OpenAI GPT Image 2.5: Flare vs Sunburst Tutorial
Compare OpenAI's GPT Image 2.5 Flare and Sunburst models for fast everyday generation vs precise editing, plus tutorial steps, limitations, and official links.
On September 8, 2026, OpenAI released ChatGPT Images 2.5, with GPT-Image-2.5 Flare and GPT-Image-2.5 Sunburst available in the API. This guide organizes product positioning, model differences, basic usage, and independent access notes from official launch material and developer documentation.
The term “most capable” reflects OpenAI’s official positioning of Sunburst as its most capable image generation and editing model, not a universal benchmark result. The article separates official OpenAI sources from the independent nanobananapro.hk model page.
What Is GPT Image 2.5?
GPT Image 2.5 is the API image generation model family following OpenAI’s ChatGPT Images 2.5 release. It includes GPT-Image-2.5 Flare and GPT-Image-2.5 Sunburst. Both models accept text and image inputs and output images, with low, medium, high, xhigh, max, and auto quality settings.
OpenAI positions Flare as the fastest high-quality everyday image generation model and the default choice for most applications. Sunburst is positioned as the most capable image generation and editing model for workflows where editing precision matters most. Note that nanobananapro.hk is an independent model page, not the official OpenAI website.
GPT Image 2.5 model comparison
The GPT Image 2.5 family in the OpenAI API includes Flare and Sunburst. Both accept text and image inputs and produce images, but they differ in editing precision, speed orientation, and practical fit.
| Comparison dimension | GPT-Image-2.5 Flare | GPT-Image-2.5 Sunburst |
|---|---|---|
| Positioning | OpenAI’s fastest high-quality everyday image generation model and the default choice for most applications. | OpenAI’s most capable image generation and editing model, aimed at workflows where editing precision matters most. |
| Speed and latency | Tuned for everyday image generation speed, with official positioning as the faster default option. | Prioritizes editing precision, so generation can take longer than Flare in some workflows. |
| Editing ability | Provides high-quality generation for rapid output and routine image tasks without deep edit iteration. | Fits precise edits, multi-turn consistency, and stronger preservation of the reference subject. |
| Input and output | Accepts text and image prompts, returning generated image content for general-purpose tasks. | Processes text-prompted and reference-image tasks, with output focused on edited or generated image results. |
| Quality settings | GPT-Image-2.5 Flare supports low, medium, high, xhigh, max, and auto quality settings. | GPT-Image-2.5 Sunburst offers the same low, medium, high, xhigh, max, and auto quality choices. |
Key upgrades in Images 2.5
Sharper details
Official launch material says Images 2.5 improves detail clarity, including texture, edges, and complex structures. Product shots, people, and scene generation can show stronger visual separation and clearer hierarchy.
More natural lighting and materials
The release emphasizes natural light and material rendering, making reflections, skin, fabric, and metal feel more realistic. For tasks that need visual believability, this change matters more than a simple sharpness boost.
More precise edits and subject preservation
Images 2.5 pays more attention to reference-subject consistency during editing, so multi-turn changes are more likely to retain key features. Sunburst is especially suited to precision editing, although generation may take longer.
Lower generation latency
OpenAI states that Images 2.5 reduces image generation latency by up to 50% compared with Images 2.0. This is an official comparison, not an independent speed benchmark measured by this site.
How to use GPT Image 2.5
This five-step API workflow covers model selection, prompt preparation, quality settings, and iteration. Flare fits most everyday generation tasks, while Sunburst is better for precision editing. If you do not use the API, you can still review the independent model page.
1. Confirm your access path
You can call the models through the official OpenAI API documentation, or open the GPT Image 2.5 model page on nanobananapro.hk for entry information. The latter is an independent page, not the OpenAI website.
- Official documentation explains the API models.
- nanobananapro.hk is only an independent model page.
2. Choose Flare or Sunburst
For most high-quality everyday image generation, Flare can be the default choice. If the task involves precise edits, multi-round changes, or reference-subject consistency, evaluate whether Sunburst fits better.
- Use Flare first for everyday generation.
- Choose Sunburst when edit precision matters more.
3. Prepare the text prompt
Describe the subject, scene, lighting, composition, style, and constraints. If you include an image input, explain how to use the reference, such as keeping the subject’s appearance while changing the background.
- Clearly describe subject, environment, and style.
- Avoid vague or contradictory instructions.
4. Set quality and parameters
The models support low, medium, high, xhigh, max, and auto quality settings. Higher quality tiers may affect image output and waiting time, so match the setting to the task budget.
- Quality options include auto and other tiers.
- Adjust based on output needs and latency budget.
