The short version
GPT Image 2.5 landed on 8 September 2026 with three claims: sharper images, edits that leave the rest of the picture alone, and consistency across repeated edits. The first week of Reddit reaction added a fourth question — whether the grainy "checkerboard" texture people complained about in GPT Image 2 was fixed — and a fifth: is it worth paying more than Seedream, the model most people were actually using for photoreal work. We tested all five. Nine tests, identical prompts, 2K, one take, no cherry-picking.
- Local edits: GPT Image 2.5 changed the sofa and touched 1.1% of the rest of the picture; Seedream 5 Pro touched 4.5%, Seedream 5 5.4%. On the sign-swap test Seedream 5 Pro was the cleanest (0.5%), GPT 2.0%, Seedream 5 13.1%. Both premium models keep what you did not ask them to change; the cheap tier does not.
- Three-turn editing: all three models carried a sofa swap, an added cat and a change to evening light through three rounds without losing an object. GPT Image 2.5 drifted under 1% per turn; Seedream 5 Pro 6.1% then 0.1% and invented a window on the evening pass; Seedream 5 about 5% every turn.
- Text and charts: all three set a six-item diner menu, a vertical Chinese title and a bar chart with correct values and geometry. The only spelling error in the batch came from Seedream 5 ("Bottomloss Coffee").
- Grain: the Reddit complaint is real and still there. In a 300-pixel patch of plain sky, GPT Image 2.5 Flare carries roughly five times the high-frequency energy of Seedream 5 Pro and nine times that of Seedream 5. Whether you read that as texture or noise is the whole argument between the two camps; the 100% crops are below so you can decide.
- Speed: text-to-image, GPT Image 2.5 Flare ran 42–46 seconds, Seedream 5 Pro 38–66, Seedream 5 30–36. Reference edits are where they separate: GPT 43–55 seconds against 130–216 for Seedream 5 Pro and 57–191 for Seedream 5.
- Cost on this platform at 2K: GPT Image 2.5 70 credits either tier, Seedream 5 Pro 100, Seedream 5 40.
If your work is editing an image you already have, GPT Image 2.5 is now the model to reach for: cleaner on two of three edit metrics, four times faster than Seedream 5 Pro on edits, and cheaper than it. If your work is generating photoreal people and landscapes from text and you dislike grain, Seedream 5 Pro still produces the smoother frame. Seedream 5 is the budget draft tier, and the tests show where the budget went.
How we tested, and how to read the numbers
Three models, one prompt per test, 2K output, one generation each. Nothing was regenerated for quality; failed API calls were retried once and are listed as such. The prompts are printed under each test so you can rerun them.
- GPT Image 2.5 Flare ran through KIE.ai (the same route this site uses); Seedream 5 Pro and Seedream 5 (the Lite tier, sold here as Seedream 5) ran through EvoLink. GPT Image 2.5 Sunburst was added on the two tests where the tier could plausibly matter: sky grain and skin.
- The edit tests start from base images generated by a fourth model, Z Image Turbo, so no contestant is editing its own output.
- For local edits we measure change, not opinion: both images are resampled to 1024×1024 greyscale, a rectangle is drawn around the thing the prompt asked to change, and we count the pixels outside that rectangle whose value moved by more than 24/255. Lower is better. Inside the rectangle we report the mean change, which should be high.
- For grain we take a 300-pixel patch of plain sky from the same prompt and compute the mean absolute Laplacian, a standard measure of high-frequency energy. It cannot tell noise from fine cloud detail, so we show the patches next to the number.
- Speed is wall-clock from request to downloadable file on 9 September 2026, single runs. It includes upstream queueing and will move with load.
A rectangle is a blunt mask. A model that changed the sofa's shadow on the floor gets penalised for it even though the shadow should change. We accept that because every model is penalised the same way, and because the crops let you see what the number is counting.
CreateVision sells all three models by the credit and earns the same margin on each, so we have no reason to prefer one. All 38 generations and 4 base images were paid for at the normal rate; nothing was retouched.
