For Seedream vs Nano Banana vs GPT Image, our task-by-task picks are Seedream 5.5 for the poster hierarchy and the three-round edit, where it changed the least outside each requested edit, and GPT Image 2.6 for the infographic, where it alone keeps the requested letter case. Nano Banana 2.1 and GPT Image tie on the product brief and the portrait, which Seedream misses with added plants and overlapping hands; Seedream and Nano Banana tie on the small-text menu, and all three tie on the multilingual sign. No sticker passes every transparency check; GPT Image comes closest. This comparison covers Seedream 5.5, Nano Banana 2.1 and GPT Image 2.6 Sunburst, with eight shared briefs covering text, edits, transparency, products and portraits. The prompts request a square 1K canvas; the returned dimensions differ between routes.
Results status All 30 comparison images are first-attempt outputs from Seedream 5.5, Nano Banana 2.1 and GPT Image 2.6 Sunburst in ChatCut, generated on November 13, 2026 with the prompts shown. No column contains substitute images, and no result was re-rolled.
Key Takeaways
- Start with the summary table, then inspect the three images beside each copyable prompt.
- Check exact lettering, item-price pairs and diagram connections before deciding whether a design is ready to use.
- The editing comparison shows every round, starting from the same source file for all three models.
- The sticker test inspects original PNG alpha and visible edge defects; a checkerboard preview alone does not establish transparency.
- GPT Image 2.6 means Sunburst throughout this comparison. The existing GPT Image 2 and Nano Banana Pro comparison uses earlier models. Read the earlier comparison.
Seedream vs Nano Banana vs GPT Image results at a glance
| Test | What earns the win | Winner |
|---|---|---|
| 1. Text poster | Four exact text fields and clear hierarchy | Seedream: all three keep 4/4 fields, but only Seedream keeps the date clearly smaller than the headline |
| 2. Small-text menu | Every item, price and footer character survives | Tie: Seedream and Nano Banana keep 12/12 fields in small type; GPT Image is also exact but enlarges the type to fill the card |
| 3. Three-round editing | Each requested change works and earlier details survive | Seedream: all three complete every round, but Seedream changes the least outside the edits (mean protected-area difference 1.6 vs 5.4 for the other two after round 3). It also edits its own source image |
| 4. Transparent sticker | Usable alpha, clean fur edges and a partly transparent bubble | No strict pass: Seedream has clean zero-alpha margins but an opaque bubble; GPT Image has the see-through bubble but faint alpha-1 pixels in the margin; Nano Banana has no alpha. GPT Image is the closest usable sticker |
| 5. Product image | The specified bottle, material, framing and contact shadow | Tie: Nano Banana and GPT Image meet every feature with no extra objects; Seedream adds plants beside the plinth |
| 6. Portrait | Natural skin and light, coherent eyes and two intact hands | Tie: Nano Banana and GPT Image show two separate hands; Seedream rests one hand on the other |
| 7. Infographic | Correct words, card associations and arrow direction | GPT Image: the only result with 10/10 exact fields, including the requested heading case |
| 8. Multilingual text | All six fields correct, with every script and accent preserved | Tie: all three show 6/6 fields, including the traditional Chinese, the middle dot and the accent |
How we compare Seedream vs Nano Banana vs GPT Image
The comparison uses seven static briefs and one three-edit chain per model. Every image in the three columns is the first result returned for its request; none was re-rolled. This is not a blind review. The cover is a separate Seedream 5.5 image with a light film finish added afterwards; the comparison images have no filter. The method diagram below represents the test design; the provenance and settings notes describe the files actually shown.
