What is the difference between image to image AI editing and text to image generation?

Text to image generation creates a visual from scratch — there is no source material, only a text prompt and a selected model. Image to image AI editing starts with an existing photograph and applies a described transformation to it. The model must balance two competing constraints: honoring what should change (background, style, lighting) while preserving what should not (face, product label, composition). Reference images add a third input layer — showing the model the target look rather than describing it.

How many reference images can each editing model accept?

GPT Image Edit accepts up to 16 reference images — the highest on this platform. Seedream 4.5 Edit, Seedream 5 Lite Edit, and Nano Banana 2 each accept up to 14 references. Flux 2 Pro Edit and Nano Banana Pro each accept up to 8. Reference count determines how much visual context the model has access to during the edit. Complex compositing tasks benefit from higher reference counts; simpler background swaps work equally well with fewer.

When should I attach reference images versus using text descriptions alone?

Text descriptions work reliably for transformations that are easy to name — 'change the background to a beach at sunset,' 'convert to black and white.' Attach reference images when the target look requires showing rather than telling: a specific painting style from an art print, a brand color palette from a design file, an environment lighting setup from a film still. Abstract visual targets — a particular 'mood,' a 'specific cinematic feel' — are substantially more accurate with references than without.

Which model produces the best results for artistic style transfer?

Seedream 4.5 Edit is specifically optimized for style transfer depth at 4K resolution. It accepts 14 reference images — enough to feed multiple exemplars of the target style — and maps them onto the source image at native 4096×4096 px without reducing subject fidelity. The key technical advantage is the native 4K rendering during the transformation pass, which preserves fine detail that typically degrades when style transfer runs at lower resolution and is subsequently upscaled.

How does Flux 2 Pro Edit's benchmark-leading win rate translate to practical editing quality?

Flux Pro Edit ranks among the top models on multi-image reference editing benchmarks — human evaluators consistently preferred its output over competing editors in head-to-head comparisons. For batch workflows — high-volume background swaps, product photography variants, seasonal re-colorings — benchmark-leading accuracy combined with sub-10-second generation speed delivers competitive quality at production throughput. For single high-stakes edits where 4K output or 14+ references matter, Seedream 4.5 Edit or GPT Image Edit is more appropriate.

Can I restore or enhance an old or damaged photograph with AI?

Yes. Nano Banana Pro handles this task well due to its identity-preservation architecture — it treats the original face structure and composition as a constraint and reconstructs damaged areas using surrounding contextual pixels rather than re-imagining the subject. Upload the damaged photograph as the source, describe the restoration target ('remove scratches, reconstruct missing areas, preserve tonal character'), and generate at 4K for maximum detail recovery. Seedream 4.5 Edit is an alternative if color or stylistic enhancement is also needed.

What types of edits does Seedream 5 Lite Edit handle better than other models?

Seedream 5 Lite Edit applies Chain-of-Thought visual reasoning — processing the spatial relationships in an edit request before generating. This makes it the most accurate model for edits involving spatial recomposition: adjusting a figure's body pose within the existing frame, repositioning multiple subjects relative to each other, or restructuring the depth-plane arrangement of overlapping elements. Standard editing models encode and decode in a single pass; Seedream 5 Lite builds an intermediate spatial plan, producing more accurate occlusion and proportional relationships in the output.

How does Nano Banana 2's Google Search grounding affect photo editing accuracy?

When Nano Banana 2 processes an edit involving a real-world subject — a specific product, a recognizable landmark, a branded environment — it queries Google Search to verify the subject's visual characteristics before applying the transformation. The practical effect: a product composite featuring a real-world package renders the label design accurately; an architecture edit referencing a specific building reflects its actual façade. Without search grounding, the model relies on training data that may be outdated or approximate for recently released products and updated brand identities.

What file formats and sizes can I upload for image editing?

Upload source images and reference images in JPG, PNG, or WebP format, up to 10 MB per file. For best editing results, upload the source at its maximum available resolution — the model uses input quality as a baseline for the transformation and generates output at the selected resolution tier. Edited images download watermark-free as PNG (for lossless, print-ready output) or JPEG (for web and social delivery).

How long does each image to image edit take to generate?

Flux 2 Pro Edit is the fastest — most edits at 1K resolution complete in under 10 seconds. Nano Banana 2 generates at Flash speed, typically 4–10 seconds. GPT Image Edit at medium quality takes 10–20 seconds. Nano Banana Pro at 2K takes 15–30 seconds. Seedream 4.5 Edit and Nano Banana Pro at 4K take 20–60 seconds. Seedream 5 Lite Edit adds reasoning time for complex spatial edits. Actual times vary with prompt complexity, resolution, and reference image count.

Can I preserve specific face or identity details through a major style transformation?