5. Generate and iterate
After the first result, refine the prompt or change models based on detail, lighting, composition, and edit consistency. OpenAI lists multi-turn editing consistency as an improvement area for Images 2.5.
- Adjust prompts and parameters after each result.
- Switch to Sunburst if fine edits are needed.
Prompt guide and usage tips
The more specific the prompt, the easier it is for GPT Image 2.5 to match the intended image. The template below separates subject, scene, lighting, style, and constraints for product shots, portraits, and scene illustrations.
Subject: [Describe the subject and key features, such as identity, clothing, expression, or object material]
Scene: [Describe the environment, space, background elements, and composition]
Lighting: [Describe light direction, intensity, color temperature, and shadows]
Style: [Examples: realistic photography, 3D render, illustration, product design]
Edit requirements: [Whether to preserve a reference subject, change a local area, or unify color]
Constraints: [Elements, text, distortion, or style shifts to avoid]
Example: A young woman stands by a window wearing a beige linen jacket, with natural light from the left, shallow depth of field, realistic photography style, preserving the facial features from the reference image, replacing the background with a clean interior, and no extra text.
- Separate subject, scene, lighting, style, and constraints instead of packing multiple goals into one long sentence.
- For editing tasks, specify which features of the reference image to keep rather than saying only “make it similar.”
- Check whether Flare is sufficient before switching to Sunburst only when edit precision becomes a problem.
- Quality tiers affect waiting time, so start with auto or a mid tier to validate direction instead of always using the highest setting.
Recommended use cases
These suggestions follow OpenAI’s official positioning and do not guarantee specific generation results. Flare is a better fit for fast, high-quality output, while Sunburst suits precision-edit workflows.
| Scenario | Recommended model | Reason |
|---|---|---|
| Rapid ecommerce product images | Flare | Daily product displays and quick scene comps fit Flare because OpenAI positions it as the faster high-quality default model. |
| Marketing poster exploration | Flare | Marketing exploration requires comparing several visual directions quickly, and Flare’s lower-latency positioning supports larger batch tests. |
| Portraits that must preserve reference features | Sunburst | Portrait editing needs consistent facial, hair, or clothing features, matching Sunburst’s subject-preservation and edit-consistency focus. |
| Complex multi-turn image editing | Sunburst | Repeated edits can accumulate drift, so workflows that need stronger edit precision and consistency should evaluate Sunburst first. |
| Unsure where to start | Start with Flare | Flare is the default for most applications, so validate the visual direction quickly before deciding whether Sunburst is needed for harder edits. |
Boundaries and limitations
Images 2.5 brings several upgrades, but it cannot guarantee perfect results for every input. The following boundaries help set realistic expectations before generation.
- Official safety and provenance measures can reduce risk, but they do not eliminate all misuse, misleading generation, or forgery risks.
- The official 50% latency reduction is a comparison with Images 2.0; it is not an independent speed benchmark for every environment.
- Sunburst offers higher edit precision but may take longer, so it should not be the default switch for every task.
- This article does not provide pricing, resolution, quota, regional availability, or exact rollout dates because those details were not included in the source materials.
- nanobananapro.hk is an independent access page rather than the OpenAI website, so readers should verify current availability and model status separately.
FAQ
What is the relationship between GPT Image 2.5 and ChatGPT Images 2.5?
ChatGPT Images 2.5 is the product name OpenAI announced on September 8, 2026. In the API, the corresponding model names are GPT-Image-2.5 Flare and GPT-Image-2.5 Sunburst.
How should I choose between Flare and Sunburst?
For most everyday high-quality image generation, Flare can be the default choice. If editing precision, reference-subject preservation, and multi-turn consistency matter most, evaluate Sunburst first.
What does “most capable” in the title mean?
It refers to OpenAI’s official positioning of Sunburst as its most capable image generation and editing model, not a general benchmark result across all image generation systems.
Is nanobananapro.hk an official OpenAI website?
No. nanobananapro.hk is an independent GPT Image 2.5 model page. The OpenAI links in this article are official sources, and the two should be understood separately.
Can I guarantee that generated results are completely safe?
No. Official safety and provenance measures reduce risk, but any image generation system can still produce inaccurate, inappropriate, or unexpected output.
Conclusion
GPT Image 2.5 offers two practical directions for image work: Flare for fast, high-quality default generation and Sunburst for workflows that value edit precision. Understanding this split helps more than remembering a single model name.
If you arrive from an English search, you can verify model capabilities through the official OpenAI sources or visit the independent GPT Image 2.5 model page at nanobananapro.hk. That page is not the OpenAI website and does not replace official documentation.
If you want to explore or try the GPT-image2 model page, use the link below to continue.
Official sources
This article draws on the following OpenAI announcement and API documentation so you can verify model capabilities and calling methods directly.