| Control | Shared test setting |
|---|---|
| Planned versions | Seedream 5.5, Nano Banana 2.1, GPT Image 2.6 Sunburst |
| Route | ChatCut for all three |
| Size and composition | Request 1K, 1:1, 1024 × 1024 pixels for every scored image |
| Output count | One image per request |
| Prompt | Copy each card verbatim, including punctuation and quoted text |
| References | Text-only for static tasks. Test 3 starts from the same Seedream 5.5 T05 output for all three models |
| Background | Auto for opaque tasks; transparent requested for T04 on Seedream and GPT Image (the Nano Banana route has no background control) |
| Optional controls | Keep shared controls identical. Record each route’s quality, complexity, prompt enhancement and grounding settings |
| Edit context | Attach only the previous image and the current round’s instruction |
| Review | Compare native-size files with model labels hidden, then reveal the model names |
Settings record Every image was generated in ChatCut on November 13, 2026, one request per image, at 1K and 1:1. Seedream 5.5 ran at its defaults (this route has no quality or complexity control), nano-banana-2.1 with complexity high and gpt-image-2.6-sunburst with quality high and the default complexity. T04 requested a transparent background from Seedream and GPT Image; Nano Banana has no background setting. The delivered square files are 1024 × 1024 for Seedream and Nano Banana and 1056 × 1056 for GPT Image. Prompt enhancement and grounding are not exposed per request and were left at each route’s default; this is a visual comparison, not a fully matched benchmark.
Seedream controls in ChatCut Pick Seedream 5.5 in the model menu; the available size, ratio and credit cost are shown before you generate. Check the current output options for transparency, then inspect the downloaded original rather than assuming a file has alpha from its preview.
The table states the requested test conditions. Read back the actual dimensions and settings for every output before filling a matched-setting verdict. Record unavailable controls explicitly. Quality and reasoning labels can differ between providers, so include their effective values with the results.
Retain original files, exact requests, job IDs, timestamps, billed credits and failed-request details. Save a failed request before any transport retry and record the retry separately. Use the initial scheduled output for the image slots, including an unattractive result. An interrupted edit chain retains its completed rounds and records the first failed round.
For text tasks, count exact fields against the quoted strings, with Unicode NFC normalization. Check case, punctuation, prices and accents. The menu has twelve fields, the infographic ten and the multilingual notice six. Inspect at native size and have fluent readers check the non-English lines.
Review each task on three dimensions from 0 to 3 — brief accuracy, preservation or structure, and visual finish. A score of 0 means the requirement is missing, 1 needs substantial repair, 2 has a minor defect and 3 meets the brief. The observations below give editorial scores for all three models. Use the highest total only after the required checks pass; a closer visual match can still fail a strict check. Report a tie for equal totals and “no usable result” when every output fails a required check. These conclusions describe this set of briefs and its recorded attempts.
ByteDance released Seedream 5.5 on November 9, 2026, highlighting stable successive edits, native RGBA assets, realism and small text. Those official claims determine which tasks we examine here. ByteDance’s announcement.
The layout borrows fal’s paired-output approach, and the revision test follows Atlas Cloud’s practice of feeding one round’s output into the next. Their published comparisons use their own routes, versions and settings. fal’s same-prompt comparison, Atlas Cloud’s chained test.
Test 1 — Exact-text poster
An event poster needs the right date and venue as well as a strong headline. T01 checks four specified text fields and their hierarchy.
Check Compare all four quoted fields character by character. Inspect the venue line at native size, confirm every field sits inside the frame and count any extra words.
Observed result All three keep 4/4 fields exactly, including the middle dot and the dash in “Corner Park · 9am–2pm”, with no extra words. Seedream sets the text in a calm block under a skyline-and-stalls illustration and is the only one that keeps the date clearly second in size; Nano Banana and GPT Image both set the date about as tall as the headline. GPT Image has the most convincing two-ink print texture. Editorial scores (brief accuracy / structure / finish) are 3/3/3 for Seedream and 3/2/3 for Nano Banana and GPT Image: Seedream wins on hierarchy.
Test 2 — Small-text menu
T02 separates readable headline text from the smaller copy that fills a real menu. Every decimal and item-price association matters.