What the public arena says before our tests
Before our own runs, the crowd-voted arena at arena.ai already ranked the two new OpenAI tiers first and second in both text-to-image and image editing. Seedream 5 Pro sits in the top ten of both; Seedream 5 is a long way behind. Snapshot of 8 September 2026:
| Model | Text-to-image | Image edit |
|---|---|---|
| GPT Image 2.5 Sunburst | #1 · 1421 (preliminary, 3,149 votes) | #1 · 1520 (preliminary, 6,704 votes) |
| GPT Image 2.5 Flare | #2 · 1399 (preliminary, 2,856 votes) | #2 · 1491 (preliminary, 5,676 votes) |
| GPT Image 2 (medium) | #3 · 1381 (78,731 votes) | #3 · 1461 (235,928 votes) |
| Seedream 5 Pro | #10 · 1257 (62,443 votes) | #8 · 1394 (179,966 votes) |
| Seedream 5 (Lite) | #37 · 1138 (109,182 votes) | #26 · 1294 (373,781 votes) |
The GPT Image 2.5 scores are marked preliminary with a few thousand votes each, against tens or hundreds of thousands for the Seedream tiers; expect them to settle. A 160-point gap in text-to-image is large by arena standards, but arena votes are aesthetic preferences on random prompts, not measurements. That is what the rest of this page is for.
Test 1 · Local edit: change the sofa, leave the room alone
The edit everyone on Reddit was waiting for. A living room with a green velvet sofa, a lamp, a painting, a plant and a coffee table; one instruction: make the sofa brown leather and change nothing else. The base image was generated by Z Image Turbo, not by any of the three.
Prompt: Change the green velvet sofa to a warm brown leather sofa. Keep everything else exactly as it is: the lamp, the painting, the plant, the coffee table, the wall, the lighting and the camera position must not change.
| Model | Pixels changed outside the edit region | Mean change inside the edit region (0–255) | Wall-clock |
|---|---|---|---|
| GPT Image 2.5 Flare | 1.1% | 13.33 | 50s |
| Seedream 5 Pro | 4.5% | 19.9 | 216s |
| Seedream 5 | 5.4% | 18.34 | 58s |
All three turned the sofa into brown leather, and to the eye all three kept the room. The numbers separate them. GPT Image 2.5 moved 1.1% of the pixels outside the sofa rectangle; Seedream 5 Pro moved 4.5%; Seedream 5 moved 5.4%. All three redrew the two-seater as a three-seat leather sofa in roughly the same footprint; the difference is in the margins, where both Seedream tiers also nudged the wall tone, the floor and the painting's colours.
Time: GPT Image 2.5 50 seconds; Seedream 5 Pro 216 seconds; Seedream 5 58 seconds.
Same visual result, but GPT Image 2.5 did it with a quarter of the collateral change and in a quarter of the time of Seedream 5 Pro.
Test 1b · Local edit: replace the text on a sign
The other classic edit: a bakery storefront whose sign reads MILLER & SONS BAKERY, and an instruction to change only the sign to HARBOR LANE BAKERY in the same lettering.
Prompt: Change only the text on the wooden sign above the door to read "HARBOR LANE BAKERY" in the same gold serif lettering. Keep the sign, the building, the bicycle, the chalkboard and the lighting exactly as they are.
| Model | Pixels changed outside the edit region | Mean change inside the edit region (0–255) | Wall-clock |
|---|---|---|---|
| GPT Image 2.5 Flare | 2% | 19.06 | 43s |
| Seedream 5 Pro | 0.5% | 16.65 | 140s |
| Seedream 5 | 13.1% | 24.78 | 68s |
All three replaced the text correctly in a matching gold serif. Here Seedream 5 Pro was the cleanest: 0.5% of pixels outside the sign changed, against 2.0% for GPT Image 2.5. Seedream 5 changed 13.1% — look at the bicycle, the chalkboard and the shadows, which all shifted slightly.
Time: GPT Image 2.5 43 seconds; Seedream 5 Pro 140 seconds; Seedream 5 68 seconds.
On a flat, text-only edit Seedream 5 Pro is as surgical as GPT Image 2.5, and slightly more so. The gap between the premium tiers and Seedream 5 is the consistent story across both edit tests.
