Higher Detail for Final Assets
Use Sunburst at medium or high quality when fine detail, layout accuracy, and consistency across edits matter most. It fits campaign creative, product imagery, and other visuals that require close review.
GPT Image 2.6 Sunburst
OpenAI’s quality-focused image model for detailed compositions and precise editing. Create campaign assets, preserve product and character details across revisions, and compare image models with one GPTProto API key and shared balance.
API Usage Examples
curl --request POST "https://gptproto.com/api/v3/openai/gpt-image-2.6-sunburst/text-to-image" \
--header "Authorization: Bearer $GPTPROTO_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
"n": null,
"quality": "auto",
"size": "auto",
"enable_sync_mode": false,
"response_format": "url"
}'GPT Image 2.6 Sunburst pricing
Start from the cost of a single sample and pick a testing budget. GPTProto rates are 5% below list price.
Auto
Low
Medium
High
XHigh
Max
Auto
1024x1024
1536x1024
1024x1536
2048x2048
2048x1152
3840x2160
2160x3840
| Scenario | OpenAI list | OpenRouter | GPTProto | You save / mo |
|---|---|---|---|---|
| Quick tests & prototypes100 images / mo | $1.35 | $1.43 | $1.29 | −$0.07≈ $0.81 / yr |
| Product & e-commerce photos1,000 images / mo | $13.54 | $14.29 | $12.87 | −$0.68≈ $8.13 / yr |
| Ad / marketing creatives2,500 images / mo | $33.86 | $35.72 | $32.17 | −$1.69≈ $20.32 / yr |
| Social media content10,000 images / mo | $135.44 | $142.89 | $128.67 | −$6.77≈ $81.26 / yr |
Save $0.00 / month
Annual savings ≈ $0.00 · pay as you go
Related Models
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GPT Image 2.6 SunburstCurrent
OpenAI · $7.6/M input · $28.5/M output
Model
Price: GPTProto
vs Official
vs OpenRouter
Resolution
Stability
GPT Image 2.6 SunburstCurrent
OpenAI
$7.60 / $28.50per 1M tokens
-5%
-10%
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GPT Image 2.6 Sunburst API
Turn demanding visual briefs into detailed images, then refine selected elements while keeping the rest of the composition consistent. Sunburst is designed for workflows where layout accuracy, edit precision, and final-image quality carry more weight than draft speed.
More Consistent Editing Rounds
Refine a character, product, or branded scene while asking the model to preserve the details that already work. Review every round against the approved source before requesting the next change.
Plan Dense Compositions
Set complexity to medium or high when the brief contains several subjects, text blocks, or spatial relationships. Complexity controls planning, while quality controls the detail in the rendered image.
Create SVGs and Animated GIFs
OpenAI documents SVG and GIF generation through the Image API. Use SVG for editable vector artwork and GIF for short loops, then confirm which parameters the GPTProto route exposes.
What Is the GPT Image 2.6 Sunburst API?
GPT Image 2.6 Sunburst is OpenAI’s quality-focused model for image generation and editing from text and image inputs. OpenAI positions it for detailed visual work and recommends it when a workflow has demanding requirements for detail, layout, or edit accuracy. At medium or high quality, Sunburst is designed to deliver higher-quality images and greater consistency across editing rounds.
The model separates scene planning from rendering detail. The complexity parameter controls how much planning happens before rendering. The quality parameter controls the fidelity of the final image. A focused color correction can use low complexity with a higher quality setting, while a poster with several objects and strict placement requirements may benefit from medium or high complexity.
| Capability | OpenAI Image API behavior |
|---|---|
| Model identifier | gpt-image-2.6-sunburst |
| Inputs and tasks | Text prompts for generation, plus source images and instructions for editing |
| Planning control | complexity supports low, medium, and high. The documented default is high. |
| Rendering quality | low, medium, high, xhigh, and max are available quality levels. |
| Guided editing | A transparent markup image can point to the requested edit area on the first input image. |
| Additional outputs | OpenAI documents SVG and animated GIF generation through the Image API. Confirm GPTProto route support before publishing these as platform features. |
Image Generation and Precise Editing Use Cases
Detailed campaign compositions. Use Sunburst for a hero image that combines a product, environmental details, deliberate negative space, and a clear visual hierarchy. State every required element and its approximate location. Review the result at the final placement size because a balanced full-size image can lose its hierarchy after a social or display-ad crop.
Controlled product revisions. Start with an approved product image and describe one requested change. Name the details that must remain unchanged, including the printed label, package proportions, camera angle, reflections, and shadow direction. Compare the edited output with the source at full resolution before beginning another editing round.
Recurring characters and branded scenes. Supply the strongest available reference and record the visual traits that define the subject. Keep clothing, proportions, color palette, and key accessories explicit. Treat each accepted result as the reference for the next revision so the workflow has a clear visual baseline.