Check Verify twelve fields — title, ten complete rows and footer — plus the ten item-price pairings. Inspect the footer and the longest item names at native size. Note whether the footer stays small, as the prompt requests.
Observed result All three keep 12/12 fields exactly, including Stracciatella at $4.30, Affogato at $5.80 and the footer’s “+$0.80 · Open daily 12–9pm”. Seedream and Nano Banana set the rows in small type on a card with wide margins, and Nano Banana adds dotted leaders. GPT Image enlarges every line until the menu fills the canvas edge to edge, so its footer is no longer small and the layout has almost no margin. Scores are 3/3/3 for Seedream and Nano Banana and 3/2/3 for GPT Image (accuracy / structure / finish): a tie between Seedream and Nano Banana.
Test 3 — Three-round editing
The common source is the Seedream 5.5 output from Test 5: a butter-yellow bottle with a white cap and loop and a cobalt-blue band on a red plinth. All three models edit that same file in round 1. Open the shared source.
This source choice is fixed before review. The editing result is conditional on this Seedream-generated source, including the plants Seedream added beside the plinth. From round 2 onward, each model receives its own immediately preceding output. Keep the earlier changes in place as the chain progresses.
Round 1 — Change the bottle color
Round 2 — Add one lemon
Round 3 — Change the band color
Check Record the requested change as pass or fail after each round. By round 3 the scene should contain a mint-green bottle, white cap, white loop, bubblegum-pink band and one yellow lemon. Compare the bottle silhouette, crop, background and plinth against both the preceding image and the common source. Keep the same protected-area mask across models, excluding the bottle body, band, lemon placement and their affected contact shadows. Record the protected-area mean absolute RGB difference on a 0–255 scale.
Observed result All three complete rounds 1/2/3: a mint-green body, one lemon on the left with its own shadow, then a pink band, with each earlier change kept. Seedream changes the least outside the edits: measured over the same protected area (everything except the bottle and the lemon’s corner of the plinth), its round-3 image differs from the common source by a mean of 1.6 on the 0–255 scale, against 5.4 for both Nano Banana and GPT Image, whose palm shadows, plants and plinth texture drift a little each round. Nano Banana renders a paler, sage-leaning mint and a softer pink; GPT Image gives the brightest mint and slightly rounds the bottle’s shoulders. Chain scores are 3/3/3 for Seedream and 3/2/3 for Nano Banana and GPT Image (accuracy / preservation / finish): Seedream wins. The common source is Seedream’s own T05 output, which may favour Seedream’s edits.
Test 4 — Transparent sticker
T04 requests both fully transparent background pixels and partial transparency inside a bubble. Preserve the downloaded original for the alpha check.
Check Verify an alpha channel in the original file, zero-alpha outer margins and partial alpha inside the bubble. Composite that original over white, black and magenta to inspect the fur, hat and sticker border. Record the delivered format and any unsupported transparency request alongside the result.
Observed result The Seedream PNG is RGBA with zero alpha everywhere in the outer margin and clean sticker edges over black and magenta, but the bubble interior is fully opaque (alpha 255), so a background will not show through it. The Nano Banana PNG is RGB with no alpha: its grey backdrop is part of the image. The GPT Image PNG is RGBA with a genuinely see-through bubble, near-zero alpha in the middle and partial alpha around the rim, and clean edges over magenta and black; however, about 1,700 margin pixels carry alpha 1 instead of 0, and the sticker body sits at alpha 253–254 rather than 255. Scores are 2/3/3 for Seedream, 0/1/2 for Nano Banana and 3/2/3 for GPT Image (accuracy / structure / finish). No file passes every strict check; GPT Image is the closest usable sticker. These are findings for the supplied files, not proof of a general provider limitation.
Test 5 — Product image
T05 asks all three models to invent the same unbranded product from a written specification. The Seedream 5.5 output supplies the shared source for Test 3.
