Comparison

Seedream 5.5 vs Nano Banana 2.1 vs GPT Image 2.6

Q: Is the same quality value comparable across the models?

No. On Seedream and Nano Banana, quality selects resolution tiers. GPT uses rendering-quality values and a separate resolution setting; complexity controls planning. Match the required file and review actual results rather than copying the same field values.

Compare Seedream 5.5, Nano Banana 2.1 and GPT Image 2.6 for transparent PNGs, layers, 4K, editing, SVG and the cost of a finished asset.

Himi LiProduct Manager at EvoLink

November 13, 202615 min read

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Start with the asset you need to deliver. Seedream 5.5 is a useful first candidate when the job depends on native transparent PNGs or separating an existing design into reusable layers. Nano Banana 2.1 is worth evaluating when 4K still images, multiple references or search grounding matter. GPT Image 2.6 offers a different set of controls for targeted editing, plus GIF and SVG workflows.

All three can generate and edit images. The choice becomes clearer when you ask what must survive an edit, what file your designer needs, and what counts as an acceptable result. A finished product cutout, an editable vector illustration and a collection of raster layers are different deliverables, even when they look similar in a browser.

Which model fits your task?

The table summarizes the EvoLink routes checked on November 13, 2026. Official model capabilities and a particular gateway's request fields are separate scopes; the explanations below use the current EvoLink contracts for integration details.

Decision	Seedream 5.5	Nano Banana 2.1	GPT Image 2.6
Generation route	`doubao-seedream-5.5`	`gemini-nano-banana-2.1`	`gpt-image-2.6` Flare; `gpt-image-2.6-sunburst`
Reference inputs	Up to 10	Up to 14	Up to 16
Size controls	1K / 1.5K / 2K; ratios or custom pixels	1K / 2K / 4K; preset ratios	1K / 2K / 4K; ratios or custom pixels, within pixel limits
Transparency control	Native `background: transparent`; PNG	No dedicated background field on this route	`background: transparent` is Preview; PNG or WebP
Existing design into layers	Separate Layerize route; base plus up to 99 PNG layers	Reference editing and composition	Mask or markup-guided edits; SVG is a different output workflow
Search controls	No web/image search switches on this route	Optional web and image search	No built-in search switches on these routes
Other deliverables	Recognized text and style data from suitable Layerize text layers	High-resolution still images	GIF animation; SVG through reference-image and authoring stages
Billing basis	Output tiers, input images; Layerize per image produced	Output tiers plus references, actual searches and text/thinking usage	Token usage; SVG also bills its authoring model

Use Seedream 5.5, Nano Banana 2.1, GPT Image 2.6 Flare and Sunburst for current prices and route examples. This article helps with the choice; those pages own the live integration and pricing information.

What each model adds to an image workflow

Seedream 5.5: transparent assets and reusable design elements

Seedream 5.5 combines text-to-image, reference-image editing and native RGBA generation. Its transparent output can include both fully transparent areas and partially transparent material. That makes it relevant to product elements, stickers and other assets that need to sit on different backgrounds. A white backdrop or a drawn checkerboard does not satisfy this requirement: inspect the downloaded PNG's alpha channel and place it on several background colors.

The generation route returns one image per request. It accepts up to 10 references, offers 1K, 1.5K and 2K tiers, and supports ratios or custom pixel dimensions. It uses prompt_priority: standard; a request migrated from Seedream 5.0 Pro must remove fast rather than assuming the modes carry over.

For an existing poster or design, use the separate doubao-seedream-5.5-layerize route. It accepts exactly one PNG or JPEG and returns a base image plus up to 99 transparent PNG layers. Optional recognition can attach text and style information to clean text layers; it does not recognize artistic lettering or handwriting. These are raster assets and recognition data, not a PSD project or automatically editable vector text. Seedream 5.5 request reference, Layerize reference.

Nano Banana 2.1: references, large stills and search grounding

Nano Banana 2.1 accepts up to 14 reference images on EvoLink. Its resolution selection is quality: 1K, 2K or 4K, and its ratio presets include very wide and tall formats such as 8:1 and 1:8. This is useful when the same campaign needs several placements or a composition must incorporate multiple supplied elements.

Its distinguishing integration option is optional web and image search. Search can help retrieve current information or visual references before generation, but the resulting image still needs factual and rights review. For a product launch graphic, verify dates, labels and source material independently; a search-enabled generation is not a guarantee that every fact was reproduced correctly.

Search is off by default. Enable it only when it serves the brief, since actual queries are billed and one generation can issue several queries. The current EvoLink route has no separate background-transparency parameter. That is a statement about this route's controls, not a claim that every Google image product is incapable of producing transparency. Google model documentation, EvoLink request reference.

GPT Image 2.6: targeted edits and additional output formats

GPT Image 2.6 includes Flare for fast iteration and Sunburst for detailed visual work. That positioning helps choose a first candidate; it does not establish the fastest or best-looking result for your own prompt. Record actual turnaround and accepted output in your workflow.

