Prompt-generated images include the Wan 3.0 site mark when removal is not available on your account.
View paid options for watermark controlYour first prompt result will appear here. Start with one clear visual direction, then compare later versions in My Creations.
A production-minded multimodal image model
Released on July 8, 2026, Seedream 5.0 Pro focuses on complex information layouts, precise regional editing, realistic materials, and multilingual visual design.
It suits posters, product imagery, localized campaigns, and video keyframes. Verify text, identity, product geometry, and asset rights before publishing.
Core capabilities
A concise look at the model’s strengths in information visualization, precise editing, realism, and multilingual generation.
Organizes charts, timelines, labels, and realistic scenes in one composition, helping dense visuals keep a clear hierarchy and reading order.
Uses point, box, lasso, and sketch controls to target edits. It also supports color and material changes, layer separation, and multi-image fusion without rebuilding the whole image.
Improves light, reflections, materials, and natural skin texture for product and portrait work. It also supports photographic effects such as panning.
Accepts and generates more than ten widely used languages while accounting for typography, reading direction, and layout balance in localized visuals.
A repeatable workflow
A strong result starts before generation. Define what will be published, assign a role to every reference, describe spatial relationships, and review against a fixed checklist. The model can interpret a complex request, but it cannot decide which brand details, legal statements, or facts your team is allowed to approve.
State the channel, audience, aspect ratio, reading distance, and purpose. A storefront banner, social carousel, product-detail panel, and motion keyframe need different framing and text density. Decide whether you are creating from text, editing one source, or combining several references.
List the subject, zones, object relationships, camera position, negative space, light, materials, exact copy, and protected elements. Then label each reference by role—identity, product geometry, palette, material, pose, layout, or background—and state which details must not migrate between subjects.
Review at full resolution for text, identity, anatomy, edges, reflections, shadows, object count, and layout. Save an approved checkpoint before the next edit. If several mistakes accumulate, return to the checkpoint rather than correcting a drifting chain of revisions.
Model comparison
A quick look at each model’s main strength and best-fit work.
| Compare | Seedream 5.0 Pro | GPT Image 2.5 | Nano Banana 2 |
|---|---|---|---|
| Core strength | Dense layouts, precise regional edits, layered production, realistic materials, and multilingual design. | Reference fidelity, detailed output, and multi-turn refinement with speed- or precision-focused variants. | Fast creation and editing with broad knowledge and search-connected workflows. |
| Editing | Point, box, lasso, sketch, color, material, layer separation, and multi-image fusion. | Prompt, selection, and reference-image edits that aim to preserve the surrounding composition. | Targeted edits, multi-image blending, repeated refinement, and subject consistency. |
| Text work | Information-rich graphics and multilingual visual composition. | Complex layouts, text rendering, and localized creative assets. | Text, translation, notes-to-diagram work, and data visuals. |
| Best for | Infographics, localized design, regional edits, layered concepts, and realistic campaign frames. | Reference-led refinement, brand variations, and controlled multi-turn editing. | Rapid ideation, knowledge-heavy visuals, search-connected subjects, and high-resolution output. |
Features and output options vary by product. Check the live interface before production.
Model library
Use the model pages and working image routes to compare how different systems handle a production brief. The links distinguish research pages from generators so the model name shown in a card never overstates what the destination can run.
Model guide
Current Wan 3.0 workflow
External model overview
Connected creation paths
Move from a model decision to the task you actually need to complete: create a new still, revise an approved reference, or prepare an image as the first frame of a video workflow.
Create from a brief
Revise a source
Carry the frame into motion
Practical answers
Short answers about model identity, input modes, editing, language support, output settings, quality review, and what is actually available on Wan 3.0 today.
Seedream 5.0 Pro is a multimodal image creation model released on July 8, 2026. Published documentation describes improvements in image-text alignment, structural coherence, text rendering, and visual aesthetics, with four main advances: complex information visualization, interactive precision editing, realistic imagery and portrait texture, and native multilingual input and generation. It is an image model, not a video model; a finished still can become a source for a separate image-to-video workflow.