Check Look for one butter-yellow bottle, a white screw cap with a white carry loop and one cobalt-blue band. Inspect the full silhouette, the empty plinth to its left, the palm shadow and the contact shadow, and look for any added objects. This task measures adherence to a fictional product brief. Reference-product preservation is examined in the editing chain.
Observed result Nano Banana and GPT Image pass every visible check: one butter-yellow bottle, a white cap and loop, one cobalt-blue band, empty plinth to the left, a palm shadow and no added objects. Nano Banana uses a rigid loop on a short cap; GPT Image uses a soft fabric loop and leaves more open wall. Seedream renders the bottle itself accurately, with a moulded loop and a crisp band, but adds red-leaved plants on both sides of the plinth, which the prompt excludes. Scores are 2/3/3 for Seedream and 3/3/3 for Nano Banana and GPT Image (accuracy / structure / finish): a tie between Nano Banana and GPT Image.
Test 6 — Portrait
T06 gives all three models the same age, pose, clothing and lighting brief. Keep the face and both hands visible during review.
Check Inspect the eyes, skin texture, shirt fabric and direction of the sunlight. Count two coherent hands with five fingers each and check their contact with the table. Assess the requested age and the film texture in the finished image.
Observed result Nano Banana and GPT Image both show a laughing woman with short grey hair in a striped shirt, two separate hands flat on the table with the fingers visible, a lemonade and a sunlit yellow wall. GPT Image looks most like a film snapshot, with warm halation, soft grain and natural skin lines; Nano Banana is cleaner and shows more of the street. Seedream has a natural, candid expression and real skin texture, but one hand rests on top of the other, which breaks the separate-hands requirement, and she smiles rather than laughs. Scores are 2/1/3 for Seedream and 3/3/3 for Nano Banana and GPT Image (accuracy / anatomy / finish): a tie between Nano Banana and GPT Image.
Test 7 — Infographic
T07 tests whether a model can keep headings, captions and icons associated with the correct step. The workflow content is supplied in full.
Check Verify ten text fields, four cards, four correct heading-caption-icon associations and three right-pointing arrows. Check order, letter case and spacing at native size.
Observed result All three keep the right words, the four heading-caption-icon associations and three right-pointing arrows. Only GPT Image keeps the requested letter case: Seedream sets the four headings in capitals (“1. GRIND”) and Nano Banana capitalises both headings and captions, so they reach 6/10 and 2/10 exact fields against GPT Image’s 10/10. Seedream adds small coffee-bean ornaments; Nano Banana moves the captions below the icons and adds a strainer to card 4. Scores are 2/3/3 for Seedream and Nano Banana and 3/3/3 for GPT Image (accuracy / structure / finish): GPT Image wins.
Test 8 — Multilingual text
T08 combines simplified Chinese, traditional Chinese, English, Spanish and Japanese with a date line. Each model receives exactly the same characters.
Check Verify all six fields in order. Inspect the traditional Chinese characters, the Japanese line, the accent in “Pan recién horneado” and the date punctuation. Record each language’s errors separately so the English line cannot conceal a mistake elsewhere.
Observed result On visual proofreading all three show 6/6 fields in order: the simplified and traditional Chinese lines, including 麵 and 鮮 and the middle dot, “Corner Bakery”, the é in “recién”, the Japanese line and the date with its vertical bar and dash. GPT Image hangs the sign beside the door as described; Nano Banana mounts the board flat on the wall beside the door; Seedream turns it into a standing board with a smiling baker behind it and uses a hand-lettered face. All three score 3/3/3 for accuracy / structure / finish on the text brief: a tie. This is visual proofreading, not independent fluent-reader sign-off or a Unicode extraction.
Which model fits your work?
Seedream vs Nano Banana for text and revisions
Use T01, T02 and T08 for lettering, and inspect the full T03 chain for preservation. A final image can look consistent while an earlier requested change has disappeared.
