structural and semantic control, providing higher precision and creative flexibility than earlier model releases.

What file types or inputs does Qwen Edit 2509 support?

Qwen Edit 2509 supports standard image formats such as PNG and JPG for image-to-image input, with compatibility for depth maps, edge maps, and keypoint data to fine-tune structural outputs.

Does Qwen Edit 2509 have any limitations?

While powerful, Qwen Edit 2509 works best with high-resolution images and moderate transformation requests. Extreme image-to-image changes may require refined prompts for optimal control and realism, especially during style transfer edits.

Can Qwen Edit 2509 edit text inside images?

Yes, Qwen Edit 2509 excels at multilingual text editing inside images. The model’s image-to-image engine allows precise insertion, removal, and style customization of text in both English and Chinese with excellent layout consistency.