Not currently. The embedded Wan 3.0 workspace is a real, usable image generator, but its selector currently lists the registered GPT Image 2 workflow. This page does not rename that model or claim the request is sent to Seedream. A direct Seedream 5.0 Pro launch on Wan 3.0 would require separate provider integration, exact request mapping, credit pricing, task polling, result parsing, safety handling, and production testing.
A currently documented integration includes text prompt to one image, one reference image plus a prompt, and multiple reference images plus a prompt. The multi-reference form lists JPEG, PNG, and WEBP inputs, a 30 MB maximum file size, and up to ten files. Layer decomposition is a separate mode with its own input and size options. Verify the live interface before building because available modes and limits can change.
Published model documentation describes spatially grounded editing through point, box, lasso, sketch, color, and material controls. It also shows layer separation into transparent, independently movable assets and multi-image fusion. These are model and supported-surface capabilities; a third-party API or this site may expose only part of them. Even when layer export is available, check masks, edges, inpainted areas, transparency, overlaps, and whether hidden background regions were reconstructed correctly.
High-density information visualization is one of its headline strengths, and official examples show multiple charts, labels, diagrams, and realistic elements coordinated in one frame. That makes the model useful for exploring hierarchy and layout. It does not make the generated image a verified data source. Compare every number, spelling, unit, relationship, date, and label with the approved source. Rebuild legal, safety, pricing, and accessibility-critical text in editable layers before publishing.
Published documentation describes native input and high-quality generation in more than ten commonly used languages. It names Chinese, English, French, German, Russian, Japanese, Korean, Spanish, and Arabic, and discusses language-aware typography such as accents and right-to-left Arabic. This is useful for localized concepts, but a fluent reviewer still needs to check meaning, grammar, line breaks, cultural detail, reading order, and every visible character.
A currently documented integration lists 1:1, 4:3, 3:4, 16:9, 9:16, 2:3, 3:2, and 21:9 aspect ratios, Basic quality for 1K, High quality for 2K, and PNG or JPEG output. Each generation request returns one image and is not described as streaming or sequential generation. Those controls are implementation-specific rather than universal guarantees for every Seedream product surface, and they are different from the controls in the Wan 3.0 workspace above.
Inspect the full-resolution image against authorized references. For a person, check identity, age cues, expression, gaze, hair, ears, hands, clothing construction, accessories, skin texture, and whether the lighting agrees across the face and body. For a product, check silhouette, proportions, seams, material response, label area, reflections, transparency, contact shadow, scale, and object count. Do not let convincing lighting hide an invented feature or a changed product shape.
The technical ability to create an image is separate from the right to publish it. Check the terms of the provider account you actually use, obtain permission for every input, avoid unauthorized people and trademarks, and keep a record of sources, prompts, settings, outputs, edits, and approvals. Rebuild critical copy, test the final crop on each breakpoint, preserve any required provenance metadata, and label concept art honestly when it is not a verified model sample.
Published model documentation notes that finer-grained text rendering and pixel-level editing consistency still have room to improve. Complex scenes can also fail in ordinary ways: incorrect labels, duplicated objects, subtle identity drift, impossible material behavior, weak layer edges, or changes outside the requested region. Begin with a controlled brief, save accepted checkpoints, change one variable at a time, and plan for manual design, fact, rights, and accessibility review.
From model output to published brand asset
The model is most useful when it sits inside an accountable production chain. A generation can establish the master art direction, but publication depends on approved sources, accurate copy, repeatable variants, responsive crops, and a clear distinction between the image model and the product that hosts it.
Open the current image workspaceDefine the campaign idea, audience, palette, product geometry, protected marks, typography rules, channel ratios, and prohibited changes. Attach only authorized identity, product, material, layout, and location references, and label the role of each file.
Use the model’s layout, realism, multilingual, and regional-editing strengths to reach a stable master. Then validate facts, names, product details, identity, edges, contrast, and crop safety. Re-typeset critical copy in normal design files instead of treating generated pixels as final artwork.
Create deliberate desktop, mobile, social, email, and presentation crops rather than relying on automatic trimming. Keep the approved checkpoint and change one ratio or content zone at a time so the visual system remains recognizable across placements.
A polished Seedream frame can anchor an image-to-video test on Wan 3.0. Describe motion, camera behavior, duration, and protected details separately; image quality alone does not define a stable video. Review the moving product, faces, text zones, occlusion, and end frame before release.