Yes. Nano Banana Pro is built specifically for this — its architecture treats facial geometry, hairstyle construction, and clothing details as hard constraints rather than soft preferences. For a major stylistic change like converting a portrait to a painted illustration, use Nano Banana Pro with the explicit preservation instruction: 'Keep the face structure, eye color, hair length, and facial expression identical; apply the style transformation only to rendering technique and background.' Seedream 4.5 Edit also preserves subject position well at 4K when identity anchors are clearly stated in the prompt.

What are the practical limitations of each image to image editing model?

GPT Image Edit maxes out at 1536 px — no 4K capability. Seedream 4.5 Edit does not support auto aspect ratio or 5:4. Seedream 5 Lite Edit caps at 3K with no 4K option; reasoning adds generation latency. Flux 2 Pro Edit caps at 2K across 7 aspect ratios. Nano Banana Pro's identity anchoring can occasionally over-preserve elements you intended to transform. Nano Banana 2 requires search latency for accuracy-critical prompts. All models process one edit per request — sequential editing passes are necessary for layered transformations.

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Image to Image AI — Reference-Guided Photo Transformation

Transforming an existing photo requires a different kind of AI than generating from scratch. You have a subject to preserve and a change to make — and the model has to understand both simultaneously. GPT Image Edit accepts up to 16 reference images per transformation, making it possible to feed a brand guide, a layout mockup, a color palette, and a product photo into one coherent edit. Seedream 4.5 Edit applies deep artistic style transfer at native 4K (up to 4096×4096 px) using 14 references — turning a product shot into a museum-quality illustration without touching the subject placement. Seedream 5 Lite Edit applies Chain-of-Thought spatial reasoning to edits requiring precise body repositioning or multi-element recomposition, with 14 references at 3K. Flux 2 Pro Edit holds a benchmark-leading performance on reference-guided editing and completes most transformations in seconds. Nano Banana 2 grounds edits in search-verified real-world accuracy with 14 references at 4K. Nano Banana Pro locks facial identity and outfit continuity through every transformation — critical when a character must remain recognizable across an entire production. Upload JPG, PNG, or WebP up to 10 MB and describe the change in plain language. Z-Video brings these editing engines into one workflow so you can choose the model that fits each transformation.

Multi-Model AI

Image to Image AI

4K Resolution

AI Style Transfer

Commercial License

Up to 16 References

AI Editing Engines — Reference Counts and Resolution Compared

The number of references you can attach, the resolution ceiling, and the editing approach each model uses — laid out before you upload a single file.

GPT Image Edit

OpenAI · 16 Reference Images Per Edit

Accepts more reference images per edit than any other model on this platform — up to 16 simultaneous inputs. Feed a brand style guide, a target layout, a product reference, a color palette, and environmental photography in a single request. The model synthesizes context from all 16 sources to produce an edit that respects every input simultaneously. Outputs at 1024 px (medium quality) or 1536 px (high quality) across 1:1, 2:3, and 3:2 aspect ratios.

16 references — highest on platformMulti-source context synthesis1024 px or 1536 px outputBest for complex multi-element compositing

Seedream 4.5 Edit

ByteDance · 4K Style Transfer — 14 References

Applies artistic style transfer at native 4K — up to 4096×4096 px — using up to 14 reference images. The model maps the visual language from style references onto your source photograph without displacing subject position or composition. Both 2K and 4K edit tiers use the same rendering pipeline. Supports 8 aspect ratios including 21:9 ultrawide. The direct choice when artistic transformation must be paired with maximum resolution output.

14 reference images per editNative 4K at 4096×4096 px8 aspect ratios including 21:92K and 4K at equal cost tier

Flux 2 Pro Edit

Black Forest Labs · Benchmark-Leading Editing Speed

Holds a benchmark-leading performance on reference-guided editing — the performance standard for accurate photo transformation at speed. Accepts up to 8 reference images and processes most edits in seconds across 1K or 2K output at 7 aspect ratios. Built for production pipelines where turnaround time matters: batch background swaps, product photography variations, and color palette iterations at volume.

Benchmark-leading editing accuracy8 reference images per editSeconds-per-edit generation speed1K and 2K resolution output

Nano Banana Pro

Google · Identity Preservation Across Edits

Google's identity-preservation editing model treats face geometry, hairstyle, clothing construction, and brand marks as hard constraints that persist through every transformation. Accepts up to 8 reference images for style and environment guidance. Outputs at 1K, 2K, or 4K across 11 aspect ratios including auto-detect. The right model whenever a person, character, or brand element must remain visually identical across an edit series.