Test 2 · Three edits in a row: does the room drift?
OpenAI's third claim is consistency across repeated edits. We fed each model its own previous output three times: brown sofa, then a sleeping grey cat on the left cushion, then evening light with the lamp switched on. Each step is scored against the step before it, so the number is drift, not distance from the original.
Prompt: Three consecutive edits, each fed the model’s own previous output. Step 1: "Change the green velvet sofa to a warm brown leather sofa. Keep everything else exactly as it is." Step 2: "Now add a sleeping grey cat curled up on the left cushion of the sofa. Change nothing else." Step 3: "Now change the time of day to evening: the lamp is switched on and the window light is dim blue dusk. Keep every object where it is."
| Model | Pixels changed outside the edit region | Mean change inside the edit region (0–255) | Wall-clock |
|---|---|---|---|
| GPT Image 2.5 Flare | 0.7% | 13.74 | 55s |
| Seedream 5 Pro | 6.1% | 25.92 | 152s |
| Seedream 5 | 5.2% | 15.92 | 57s |
GPT Image 2.5 held the room through all three turns: the sofa swap moved 0.7% of the outside pixels, the cat arrived on the left cushion with nothing else touched, and the evening pass changed the light everywhere — as asked — while every object stayed in place, including the cat.
Seedream 5 Pro also kept every object through all three turns. Its sofa swap moved 6.1% of the outside pixels (the wall and painting tones shifted), then its cat step was the cleanest edit in the whole batch at 0.1%; on the evening pass it invented a window on the left wall that was never there. Seedream 5 kept the objects too, at a steady 5.2% and 5.5% drift per turn, and turned the evening step into a saturated blue night rather than dusk. Time per turn: GPT 55/50/48 seconds, Seedream 5 Pro 152/130/135, Seedream 5 57/69/140.
Multi-turn consistency is not the GPT-only feature the launch post implies: all three held the room for three turns. What separates them is drift per turn — GPT under 1% on both measured steps, Seedream 5 Pro either 6.1% or 0.1% depending on the step, Seedream 5 about 5% every time — and that GPT did each turn in under a minute.
Test 3 · Two references: put this man's hands on that product
Reference fidelity with two inputs: a café portrait and a tea tin, both generated by Z Image Turbo, with the instruction to have the man hold the tin at chest height, label facing the camera. The test is whether the face and the label both survive.
Prompt: The man from the first image, exactly as he is, holding the tea tin from the second image with both hands at chest height, the label facing the camera and readable, same café window light, documentary style.
All three kept the man recognisable — glasses, beard, mustard sweater — and all three kept the label readable. The differences are in scale and staging: GPT Image 2.5 rendered the tin at a believable size and kept the café window behind him; Seedream 5 Pro was close, with a slightly darker table; Seedream 5 inflated the tin to the size of a lunchbox.
Time: GPT Image 2.5 51 seconds; Seedream 5 Pro 190 seconds; Seedream 5 191 seconds. Two-reference edits are the slowest thing Seedream does through this route.
Identity holds on all three. GPT Image 2.5 gets the physics of the composite right and does it in a quarter of the time.
Test 4 · Text: a six-item diner menu with prices
Small type is where image models still fail. A menu headed THE BLUEBIRD DINER, three sections, six items with prices, exact wording specified.
Prompt: A printed diner menu photographed straight on: heading 'THE BLUEBIRD DINER', then three sections — BREAKFAST with 'Buttermilk Pancakes 7.50 / Two-Egg Special 6.80', LUNCH with 'Patty Melt 9.20 / Cobb Salad 8.60', and DRINKS with 'Bottomless Coffee 2.50 / Fresh Lemonade 3.20'. Clean typeset layout on cream paper, every word and price legible and correctly spelled, no other text.
GPT Image 2.5: heading, six items and six prices all correct, set in a confident bold serif with a bluebird mark it invented. Seedream 5 Pro: all correct, in a smaller, quieter typeface presented as a card on a wall. Seedream 5: everything but one word — "Bottomless Coffee" came back as "Bottomloss Coffee".
