Seedream 5.5 vs GPT Image 2.6: A Filmmaker’s Test

Seedream 5.5 vs GPT Image 2.6 is the new image-model matchup, and most comparisons test it on product shots and ads. This one tests it the way a filmmaker works: one character carried across storyboard shots, a cinematic wide frame, a poster with exact title text, and a revision made from a reference image. We ran the same prompts once on Seedream 5.5, GPT Image 2.6 Sunburst and GPT Image 2.5 Sunburst, the model most people are still searching for and the one ByteDance benchmarked Seedream 5.5 against.

You’ll also get what each maker published, the official API prices, and what you can use in CinemaDrop today.

Seedream 5.5 vs GPT Image 2.6: the short answer

The two releases aim at different problems. ByteDance built Seedream 5.5 around repeated edits without degradation, transparent assets and cleaner text. OpenAI built GPT Image 2.6 around speed and new outputs: animated GIFs, SVG files and a planning setting. GPT Image 2.5 stays a sensible baseline at the same token rates.

Our one-take renders favored GPT Image 2.6 Sunburst: it alone spelled the poster exactly, kept the scar in every close shot and landed the two-window edit. Seedream 5.5 made the most natural-looking frames but dropped the scar once and added a garbled poster line. One take each is a test, not a benchmark.

What’s new in Seedream 5.5

ByteDance’s Seed team describes Seedream 5.5 as its next-generation image creation model, with three headline upgrades. If you’re coming from the previous release, our Seedream 5.0 guide covers Lite and Pro.

• Stable multi-turn editing. ByteDance says Seedream 5.5 preserves unedited regions at the pixel level, without color shifts, and reduces detail loss across successive edits. Its demo runs 100 rounds of edits on the same image, each using the previous output.
• Native RGBA output. The model can generate images with an alpha channel, including full and partial transparency, so an element can drop into a composite without background removal.
• More realistic images and clearer text. ByteDance says lighting, materials and skin look more natural, with less excess gloss and overexposure, and that dense small text renders more accurately.

The numbers come from ByteDance’s own evaluation on its MagicArena platform, across six use cases including film and television. ByteDance reports a severe text corruption rate of 0.4% and a minor rate of 1.7%. It says Seedream 5.5 leads GPT Image 2.5 Sunburst and Nano Banana 2.1 in text structure and shows a substantial advantage in text-to-image realism. In film and television, ByteDance says usability rates were more than twice those of Seedream 5.0 Pro. These are the maker’s results, not an independent benchmark. ByteDance also says a Pro version of Seedream 5.5 will follow.

What’s new in GPT Image 2.6 (Sunburst and Flare)

OpenAI released GPT Image 2.6 on November 4, 2026, in two variants. Sunburst is for detailed work, and OpenAI says it brings “even greater image consistency across edits when quality is set to medium or high.” Flare is for fast iteration, and OpenAI says it improves layout quality for posters and product imagery. Sunburst and Flare are also the variant names on GPT Image 2.5, so always check the version number as well as the variant.

• Speed. OpenAI says Images 2.6 “generates images 50% faster than before.”
• Animated GIFs. OpenAI names “animated storyboards to explore character movement before video production” as a use case, which makes this the most filmmaker-relevant addition. GIF output works on both new images and edits.
• SVG output. Vector files with editable paths and colors, for new images only, one at a time.
• A complexity setting. Low, medium or high (the default is high) controls how much the model plans before rendering, at no separate fee. OpenAI suggests low for focused edits and higher for dense text or complex layouts, which can add latency and unwanted changes.
• Markup-guided edits. You draw on an annotation layer to show where a change goes. Markup applies to the first input image; any other images act as references.

OpenAI says Images 2.6 is available in ChatGPT and Codex across all subscription tiers, as well as in the API.

GPT Image 2.6 vs GPT Image 2.5: what changed for storyboards

GPT Image 2.5 arrived on September 8, 2026, also as Sunburst and Flare. OpenAI’s changelog recommends Sunburst “for workflows where editing precision matters most” and Flare for fast, everyday generation. Both versions offer the same five quality levels: low, medium, high, xhigh and max.

For a storyboard artist, 2.6 adds GIF previews of character movement, SVG output, the complexity setting and OpenAI’s “50% faster” claim. Markup-guided editing is not exclusive to 2.6: OpenAI added it for supported GPT Image 2.5 models the same day.

Pricing hardly moved. OpenAI’s pricing page lists the same token rates for GPT Image 2.6 and GPT Image 2.5: $8 per million image input tokens, $30 per million image output tokens and $5 per million text input tokens, with Batch rates at half that. OpenAI adds a caveat worth keeping: “Equal token rates don’t mean equal cost per image,” because token use varies by model and quality setting.

So is GPT Image 2.5 still worth using? For storyboard stills, yes. It shares 2.6’s prices and quality levels, it now supports markup edits, and it’s the version you can use in CinemaDrop today. If you searched for “chat gpt image 2.5”, note that OpenAI’s announcement names Images 2.6 as the version in ChatGPT.

