1
Choose Image to Image
Open the editor and select Image to Image so the workspace shows the reference uploader.
Image To Image AIReference-first AI image editing
Image to Image AI Generator
Edit, restyle, and reimagine existing visuals with a prompt
Start from up to eight reference images with the default model. Tell the AI what to change and what to preserve, then compare the output with your source before downloading.
How it works
Create an image edit in four steps
2
Upload references
Add JPG, PNG, or WebP images within the displayed file and model limits.
3
Write the edit instruction
Describe the requested change and explicitly state the details that should remain unchanged.
4
Generate and inspect
Review the result at full size, refine one variable, and download only after checking important details.
Why use Image To Image AI
One workspace for reference-based image edits
Prompt-based edits
Describe a background, material, lighting, outfit, object, or style change in plain language.
Multi-reference input
Attach multiple images when the active model supports them and explain the role of each reference in your prompt.
Model choice
Choose among enabled image models based on reference capacity, output controls, speed, and credit cost.
Controlled iteration
Keep the same source and adjust one instruction at a time to explore a direction without losing context.
Generation history
Return to previous results, review pending tasks, and compare variations in the same workspace.
Failure-aware credits
Credits are checked before submission, and the server follows its refund path when a provider submission fails.
HOW TO USE IMAGE TO IMAGE AI
A practical reference-editing workflow
A reference image gives the model visual context. A focused prompt tells it how to use that context without assuming every source detail will be preserved automatically.
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Select an image-to-image model
Choose a model that supports reference input. Review its reference limit, aspect ratios, quality options, and credit cost.
- 2
Upload a clean source
Use a sharp image with the important subject clearly visible. Add extra references only when they solve a specific visual need.
- 3
Separate change from preserve
Write the desired edit, then add a preservation instruction such as keep the face, pose, product shape, camera angle, and framing unchanged.
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Set output options
Choose only the settings supported by the active model. Auto aspect ratio is useful when you want to follow the source composition.
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Review and iterate
Compare source and result, inspect sensitive details, and make one targeted prompt change before generating again.
Prompt patterns that improve image edits
Use direct verbs
Replace, restyle, remove, add, relight, and recolor give the model a clearer task than vague requests to improve an image.
Repeat critical invariants
If identity or product geometry matters, repeat those preservation requirements on every refinement.
Match references to roles
Identify which reference provides the subject, style, background, or product when more than one image is attached.
Do a production review
AI outputs can alter text, hands, faces, logos, and fine geometry. Check them at actual size before publishing.
Image-to-image use cases
Useful when the source already carries visual value
Creators and social teams
Restyle photos, explore seasonal variations, and create alternate campaign directions from approved source material.
E-commerce teams
Place products into new visual contexts while checking shape, label, and color accuracy before use.
Designers and artists
Turn sketches, references, or early compositions into visual explorations for mood boards and concept reviews.
Character workflows
Use reference images to guide identity and styling, then inspect every result for consistency-sensitive details.
Image to Image AI FAQ
Capabilities, limits, and practical guidance
What does an image-to-image generator do?
It uses a source image as visual guidance and a text prompt as editing direction. The output is newly generated rather than a deterministic layer-by-layer edit.
Which model is selected by default?
The current workspace selects Flux 2 Pro Image to Image by default because its configured credit cost fits within the six signup credits and it supports up to eight references.
Which image formats can I upload?
The current uploader accepts JPG, PNG, and WebP files up to 10MB each. The active model can impose a separate reference-count limit.
Do I need an account?
Yes. Uploading and generation are protected actions because they use storage, credits, provider APIs, and a saved generation history.
How should I describe an edit?
Use a direct edit instruction followed by preservation rules. For example: replace the background with a warm studio set; keep the product shape, label placement, camera angle, and shadows consistent.
Can I combine multiple images?
Yes, when the active model supports multiple references. Explain how each image should be used instead of expecting the model to infer their roles.
Can the result match the source exactly?
No exact match is guaranteed. The source guides the generation, but fine details may change. Verify identity, products, logos, text, and geometry.
How many images are generated at once?
The form supports one to four outputs where the selected model and provider allow it. Credit cost updates with the chosen output count.
What happens if generation submission fails?
The server pre-debits credits, submits to the provider, and follows its refund path when submission fails. Later provider failures are handled by the task lifecycle.
Can I use the output for client or commercial work?
Check the selected model and platform terms, and confirm you hold the necessary rights to every reference image, person, brand, and asset.
Are uploaded images automatically private?
The editor requires authentication for uploads, but visibility and retention depend on the current storage, gallery, and account settings. Review those settings before using sensitive material.
How do I improve a weak result?
Keep the source fixed, simplify the prompt, strengthen the preservation rules, and change one visual variable at a time.