Face and outfit anchoring8 references per edit1K / 2K / 4K resolution11 aspect ratios including auto

Nano Banana 2

Google · Search-Verified Editing at 4K

Google's search-grounded editing model verifies real-world subjects during transformation — ensuring that edits involving recognizable brands, products, or locations reflect verified real-world appearance rather than approximate model memory. Accepts 14 reference images for complex multi-element edits. Outputs at 4K across 15 aspect ratios at Flash generation speed. Ideal for editorial pre-visualization, product composite accuracy, and branded content that references real-world assets.

Google Search grounding during edit14 reference images per edit4K resolution at Flash speed15 aspect ratios — widest selection

Seedream 5 Lite Edit

ByteDance · Reasoning-Driven Spatial Edits

ByteDance's reasoning-driven editing model applies Chain-of-Thought visual logic to edits requiring spatial recomposition — adjusting body pose, repositioning multiple subjects within a frame, or restructuring choreographic arrangements. Processes 14 reference images to preserve identity while transforming spatial relationships. Outputs at 2K or 3K across 8 aspect ratios. Purpose-built for motion pre-visualization and complex scene restructuring tasks.

Chain-of-Thought spatial reasoning14 reference images per edit2K or 3K resolutionMulti-figure recomposition accuracy

Photo Editing Driven by Reference Images, Not Just Text

Text-only editing prompts describe what you want but cannot show it. Reference images close that gap. GPT Image Edit's 16-reference capacity means a single edit request can simultaneously process a style board, a brand guide, an environment photograph, and a layout comp — the model synthesizes all of them against your source photo. Seedream 4.5 Edit maps the visual language from 14 style references onto your subject at native 4K, producing transformations that reflect genuine artistic intent rather than a generic approximation. When speed is the priority, Flux 2 Pro Edit's benchmark-leading performance on reference editing means you get fast results without sacrificing consistency. For edits where subject identity must survive every transformation — portraits, mascots, recurring brand characters — Nano Banana Pro treats face and outfit as hard constraints, not suggestions.

Image to image AI example: photo transformation with style transfer using GPT Image 1.5, Seedream 4.5, Flux 2 Pro, and Nano Banana Pro

Image to Image Editing Workflows by Task Type

Six production scenarios mapped to the model that handles each one best — with the specific technical reason it wins that task.

Artistic Style Transfer

Recommended: Seedream 4.5 Edit — 14 references, native 4K

Upload your photograph alongside up to 14 style references — painted art prints, film color grades, illustrated book covers — and Seedream 4.5 Edit maps their visual language onto your subject without altering its composition. The transformation renders natively at 4K, preserving fine detail through the entire stylistic shift.

Vintage Photo Restoration and Enhancement

Recommended: Nano Banana Pro — identity-anchored detail recovery

Restore degraded photographs by preserving the original face structure, expression, and tonal character while removing scratches, grain, and compression artifacts. Nano Banana Pro reconstructs missing detail using surrounding context without reinterpreting the subject. Output at 1K, 2K, or 4K depending on the final use case.

Background Replacement and Environment Swap

Recommended: GPT Image Edit — 16 references for environment context

Describe the replacement environment in your prompt or attach reference images showing the target scene. GPT Image Edit uses spatial context from up to 16 references — including lighting photos, location shots, and atmosphere references — to place your foreground subject in the new environment with matched lighting direction and shadow placement.

Object Addition, Removal, and Substitution

Recommended: Flux 2 Pro Edit — benchmark-leading win rate, fastest

Add props, remove distractions, or swap objects between scenes. Flux 2 Pro Edit processes object edits in seconds at 1K or 2K, making it the practical choice for iterating through multiple prop placements or testing different product variants in the same scene. Accepts up to 8 reference images for guided object positioning.

Resolution Upscaling to 4K with Detail Regeneration

Recommended: Seedream 4.5 Edit or Nano Banana 2 — native 4K rendering

Re-render a lower-resolution source image at 4K during the edit pass — generating new fine detail during the diffusion process rather than interpolating from existing pixels. Seedream 4.5 Edit outputs natively at 4096×4096 px across 8 ratios. Nano Banana 2 reaches 4K across 15 ratios. Both produce detail that bilinear or AI upscalers cannot reconstruct.

Product Mockup and Brand Compositing

Recommended: GPT Image Edit — 16 references for brand element accuracy

Composite a product photo into a lifestyle scene while maintaining label legibility and brand mark accuracy. GPT Image Edit processes all 16 reference inputs simultaneously — product shot, brand guide, target environment, and layout template — generating variants where text remains correctly rendered and brand elements stay spatially consistent.

Image Editing Prompt Templates

Each template pairs a specific transformation type with the model built to handle it, plus the technical factors that make the match work.