Both premium tiers are reliable on small type. Seedream 5 is the only model in the batch that misspelled a word.
Test 4b · Text: a vertical Chinese title with an English subtitle
Seedream is a ByteDance model and Chinese typography is supposed to be its home ground. A bookstore poster with the vertical title 夜航书局 and the subtitle NIGHT VOYAGE BOOKS.
Prompt: Minimal poster for an independent Chinese bookstore: a large vertical Chinese title 「夜航书局」 running down the right side in a refined song-style serif, a small English subtitle 'NIGHT VOYAGE BOOKS' at the lower left, a single lit reading lamp on a dark wooden desk with a stack of clothbound books, deep indigo night palette with one warm pool of lamplight, no other text.
All three set all four characters correctly and the English subtitle correctly. GPT Image 2.5 built the richest scene (a moonlit window behind the desk) with a legible cream title. Seedream 5 Pro chose a dark blue title on a dark blue wall, correct but hard to read. Seedream 5 produced the most poster-like typography of the three, large and high-contrast.
No separation on correctness. On this prompt, Seedream 5 — the cheapest — made the best poster.
Test 5 · A bar chart with real numbers
A chart titled Quarterly Revenue 2025: four bars, values 12/18/15/24 printed above them, an axis from 0 to 30 in steps of 10, a footer line. Models usually get the digits right and the geometry wrong.
Prompt: A clean flat-design bar chart titled 'Quarterly Revenue 2025' with exactly four bars labelled Q1, Q2, Q3, Q4 and values 12, 18, 15, 24 printed above each bar, a y-axis from 0 to 30 in steps of 10, bars proportional to their values, muted blue on white, a small footer 'Source: internal data', no other text.
All three got everything right: values above the correct bars, bars proportional to their values, axis 0–30, footer intact. GPT Image 2.5 set the boldest, most legible chart; Seedream 5 Pro added light gridlines; Seedream 5 used a lighter blue. This is the first batch we have run where a chart passed on every model.
A draw. Chart geometry has stopped being a differentiator between these three.
Test 6 · The grain question: sky, grass and fur at 100%
The most-upvoted technical complaint in the GPT Image 2.5 launch threads was that the fine "checkerboard" texture of GPT Image 2 had not gone away, especially in clouds, grass and hair. One prompt covers all three: a golden retriever in tall grass under an overcast sky. Sunburst joins this test.
Prompt: Photograph of a golden retriever sitting in tall summer grass on a hillside, soft overcast sky filling the upper third of the frame, fine fur and individual grass blades in focus, shot on a 50mm lens, no text.
Below are 420-pixel crops at 100%, no resizing: the sky from the top of each frame, then the grass from the bottom. The number is the mean absolute Laplacian of a 300-pixel sky patch — high-frequency energy, where higher means more grain or more detail; the crops tell you which.
Sky patch energy: GPT Image 2.5 Flare 3.25, Sunburst 2.18, Seedream 5 Pro 0.70, Seedream 5 0.35. In the crops, both GPT tiers render cloud structure with a fine speckle on top of it; both Seedream tiers render an almost flat, softly graded sky. The complaint is accurate: GPT Image 2.5 still carries texture in flat areas, and Sunburst carries less of it than Flare.
Grass and fur: GPT resolves individual blades and hairs sharply; Seedream 5 Pro paints the grass softer and more uniform; Seedream 5 saturates it. Which is "better" depends on whether you are printing at A2 or posting at 1080 pixels — at social sizes the GPT grain disappears and the sharper blades win; at print sizes the Seedream frame is the one that does not need denoising.
Reddit was right about the grain and right that it is not fatal. If you shoot skies and skin for print, Seedream 5 Pro; if you shoot detail for screens, GPT Image 2.5.
Test 7 · Counting and placing: three apples, one pear, a fork above, a napkin below
A prompt with five countable, positionable constraints. Models that "understand" a prompt should get all five; models that pattern-match get three or four.
Prompt: Overhead photograph of a white square plate on a light wooden table: exactly three red apples on the left half of the plate, exactly one green pear on the right half, a single silver fork placed above the plate pointing right, and a folded blue napkin below the plate. Nothing else on the table, no text.