Prompt-generated images include the Wan 3.0 site mark when removal is not available on your account.
View paid options for watermark controlYour first prompt result will appear here. Start with one clear visual direction, then compare later versions in My Creations.
A production-minded multimodal image model
Released on July 8, 2026, Seedream 5.0 Pro focuses on complex information layouts, precise regional editing, realistic materials, and multilingual visual design.
It suits posters, product imagery, localized campaigns, and video keyframes. Verify text, identity, product geometry, and asset rights before publishing.
Core capabilities
A concise look at the model’s strengths in information visualization, precise editing, realism, and multilingual generation.
Organizes charts, timelines, labels, and realistic scenes in one composition, helping dense visuals keep a clear hierarchy and reading order.
Uses point, box, lasso, and sketch controls to target edits. It also supports color and material changes, layer separation, and multi-image fusion without rebuilding the whole image.
Improves light, reflections, materials, and natural skin texture for product and portrait work. It also supports photographic effects such as panning.
Accepts and generates more than ten widely used languages while accounting for typography, reading direction, and layout balance in localized visuals.
A repeatable workflow
A strong result starts before generation. Define what will be published, assign a role to every reference, describe spatial relationships, and review against a fixed checklist. The model can interpret a complex request, but it cannot decide which brand details, legal statements, or facts your team is allowed to approve.
State the channel, audience, aspect ratio, reading distance, and purpose. A storefront banner, social carousel, product-detail panel, and motion keyframe need different framing and text density. Decide whether you are creating from text, editing one source, or combining several references.
List the subject, zones, object relationships, camera position, negative space, light, materials, exact copy, and protected elements. Then label each reference by role—identity, product geometry, palette, material, pose, layout, or background—and state which details must not migrate between subjects.
Review at full resolution for text, identity, anatomy, edges, reflections, shadows, object count, and layout. Save an approved checkpoint before the next edit. If several mistakes accumulate, return to the checkpoint rather than correcting a drifting chain of revisions.
Model comparison
A quick look at each model’s main strength and best-fit work.
| Compare | Seedream 5.0 Pro | GPT Image 2.5 | Nano Banana 2 |
|---|---|---|---|
| Core strength | Dense layouts, precise regional edits, layered production, realistic materials, and multilingual design. | Reference fidelity, detailed output, and multi-turn refinement with speed- or precision-focused variants. | Fast creation and editing with broad knowledge and search-connected workflows. |
| Editing | Point, box, lasso, sketch, color, material, layer separation, and multi-image fusion. | Prompt, selection, and reference-image edits that aim to preserve the surrounding composition. | Targeted edits, multi-image blending, repeated refinement, and subject consistency. |
| Text work | Information-rich graphics and multilingual visual composition. | Complex layouts, text rendering, and localized creative assets. | Text, translation, notes-to-diagram work, and data visuals. |
| Best for | Infographics, localized design, regional edits, layered concepts, and realistic campaign frames. | Reference-led refinement, brand variations, and controlled multi-turn editing. | Rapid ideation, knowledge-heavy visuals, search-connected subjects, and high-resolution output. |
Features and output options vary by product. Check the live interface before production.
Model library
Use the model pages and working image routes to compare how different systems handle a production brief. The links distinguish research pages from generators so the model name shown in a card never overstates what the destination can run.
Model guide
Current Wan 3.0 workflow
External model overview
Connected creation paths
Move from a model decision to the task you actually need to complete: create a new still, revise an approved reference, or prepare an image as the first frame of a video workflow.
Create from a brief
Revise a source
Carry the frame into motion
Practical answers
Short answers about model identity, input modes, editing, language support, output settings, quality review, and what is actually available on Wan 3.0 today.
Seedream 5.0 Pro is a multimodal image creation model released on July 8, 2026. Published documentation describes improvements in image-text alignment, structural coherence, text rendering, and visual aesthetics, with four main advances: complex information visualization, interactive precision editing, realistic imagery and portrait texture, and native multilingual input and generation. It is an image model, not a video model; a finished still can become a source for a separate image-to-video workflow.