Product Scene Composite with Brand Text

Best with GPT Image Edit — 16 references, text-accurate compositing

"Place this product bottle on a sunlit linen tablecloth. Morning light from upper-left window, clean shadow falling to the right of the product. Keep all label text and brand marks completely legible at 100% zoom. Add a small sprig of dried lavender to the left and a shallow ceramic bowl to the right. Lifestyle editorial style, warm 5600K daylight, 3:2 aspect ratio."

Portrait Artistic Style Transfer

Best with Seedream 4.5 Edit — 14 style references, native 4K output

"Transform this portrait photograph into a Flemish Golden Age oil painting style. Preserve the exact face structure, eye color, hair length, and gaze direction — do not alter the likeness. Apply visible impasto brushwork on clothing and background. Rembrandt-style split lighting from upper-right, dark umber and burnt sienna background tones, warm varnish color temperature. 4K output, 3:2 ratio."

Architecture Time-of-Day Transformation

Best with Flux Pro Edit — fastest editing turnaround

"Shift this building exterior from midday to blue-hour twilight. Add warm amber light visible through windows, wet pavement reflections on the forecourt, deep indigo sky transitioning to copper at the horizon. Preserve all architectural geometry, signage, and surface materials. Real estate editorial photography style, 16:9 ratio."

Damaged Photograph Restoration

Best with Nano Banana Pro — identity-preserved, 4K detail reconstruction

"Restore this vintage photograph: eliminate all visible scratches, fold creases, and water stains. Reconstruct damaged areas of the face and background using context from undamaged portions of the image. Preserve the warm sepia-to-neutral tonal character and the original depth-of-field. Enhance sharpness and local contrast. Do not colorize. 4K output."

How to Write Editing Prompts That Preserve What Matters

• State the transformation type first - Open with the edit category — 'Replace the background with...', 'Transfer the visual style to...', 'Remove the object and fill with...' Models trained on editing tasks respond more precisely to explicit instruction type than to descriptive prompts alone.
• List every element that must not change - Preservation anchors are as important as transformation instructions. Name what stays: 'Keep the subject's face, hair length, and jacket color unchanged.' Without explicit anchors, models may reinterpret elements you intended to preserve.
• Use references to show the target look - A 500-word prompt describing a painting style is weaker than one reference image from that style. GPT Image Edit supports 16 references — attach as many visual exemplars as clarify your intent. Seedream 4.5 Edit accepts 14; Flux 2 Pro Edit accepts 8.
• Match model to the primary constraint of the edit - Most references needed? GPT Image Edit (16). Highest output resolution? Seedream 4.5 Edit (native 4K). Fastest turnaround? Flux 2 Pro Edit (benchmark-leading accuracy, seconds per edit). Subject identity must survive? Nano Banana Pro. Real-world accuracy required? Nano Banana 2 with Google Search grounding.

How Reference-Guided Image Editing Works

Upload your source, attach your references, describe the transformation — the model handles the rest while keeping your anchors intact.

Upload Your Source Image and References

Upload the base photo you want to transform in JPG, PNG, or WebP format, up to 10 MB. Attach optional reference images — style boards, color palettes, brand guides — to guide the target look. More specific references produce more predictable edits.

Describe What Changes and What Stays

Write the transformation in natural language. Specify what should change (background, style, lighting, objects) and explicitly name what must remain (face, product label, composition). Select the model that matches your reference count and resolution needs.

Generate, Review, Iterate

Receive the edited image in 5–60 seconds depending on model and resolution. Output downloads watermark-free as PNG or JPEG. Run the same source image and prompt on a second model to compare how different engines interpret the same edit instruction.

Image to Image Transformation Results

Style transfers, background replacements, and identity-preserving edits generated from real user workflows.

Extend Your Editing Workflow

Generate the base image from scratch, animate the edited result into video, or build motion sequences from your transformed photos.

Text to Image AI Generator — Create from Scratch

Text to Video — Generate Motion from a Brief

Image to Video — Animate Your Edited Photos

Image to Image AI Editor — Technical FAQ

Reference image logistics, model selection guidance, resolution specs, and editing best practices answered with specific technical data.

Transform Photos with Reference-Level Precision

Attach up to 16 references with GPT Image Edit to synthesize brand guide, product photo, and layout comp in one request. Apply 4K artistic style transfer with Seedream 4.5 Edit using 14 references. Let Seedream 5 Lite Edit reason through spatial recompositions. Get search-verified edits with Nano Banana 2's Google grounding. Lock identity through every transformation with Nano Banana Pro. Move through quick iterations at benchmark-leading win rate with Flux 2 Pro Edit. Upload your photo — choose your model — download the result.

Image to Image AI — Reference-Guided Photo Transformation

Photo Editing Driven by Reference Images, Not Just Text

Transform Photos with Reference-Level Precision