All three passed every constraint: three red apples on the left, one green pear on the right, the fork above the plate pointing right, the folded blue napkin below. Composition differed — GPT Image 2.5 filled the frame, Seedream 5 Pro left more table, Seedream 5 shot from slightly higher — but none dropped or duplicated an object.
A draw. Prompt adherence at this level of complexity is solved on all three.
Test 8 · Skin: a laughing woman in her late fifties, window light
The prompt asks for silver hair, freckles, visible skin texture, fine lines and no retouching. Sunburst joins again, because "sharper" and "oversharpened" are the same adjective said in two moods.
Prompt: Documentary portrait of a woman in her late 50s with silver hair and freckles, laughing, natural window light from the left, visible skin texture and fine lines, no retouching, 85mm lens, shallow depth of field, no text.
Below are 520-pixel crops at 100% around the eyes and cheek.
GPT Image 2.5 Flare renders pores, freckles and fine lines with a slight crispness at the edges; Sunburst goes further, with wrinkle detail that tips into the etched look some Reddit posters called oversharpened. Seedream 5 Pro renders the same age with softer, more photographic skin and the most natural laugh of the four. Seedream 5 is soft and lower in detail, and closed the eyes.
For beauty and lifestyle work, Seedream 5 Pro's skin is the one a retoucher would leave alone. GPT Image 2.5 is the one you would pick if the brief said "documentary".
Speed and cost, measured
All timings are wall-clock from API request to a downloadable file, measured on 9 September 2026 through the same routes this site uses. Credits are what each model costs here at 2K.
| Model | Text-to-image (2K) | Reference edit (2K) | Credits at 2K | Fastest / slowest run |
|---|---|---|---|---|
| GPT Image 2.5 Flare | 42–46 s, median 44 (6 runs) | 43–55 s (6 runs) | 70 | 42 s / 55 s |
| GPT Image 2.5 Sunburst | 43–44 s (2 runs) | Editing runs on Flare | 70 | 43 s / 44 s |
| Seedream 5 Pro | 38–66 s, median 56 (6 runs) | 130–216 s (6 runs) | 100 | 38 s / 216 s |
| Seedream 5 | 30–36 s, median 32 (6 runs) | 57–191 s (6 runs) | 40 | 30 s / 191 s |
Seedream 5 is the fastest text-to-image model of the three and the cheapest. The moment a reference image is attached, both Seedream tiers slow down by three to four times while GPT Image 2.5 barely changes. If your day is edits, that gap is the whole comparison.
Scorecard
One row per test. "Pass" means the prompt was fully satisfied on the first take; numbers are the measured metric where we have one.
| Test | GPT Image 2.5 | Seedream 5 Pro | Seedream 5 |
|---|---|---|---|
| Local edit — sofa (outside pixels changed) | 1.1% | 4.5% | 5.4% |
| Local edit — sign text (outside pixels changed) | 2.0% | 0.5% | 13.1% |
| Three-turn edit chain | Held all three turns | Held; drift 6.1% then 0.1%; invented a window | Held; drift 5.2% / 5.5%; night instead of dusk |
| Two-reference composite | Pass | Pass | Pass, tin oversized |
| Diner menu (heading + 6 items + 6 prices) | 13/13 | 13/13 | 12/13 |
| Chinese + English poster | Pass | Pass, low contrast | Pass, best poster |
| Bar chart geometry | Pass | Pass | Pass |
| Sky grain (lower is smoother) | 3.25 Flare · 2.18 Sunburst | 0.70 | 0.35 |
| Prompt adherence (5 constraints) | 5/5 | 5/5 | 5/5 |
| Skin | Detailed, slightly crisp | Most natural | Soft, eyes closed |
| Median text-to-image time | 44 s | 56 s | 32 s |
| Reference-edit time | 43–55 s | 130–216 s | 57–191 s |
| Credits at 2K | 70 | 100 | 40 |
Single runs. A second batch would move individual numbers; it would be surprising if it moved the pattern — premium tiers tied on text and adherence, GPT ahead on edits and speed, Seedream ahead on smooth skies and skin.