Two editing controls matter. A mask specifies the area to regenerate. A separate transparent markup_url layer can instead point to the object with circles, sketches or notes, while the prompt describes the change. On EvoLink, markup must match the first reference image's dimensions and cannot be combined with mask_url in the same request.

quality controls rendering, while complexity controls planning. Raising both together makes it harder to identify which change helped. Test them separately for dense text, object relationships or a focused edit. Transparency is a Preview option and requires PNG or WebP on these routes. GIF output adds a sequence and timing decision; SVG adds a reference-image stage and a separately billed SVG authoring model. Flare model card, Sunburst model card, current EvoLink reference.

On the documented EvoLink GPT routes, SVG supports generation only: set n: 1 and do not send image_urls. The reference image in this process is generated internally; it is not an uploaded finished design being converted to SVG.

Transparent PNG, PNG layers and SVG solve different problems

A transparent PNG is one raster image with an alpha channel. It can be placed on another background, but the product, text and decorations inside it are not automatically separate objects. Use it when the entire element should move as one asset.

A Layerize result is a collection of raster images representing extracted elements and a base. It supports rearrangement, replacement and compositing, but a text layer remains pixels even when recognition also supplies its wording and style. If your designer needs live text, plan a recreation step in the design tool using the recognized information.

An SVG describes vector shapes and paths. It is suitable when the deliverable requires scalable geometry, but its usefulness depends on the actual structure of the file. Open it in the intended editor and inspect paths, text and embedded raster content. A file extension alone does not establish convenient editability.

This distinction changes the trial. For a product sticker, test alpha and edges. For a localized campaign, test element separation and the time needed to rebuild text. For an icon set, test vector structure and scaling. Comparing all three as “editable images” would hide the work required after generation.

For the next step, use the transparent PNG delivery guide, the Layerize recomposition workflow, or the 5.5 vs 5.0 Pro switching guide.

Compare dimensions, not just the 2K or 4K label

Seedream 5.5's generation route offers 1K, 1.5K and 2K tiers, with custom dimensions classified by pixel count. Layerize accepts its own quality options and does not take the generation route's ratio or custom-size fields. Nano Banana 2.1 offers its own resolution tiers and aspect-ratio presets. GPT Image 2.6 uses a resolution shortcut with ratio sizes, while explicit pixel sizes follow separate limits.

On the current GPT routes, 4K at 16:9 corresponds to 3840 × 2160; square 4K is 2880 × 2880 under the 8,294,400-pixel budget. It does not mean 4096 × 4096. Nano Banana's 8:1 preset also cannot be copied to GPT's current 3:1 aspect-ratio limit.

Write the required width, height and crop tolerance into the brief. Then inspect each returned file. If one candidate needs an upscaler, padding or a crop to meet delivery requirements, include that extra step in the cost and time comparison.

How to compare the complete cost

Seedream: count inputs, output tiers and extracted layers

For ordinary generation or editing, the task cost is the selected output tier plus one input-image charge for each reference. A prompt-only transparent asset and an edit with several references therefore have different totals even at the same output tier.

Layerize bills one input image and every image actually produced, each at its own tier. A base plus eight layers is nine output images. If all nine are in the low tier, its cost is input rate + 9 × low-tier output rate.

The reserve is different from the final charge: n caps total outputs including the base, from 2 to 100, with a default of 30. The initial reserve uses one input plus n outputs at the 2K rate; unused reserve is returned after actual output billing. A larger reservation does not mean the model produced or charged for that many layers.

Nano Banana: include references and actual searches

The output tier is only part of the total. Include reference images, prompt/thinking usage and the actual number of web or image searches. An estimate based on one enabled tool is not a fixed one-query charge for every task. Compare a search-disabled supplied-reference job with another job under the same information conditions, rather than attributing retrieval costs to image quality.

GPT Image: use returned usage and account for SVG's second stage

Token rates are not a flat price per image. Size, quality and input material affect usage. GIFs also change the output being purchased. SVG has the image model's reference-generation stage and the selected authoring model's token cost, so a raster-image estimate is not the entire SVG budget. OpenAI pricing.

For all three, record total billable spend divided by the number of accepted deliverables. Include retries, follow-up edits and necessary finishing steps. Use the current model-page rates for your account; do not turn a dated headline price or an untested speed claim into a universal cost winner.

Four practical briefs for choosing a model

The following fictional briefs are reusable test inputs, not reported benchmark results. Keep the source assets and acceptance criteria fixed; adapt the request fields to each model.

1. A transparent product asset

Supply the same product reference and request a centered cutout on a transparent canvas, preserving its shape, label and fine edges. A possible prompt is:

Create a standalone asset of the product in the reference image.
Preserve its shape, label text and material. Keep the full product visible.
Use a transparent background; do not draw a checkerboard or a floor.

Start with Seedream's native transparency control and GPT's Preview option. For the Nano Banana route, account for any separate background-removal step your pipeline needs. Inspect alpha, halos, semi-transparent parts and product identity on light and dark backgrounds. A visually white background is not a pass.

2. Three edits to one campaign image

Begin with one supplied poster. First change the product color, then replace one line of copy, then change only the background lighting. Use each accepted output as the next input and save every version.