Not currently. The embedded Wan 3.0 workspace is a real, usable image generator, but its selector currently lists the registered GPT Image 2 workflow. This page does not rename that model or claim the request is sent to Seedream. A direct Seedream 5.0 Pro launch on Wan 3.0 would require separate provider integration, exact request mapping, credit pricing, task polling, result parsing, safety handling, and production testing.
A currently documented integration includes text prompt to one image, one reference image plus a prompt, and multiple reference images plus a prompt. The multi-reference form lists JPEG, PNG, and WEBP inputs, a 30 MB maximum file size, and up to ten files. Layer decomposition is a separate mode with its own input and size options. Verify the live interface before building because available modes and limits can change.
Published model documentation describes spatially grounded editing through point, box, lasso, sketch, color, and material controls. It also shows layer separation into transparent, independently movable assets and multi-image fusion. These are model and supported-surface capabilities; a third-party API or this site may expose only part of them. Even when layer export is available, check masks, edges, inpainted areas, transparency, overlaps, and whether hidden background regions were reconstructed correctly.
High-density information visualization is one of its headline strengths, and official examples show multiple charts, labels, diagrams, and realistic elements coordinated in one frame. That makes the model useful for exploring hierarchy and layout. It does not make the generated image a verified data source. Compare every number, spelling, unit, relationship, date, and label with the approved source. Rebuild legal, safety, pricing, and accessibility-critical text in editable layers before publishing.
Published documentation describes native input and high-quality generation in more than ten commonly used languages. It names Chinese, English, French, German, Russian, Japanese, Korean, Spanish, and Arabic, and discusses language-aware typography such as accents and right-to-left Arabic. This is useful for localized concepts, but a fluent reviewer still needs to check meaning, grammar, line breaks, cultural detail, reading order, and every visible character.
A currently documented integration lists 1:1, 4:3, 3:4, 16:9, 9:16, 2:3, 3:2, and 21:9 aspect ratios, Basic quality for 1K, High quality for 2K, and PNG or JPEG output. Each generation request returns one image and is not described as streaming or sequential generation. Those controls are implementation-specific rather than universal guarantees for every Seedream product surface, and they are different from the controls in the Wan 3.0 workspace above.
Inspect the full-resolution image against authorized references. For a person, check identity, age cues, expression, gaze, hair, ears, hands, clothing construction, accessories, skin texture, and whether the lighting agrees across the face and body. For a product, check silhouette, proportions, seams, material response, label area, reflections, transparency, contact shadow, scale, and object count. Do not let convincing lighting hide an invented feature or a changed product shape.
The technical ability to create an image is separate from the right to publish it. Check the terms of the provider account you actually use, obtain permission for every input, avoid unauthorized people and trademarks, and keep a record of sources, prompts, settings, outputs, edits, and approvals. Rebuild critical copy, test the final crop on each breakpoint, preserve any required provenance metadata, and label concept art honestly when it is not a verified model sample.
Published model documentation notes that finer-grained text rendering and pixel-level editing consistency still have room to improve. Complex scenes can also fail in ordinary ways: incorrect labels, duplicated objects, subtle identity drift, impossible material behavior, weak layer edges, or changes outside the requested region. Begin with a controlled brief, save accepted checkpoints, change one variable at a time, and plan for manual design, fact, rights, and accessibility review.
From model output to published brand asset
The model is most useful when it sits inside an accountable production chain. A generation can establish the master art direction, but publication depends on approved sources, accurate copy, repeatable variants, responsive crops, and a clear distinction between the image model and the product that hosts it.
Open the current image workspaceDefine the campaign idea, audience, palette, product geometry, protected marks, typography rules, channel ratios, and prohibited changes. Attach only authorized identity, product, material, layout, and location references, and label the role of each file.
Use the model’s layout, realism, multilingual, and regional-editing strengths to reach a stable master. Then validate facts, names, product details, identity, edges, contrast, and crop safety. Re-typeset critical copy in normal design files instead of treating generated pixels as final artwork.
Create deliberate desktop, mobile, social, email, and presentation crops rather than relying on automatic trimming. Keep the approved checkpoint and change one ratio or content zone at a time so the visual system remains recognizable across placements.
A polished Seedream frame can anchor an image-to-video test on Wan 3.0. Describe motion, camera behavior, duration, and protected details separately; image quality alone does not define a stable video. Review the moving product, faces, text zones, occlusion, and end frame before release.