GPT Image 2.6 Sunburst Prompt Guide
Build a detailed campaign key visual
Create a 4:5 luxury travel advertisement for a glass-roof sleeper train crossing a snow-covered valley at blue hour. Show the train in the lower third, warm cabin light, layered mountains, and a clear night sky. Reserve the upper-left area for a short headline. Keep the train architecture realistic and every window aligned. Leave the image free of text.
Check the train geometry, window alignment, lighting direction, and usable headline space. Correct structural problems before requesting style changes.
Revise one element and preserve the approved design
Change only the center gemstone from emerald green to deep sapphire blue. Preserve the ring shape, prong count, metal texture, camera angle, reflections, background, and shadow. Match the existing studio lighting and leave every other element unchanged.
When the route supports markup, circle the gemstone on a separate transparent overlay. Compare the prongs, reflections, and ring proportions against the approved source after the edit.
Generate a detailed looping GIF
Animate the illustrated clockwork bird turning its head toward the viewer, blinking once, and returning to its opening pose. Keep the body, brass feather pattern, perch, background, and camera fixed. Make the final frame transition smoothly into the first.
For endpoints that expose OpenAI’s GIF controls, set a modest frame count first and inspect subject consistency across the complete loop. Increase the frame count only when the movement needs more intermediate poses.
GPT Image 2.6 Sunburst vs GPT Image 2.6 Flare and Other Image Models
Sunburst and Flare share the GPT Image 2.6 generation and editing toolset, while their recommended roles differ. Choose Sunburst when detailed composition or precise editing determines whether the output is usable. Choose GPT Image 2.6 Flare when rapid drafts and response time matter most. Test both with the same prompt, reference images, dimensions, complexity, and quality wherever the route exposes matching controls.
| Model | Best starting point | What to measure |
|---|---|---|
| GPT Image 2.6 Sunburst | Detailed compositions, quality-focused final assets, and precise revisions | Small-detail retention, layout accuracy, edit boundaries, and consistency after two revision rounds |
| GPT Image 2.6 Flare | Fast concepts, frequent previews, and interactive iteration | Time to the first usable draft and the number of revisions required for approval |
| GPT Image 2.5 Sunburst | A direct baseline for teams already using the earlier precision tier | Run existing prompts at matching settings and compare detail, edit accuracy, latency, and token usage |
| Nano Banana 2.1 | High-volume generation, conversational edits, or workflows using several references | Identity retention, per-image spend, and the number of edits needed for an approved asset |
| Nano Banana Pro | Detailed mockups, localized visual copy, and complex design briefs | Text legibility, layout adherence, reference fidelity, and cost per approved image |
| Seedream 5.0 Pro | Product visuals and poster workflows that benefit from per-image billing and multiple references | Composition quality at the intended size, reference charges, and total cost after revisions |
OpenAI lists the same token rates for Sunburst and Flare, but equal per-token rates do not guarantee equal cost per approved image. Models can consume different output-token amounts at the same quality setting. Record usage for every test, then divide total spend by the number of images that pass review.
Compare GPT Image 2.6 Sunburst
Side-by-side price, speed and fit against the models people weigh it against.
FAQ
How do I get a GPT Image 2.6 Sunburst API key?
Create a GPTProto API key from your account dashboard. The same key and shared balance can access other supported models, which lets you compare Sunburst with Flare and other image APIs without managing separate provider balances. Use the model identifier displayed in GPTProto’s API example for the route you call.
How much does the GPT Image 2.6 Sunburst API cost?
Check the live pricing panel on this model page for GPTProto rates. OpenAI’s standard rates are $5 per million text input tokens, $8 per million image input tokens, and $30 per million image output tokens. Cached text and image input rates are $1.25 and $2 per million tokens. Your cost per image depends on token usage, quality, dimensions, and repeat renders.
What changed from GPT Image 2.5 Sunburst to GPT Image 2.6 Sunburst?
OpenAI positions the 2.6 model for detailed visual work and highlights improved editing consistency, detail preservation, markup-guided edits, SVG generation, and animated GIF generation across the Images 2.6 release. Test your existing 2.5 prompts at matching settings and compare the exact details that determine approval in your workflow.
Can the GPT Image 2.6 Sunburst API generate animated GIFs?
OpenAI’s Image API supports native GIF generation with output_format="gif". Its documented controls include 2–64 frames and 20–2,000 milliseconds per frame, subject to the request pixel budget. GIF is a generation output. Confirm that the GPTProto route exposes these fields before implementing the workflow.
Should I always use high complexity with Sunburst?
Use the lowest complexity that satisfies the brief. OpenAI recommends low complexity for focused edits and medium or high for scenes with several elements or constraints. Higher complexity can increase latency and may introduce changes you did not request, so compare settings on a representative sample.
Does Sunburst support markup-guided editing and SVG output?
OpenAI documents both capabilities for GPT Image 2.6 through the Image API. Markup uses a separate transparent annotation image to guide an edit on the first raster input. SVG is available for new generations and produces static vector content. Confirm parameter support on the GPTProto route before adding either option to your application.
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