Check the logo, unchanged lettering, product geometry and layout after each round. GPT's mask or markup can help specify a local edit; Seedream and Nano Banana also support reference-led revisions. Record unwanted changes and recovery work. If the product identity fails, return to the last accepted version instead of continuing a damaged chain.

3. A 4K visual using current information

Provide a fixed event brief with verified names, dates and a required aspect ratio. If retrieval is part of the job, test Nano Banana's search tools and retain the facts and references used. For a comparable generation-only trial, give the same verified information to all candidates.

Verify both facts and returned pixel dimensions. A model that retrieves information and a model given a completed fact sheet are doing different amounts of work; make that distinction visible in the timing and billing record.

4. A design that must remain reusable

Decide whether the recipient needs separate raster elements, live text, vector paths or a short animation. Try Layerize when the starting point is a finished design that needs independent elements. Try GPT's SVG workflow for a vector deliverable, or its GIF workflow for an animation. Judge the output in the actual design or publishing tool, including the time spent correcting text, ordering elements or rebuilding shapes.

Move from the trial to an API workflow

On EvoLink the models share an asynchronous task flow, but their fields are not interchangeable. For example, Seedream and Nano Banana use quality for resolution tiers, whereas GPT separates resolution, rendering quality and planning complexity. A model-ID substitution alone can change the meaning of a request.

This Seedream request is a template for the first brief, not a recorded generation:

{
  "model": "doubao-seedream-5.5",
  "prompt": "Create a standalone product asset from the reference. Preserve the label and shape; use a transparent background.",
  "image_urls": ["https://example.com/product.png"],
  "size": "1:1",
  "quality": "1.5K",
  "background": "transparent",
  "output_format": "png"
}

Replace the example image URL with your accessible asset, submit through the documented image-task endpoint, save the task ID and poll or use an HTTPS callback. Archive the request, status, usage, output dimensions and accepted/rejected decision together. The Seedream page and each alternative's API reference provide the full field contract.

What can you conclude about image quality?

Use vendor evaluations as evidence for their stated setup, then test your own deliverable. ByteDance's Seedream 5.5 announcement compares text structure and realism with Seedream 5.0 Pro, Nano Banana 2.1 and GPT Image 2.5 Sunburst. It is not a direct benchmark against GPT Image 2.6. Its long-edit demonstrations also do not guarantee that every customer image will survive the same sequence unchanged. ByteDance evaluation and demonstrations.

Choose a first candidate from the required output and controls, then compare actual acceptance, finishing work, spend and turnaround. A lower rate, a newer release and a higher resolution label are useful inputs to a decision; none is a substitute for meeting the brief.

Frequently asked questions

Which model should I start with for ecommerce images?

Start with the deliverable. Seedream 5.5 is a candidate for transparent product assets and extracted elements; Nano Banana 2.1 for large multi-reference compositions or search-assisted visuals; GPT Image 2.6 for explicitly guided edits and SVG or GIF requirements. Verify product identity and label accuracy with your own references.

Does Layerize return an editable PSD or SVG?

No. It returns a base and separate PNG layers, with optional recognition data for suitable text. Rebuilding live text or a vector design is a separate step. GPT's SVG output is a different generation workflow.

Is the same quality value comparable across the models?

No. On Seedream and Nano Banana, quality selects resolution tiers. GPT uses rendering-quality values and a separate resolution setting; complexity controls planning. Match the required file and review actual results rather than copying the same field values.

Which is cheapest for a finished asset?

That depends on the inputs, output, attempts and finishing work. Use live rates and actual billed usage, then divide complete workflow spend by accepted deliverables. Treat Layerize reserves and SVG authoring costs according to their own rules.

Can I use one EvoLink API key for all three?

Yes. One key and balance can cover these routes, with shared task tracking. Keep model-specific validation, output handling and billing expectations in your integration. You can compare the model pages before committing to a production routing choice.

Does a white or checkerboard background prove transparency?

No. Download the file and inspect its alpha channel, then preview it on light and dark backgrounds. Seedream has a native transparency control, GPT offers a Preview control, and this Nano Banana route has no dedicated background field; include any separate removal and edge cleanup in the workflow.

Does 4K always mean 4096 × 4096?

No. On the documented GPT routes, 4K at 16:9 is 3840 × 2160 and square 4K is 2880 × 2880. Seedream generation has no 4K tier. Choose by required pixel dimensions, ratio and crop tolerance, then inspect the returned file.

Is this a measured three-model benchmark?

No. This guide compares documented capabilities and provides fictional evaluation briefs; no EvoLink generation API requests were run for it. ByteDance’s cited comparison uses GPT Image 2.5 Sunburst, not 2.6. Your own acceptance, turnaround and billed usage remain to be measured.

Sources and further reading

ByteDance Seedream 5.5 announcement.
Google Nano Banana 2.1 model documentation.
Official OpenAI image generation documentation and pricing.
EvoLink Seedream 5.5, Nano Banana 2.1, Flare and Sunburst routes.
GPT Image 2.6 Flare vs Sunburst for the narrower choice between the two OpenAI variants.

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#Seedream 5.5 #Nano Banana 2.1 #GPT Image 2.6