Which one should you pick?
The models are close enough on text, charts and adherence that those tests should not decide anything. Decide on the three things that actually separated them.
You edit more than you generate
GPT Image 2.5. Cleaner on the sofa edit, nearly as clean on the sign, unchanged through three turns, and 43–55 seconds per edit against two to three and a half minutes for Seedream 5 Pro. Reference images are free on both, but you will wait a lot less.
You generate photoreal people and landscapes for print
Seedream 5 Pro. The smoother sky, the more natural skin, no grain to denoise. It costs more per image here (100 vs 70 credits at 2K) and it is slower on edits, but for a single hero image that will be printed, the frame it hands you needs the least work.
You need volume and drafts
Seedream 5. Fastest text-to-image of the three and 40 credits. Accept a misspelling now and then and a heavier hand on edits; use it to explore, then send the winning direction to one of the other two.
You are choosing between Flare and Sunburst
Flare, unless the brief is skin or sky. Sunburst carried less grain in the sky patch and more wrinkle detail in the portrait — which is either the point or the problem. They cost the same here, so run both on your own prompt.
Frequently asked questions
Is GPT Image 2.5 better than Seedream 5 Pro?
On editing, yes, by our measurements: less collateral change on two of three edit tests and three to four times faster. On text-to-image quality they traded wins — GPT resolves more detail, Seedream 5 Pro renders smoother skies and skin. On text, charts and prompt adherence they tied.
Did GPT Image 2.5 fix the grain that Reddit complained about?
No. Our sky patch shows GPT Image 2.5 Flare carrying about five times the high-frequency energy of Seedream 5 Pro, and the 100% crops show a fine speckle over the clouds. Sunburst has less of it than Flare. It is invisible at social-media sizes and visible in print.
Is Seedream 5 (the Lite tier) worth using?
For drafts and volume, yes: fastest of the three and 40 credits at 2K. It produced the only spelling error in the batch, changed 13% of a storefront when asked to change only the sign, and inflated a product in a composite. Explore with it; deliver with the other two.
Why did you measure pixels instead of judging by eye?
Because "it kept the rest of the image" is exactly the kind of claim that eyes agree with too easily. All three sofa edits look fine at a glance; the count of changed pixels outside the sofa is what shows GPT Image 2.5 at 1.1% against 4.5% and 5.4%. The method and its limits are in the section above.
How much does each model cost here?
At 2K: GPT Image 2.5 70 credits on either tier, Seedream 5 Pro 100, Seedream 5 40. Reference images are free on all three, and every model here is one image per run. Failed generations are refunded.
What about Flare vs Sunburst?
Same price on this platform and upstream. In our two head-to-head tests Sunburst carried less sky grain and more skin detail. OpenAI positions it for production campaign work; reference editing runs on Flare on this platform because the Sunburst editing endpoint was not live at launch.
Can I rerun these tests?
Yes. Every prompt is printed under its test, all three models are on this site under one credit balance, and the raw results file with timings and metrics is linked in the sources.
Sources and raw data
Everything on this page was generated on 9 September 2026. The raw results, including per-run timings, upstream cost and the pixel metrics, are in the repository file listed here.
- OpenAI — Introducing ChatGPT Images 2.5 (openai.com/index/introducing-chatgpt-images-2-5), 8 September 2026: claims on fidelity, precision editing, multi-turn consistency and latency.
- arena.ai — Text-to-Image and Image Edit leaderboards, snapshot 8 September 2026.
- Reddit — r/OpenAI, r/ChatGPT, r/singularity, r/codex launch threads, 8–9 September 2026: the grain, editing and speed threads that set the test angles.
- CreateVision — scripts/research-gpt25-vs-seedream5.mjs and scripts/gpt25-vs-seedream5-results.json: prompts, timings, upstream cost and metrics for all 38 generations and 4 base images.
- Pricing: CreateVision model registry (2K: GPT Image 2.5 70, Seedream 5 Pro 100, Seedream 5 40 credits), read 9 September 2026.