Specs and pricing: Seedream 5.5 vs GPT Image 2.6 vs GPT Image 2.5

Every cell comes from the maker’s own pages, checked November 13, 2026. Where a maker doesn’t publish something, the table says so.

BytePlus charges per image within each size tier, while OpenAI bills tokens, so a GPT image’s cost depends on its size and quality.

How we tested: same prompt, one take, three models

Each prompt went to all three models word for word, at 16:9 except the 9:16 poster, with one take per model, GPT models at high quality and no rerolls. Weak results stay in. Our character, Mara Voss, is fictional, as is every place and title. We judged what a director would notice in review: identity drift, legibility and what changed that shouldn’t have.

Our AI video prompts guide covers the same prompt structure: subject, setting, camera, light and style.

Test 1: a character sheet

A character sheet is the reference every later shot leans on. If the scar, coat or hair changes between views here, it drifts further in the storyboard. It’s the job of a character sheet generator: several angles and expressions of one person in a single image.

Character reference sheet of Mara Voss, a weathered lighthouse keeper in her late 40s: short silver-streaked black hair, a thin scar through her left eyebrow, a dark green oilskin coat over a cream cable-knit sweater, brass compass on a cord. Front view, three-quarter view and side profile standing on a plain light-grey background, plus three head close-ups showing neutral, worried and determined expressions. Even studio lighting, realistic film still style, no text.

What we checked: the same face in all six views, the scar on the left eyebrow every time, and matching coat, sweater and compass.

Both GPT models drew full-length standing views with the scar through her left eyebrow. Seedream 5.5 kept the face, coat and compass consistent, but its standing views crop at the hips, a weaker full-body reference.

Test 2: the same character in three storyboard shots

This is the core test for anyone storyboarding with AI. Each model got its own Test 1 sheet back as a reference image, then three separate shot prompts: a wide, a medium and a close-up. The shot sizes follow standard camera shot types, the kind you’d list in a shot list.

2a Wide: Wide establishing shot: Mara Voss from the reference walks along a rocky cliff path toward a white lighthouse at dusk, storm clouds, small figure in the lower third, cinematic 16:9 film still.

2b Medium: Medium shot inside the lighthouse lamp room at night: Mara Voss from the reference, same coat and scar, lit by the warm rotating lamp, looking out the rain-streaked glass, cinematic film still.

2c Close-up: Close-up of Mara Voss from the reference, rain on her face, jaw set, cold blue moonlight, shallow depth of field, cinematic film still.

What we checked: the face, hair, scar, coat and compass against the Test 1 sheet, shot by shot. Small drift here matters, because inconsistent AI video usually starts with inconsistent frames, and a storyboard frame often becomes the start frame of a clip. See our guide to creating consistent AI characters.

Only Seedream 5.5 followed the wide’s direction, walking Mara toward the lighthouse. Both GPT models walked her toward the sea instead, and 2.5’s figure is large, not small as prompted. In the medium, Seedream lost the scar; both GPT models kept it. All three close-ups hold the face.

Test 3: a cinematic wide frame

Some frames have to sell mood, light and scale without a close-up. We asked for a scope-style composition inside 16:9, with the action in the middle band so it survives a letterbox matte.

Anamorphic-style cinematic wide shot of a rain-soaked harbor town at blue hour, sodium-vapor street lamps reflecting on wet cobblestones, a lone figure in a green oilskin coat under a flickering lamp, fog over the water, 2.39:1 composition framed inside 16:9 with action in the middle band, film grain, no text.

What we checked: believable light and reflections, whether the frame reads as a film still rather than an illustration, and whether the figure and key light stay inside the middle band.

All three added letterbox bars on their own and kept the figure in the middle band. Seedream’s frame is cooler and sparser, the GPT frames warmer and denser: a matter of taste on one take.

Test 4: a movie poster with title text

Title text is where image models used to fail most visibly. ByteDance claims better text accuracy and OpenAI better poster layout with Flare. We used Sunburst on both GPT versions, so this doesn’t test Flare’s claim. If you’re cutting a teaser, our AI movie trailer guide shows where a key art frame fits.

Theatrical one-sheet movie poster for a coastal thriller: Mara Voss silhouetted against a lighthouse beam in a storm. Title at top in bold serif capitals: THE LAST LIGHT. Tagline below the title: Every storm keeps a secret. Bottom line in small caps: COMING SOON. No other text, no logos.

What we checked: exact spelling of all three lines, legibility, title-safe placement and any extra text.

GPT Image 2.6 Sunburst got every line exactly right. GPT Image 2.5 was correct but wrapped the title onto two lines. Seedream 5.5 added a garbled extra line under the tagline. None rendered true small caps for COMING SOON.