Seedream and Nano Banana both keep every poster, menu and sign field exact; Seedream follows the poster’s size hierarchy more closely, and Nano Banana switches the infographic to capitals. In the three-round edit both complete every change, but Seedream holds the rest of the scene almost unchanged while Nano Banana lets the background drift and renders paler colours. Seedream edited its own source image here.
Seedream vs GPT Image for transparent assets and product work
Use the native-file checks in T04 and the product specification in T05. Keep the source-file limitation from T03 attached to any editing recommendation.
Seedream returns a real alpha channel with fully transparent margins, but its soap bubble is opaque; GPT Image delivers the see-through bubble, with near-invisible alpha-1 pixels left in the margin. On the product brief GPT Image follows every instruction, while Seedream renders the bottle well but adds plants the prompt excluded.
Nano Banana vs GPT Image for portraits and information design
Compare T06 at native size, then inspect T07’s labels and connections. The decision can differ between an editorial portrait and a diagram with exact copy.
Both models show two separate hands in the portrait, with GPT Image closer to a film snapshot. In the infographic both keep the words and arrows, but GPT Image keeps the requested letter case while Nano Banana capitalises every heading and caption. Both read the multilingual sign correctly.
Time and credits at the tested settings
Record submission-to-downloadable-image time for T01 and the total time for the three-edit chain. Keep the invoice or Credits history record with the request log. Editorial review date — November 13, 2026; billed credits are read from the ChatCut job receipts, and timing was not recorded. Read the current model quote and plan requirements before generating. ChatCut pricing, GPT Image 2.6 settings.
| Model | T01 elapsed time | Full three-edit chain | Credits at the recorded settings |
|---|---|---|---|
| Seedream 5.5 | Not recorded | Not recorded | 0.08 credits per new 1K image; 0.11 per edit round with one reference image; 0.33 for the full chain |
| Nano Banana 2.1 | Not recorded | Not recorded | 0.22–0.26 credits per new 1K image at complexity high; 0.19–0.21 per edit round; 0.59 for the full chain |
| GPT Image 2.6 Sunburst | Not recorded | Not recorded | 0.27 credits per new 1K image at quality high; 0.30–0.31 per edit round; 0.92 for the full chain |
Include charged failures and retries when calculating cost per usable image. For editing, divide the chain’s total charge by usable completed chains and label the unit clearly.
Use the same prompts in ChatCut
Seedream 5.5 is available in ChatCut alongside Nano Banana 2.1 and GPT Image 2.6. Choose the exact model, paste a prompt above and keep the generated image in your project. The settings that need confirmation for Seedream are listed in the method section. Seedream 5.5, GPT Image 2.6, image-generation guide.
Place a generated still on the timeline, or use it as a first frame with Kling 4.0 or Seedance 2.5. Then add captions, voiceover and music and export from the same project. Kling 4.0, Seedance 2.5, image-to-video workflow.
For more briefs, use the Seedream, GPT Image and Nano Banana prompt collections. Seedream 5.5 prompts, GPT Image prompts, Nano Banana prompts.
For version background and broader choices, read the release guide, series overview and previous-version comparison. Seedream 5.5 guide, Seedream series, Seedream 5.5 vs 5.0 Pro. Access and wider model selection have their own guides. Seedream free access, best AI image generators.
Frequently asked questions
Seedream vs Nano Banana — which is better?
Is Seedream 5.5 better than GPT Image 2.6?
What is better, GPT Image 2 or Nano Banana?
Which one is better, Nano Banana or ChatGPT?
Which Nano Banana is best for image generation?
Which AI image generator is the best in 2026?
Is GPT Image 2 slow?
Can Seedream 5.5 generate transparent PNGs?
Cover artwork prompt
The cover is a separate Seedream 5.5 image requested at 2K in 4:3 and 16:9, with a light film finish added afterwards. It shows three framed versions of the same red-bicycle photograph on a cobalt-blue wall.