Test 5: editing a frame from a reference image

Directors revise frames: the same shot, later at night, with a light on in a window. Each model got its own Test 3 frame and one plain instruction, rather than OpenAI’s markup route. For multi-image setups, see our pages on multi-reference image generation and the reference image prompt workflow.

Change the scene from blue hour to deep night, add warm light in two upstairs windows on the left, keep the composition, the figure and the street exactly the same.

What we checked: whether the requested changes landed, and what changed that shouldn’t have, such as the figure, the lamp positions or the reflections.

Seedream 5.5 and GPT Image 2.6 both turned the scene to night and warmed two windows on the left, keeping the figure and street in place. GPT Image 2.5 brightened one tall window that was already lit, a partial edit.

Which should filmmakers use?

These picks come only from the five tests above, one take each, so test your own key shot first.

• Character continuity: either GPT model; both kept the scar and full-length views.
• Cinematic frames: a tie on this take.
• Title text: GPT Image 2.6 Sunburst, the only exact poster.
• Revisions: Seedream 5.5 or GPT Image 2.6 Sunburst.

Two choices don’t depend on our renders. If you want to preview character movement before you make video, GPT Image 2.6’s GIF output is the only built-in option of the three. If you need cut-out elements for compositing, Seedream 5.5’s native transparency is the documented feature to try.

Using GPT Image and Seedream in CinemaDrop

Seedream 5.5 and GPT Image 2.6 are both coming soon to CinemaDrop. Neither is in the app yet. Here’s what you can use for the same work right now:

• GPT Image 2.5 Sunburst is CinemaDrop’s default image model, and the default for Edit Image and for new Element images. GPT Image 2.5 Flare is there too. Both accept up to 16 reference images.
• Seedream 5.0 Lite accepts up to 14 reference images and costs 10 credits per image at any size.
• Character Elements hold up to four images of a character, and you @-tag them in storyboard shot prompts to carry the character from shot to shot. This is the in-app answer to Test 2, and it’s what our consistent characters and scene continuity pages are built on.
• Edit Image lets you describe a change to an existing frame, the kind of revision Test 5 makes. It’s on every plan, from the free Lite plan up. The Edit Image guide covers the steps.

Images come in 16:9, 1:1 or 9:16. On the credits page, GPT Image 2.5 Sunburst and Flare cost the same: 5 to 26 credits per 16:9 or 9:16 image and 6 to 32 at 1:1, from Low to Max quality.

FAQ

Is Seedream 5.5 better than GPT Image 2.6?

Not across the board. ByteDance’s own evaluation favors Seedream 5.5 on text and realism against GPT Image 2.5 Sunburst, not 2.6. OpenAI’s 2.6 adds GIF and SVG output that Seedream doesn’t list. Our test-by-test picks are in the section above.

What’s the difference between GPT Image 2.6 and GPT Image 2.5?

Version 2.6 adds animated GIF and SVG output, a complexity setting and, per OpenAI, 50% faster generation. Token rates and quality levels are the same, and both versions support markup-guided edits.

What’s the difference between Sunburst and Flare?

They’re variants of both versions. OpenAI positions Sunburst for detail and editing precision and Flare for speed. On 2.6, OpenAI also says Flare improves poster and product layouts.

Is GPT Image 2.5 still worth using?

Yes, for storyboards: same token rates as 2.6, markup edits, and it’s in CinemaDrop today.

Which is better for consistent characters across storyboard shots?

In our one-take Test 2, both GPT models kept the scar; Seedream 5.5 lost it once. Start from a strong character sheet, or use Character Elements in CinemaDrop.

Which renders title text more accurately?

ByteDance reports low text corruption rates for Seedream 5.5 in its own evaluation, and OpenAI says GPT Image 2.6 Flare improves poster layout. On our one poster take, only GPT Image 2.6 Sunburst was exact.

How much do Seedream 5.5 and GPT Image 2.6 cost?

On BytePlus ModelArk, Seedream 5.5 costs $0.020 or $0.035 per output image depending on size, plus $0.008 per input image. GPT Image 2.6 costs $30 per million image output tokens on OpenAI’s API, so the price per image varies with size and quality. Rates as of November 13, 2026.

Can I use ChatGPT Images 2.6 for free?

OpenAI says Images 2.6 is in ChatGPT across all subscription tiers. Its announcement doesn’t publish usage limits, so check your plan.

Can I use Seedream 5.5 or GPT Image 2.6 in CinemaDrop?

Not yet. Both are coming soon to CinemaDrop. Today you can use GPT Image 2.5 Sunburst, GPT Image 2.5 Flare and Seedream 5.0 Lite.

Start a storyboard with GPT Image 2.5 Sunburst

You don’t have to wait for either new model. Build your character as an Element, then start a storyboard with GPT Image 2.5 Sunburst, the default, or try Seedream 5.0 Lite on the same shot in the Playground. Our guide to storyboarding with AI walks through the process, and plans start free.