| Operation — find the task you are actually doing | GPT Image 2.5 Flare — observed result and limit | Sunburst — observed result and limit | How to read the result — decision guidance |
|---|---|---|---|
| Increase quality while retaining a product composition | In a matched product sequence, framing and the case’s apparent shape or size changed between quality settings. | The case, camera angle and reflection stayed consistent across that sequence. | Compare composition before judging detail. This supports testing Sunburst for this operation, not declaring it better at every edit. |
| Continue a portrait through successive edits | Faces remained recognizable; an item omitted from the preservation instructions disappeared. | Faces also remained recognizable; the omitted item disappeared here too. | This sequence did not clearly separate the variants. Check retained objects as well as faces. |
| Choose a model for photographic appearance | No matched Flare-versus-Sunburst photography result is established by these records. | A photographic comparison produced conflicting preferences; model labels and the full prompt were supplied later. | There is no basis here for choosing either variant on photographic taste alone. Establish the prompt and image labels before interpreting preferences. |
| Respond to a timeout during long-prompt generation | Timeouts occurred in a mobile Firefox workflow. | The same workflow also produced Sunburst timeouts, and some results arrived afterward. | An interface timeout does not by itself establish that generation stopped. These records do not identify a more reliable variant. |
| Repair repetitive texture or swirly detail | No basis for assigning the unlabelled texture failures specifically to Flare. | No basis for assigning those failures specifically to Sunburst. | Treat this as an unresolved texture problem, not evidence for a variant switch. Fresh generations and edited images both showed problems; a new conversation was not a dependable cure. |
| Fix the wrong content or wrong deliverable | No variant-specific result establishes a cure for questions appearing on a poster or sharpening without a dimension increase. | No variant-specific result establishes a cure for either failure. | Check the requested content and actual output dimensions. Better-looking text or sharper pixels can still leave the task unfinished. |
How to read the table
The model columns describe bounded observations. “No basis” means the available records cannot support that comparison; it does not mean the model cannot perform the task. The final column contains editorial recommendations inferred from those observations, not additional test results.
A decision order for GPT Image 2.5 Flare
- Identify the operation and the variant. Decide whether you are increasing quality, continuing an edit, judging photographic appearance or investigating a failure. If the variant is unconfirmed, stop at “variant comparison unresolved.”
- Check what counts as completion. For an edit, inspect the requested change and the details that should remain. For a poster, check that the intended copy became the design. For a larger-image request, inspect the dimensions. An attractive result that fails the requested deliverable does not pass.
- Use the matching comparison. A composition change during a quality increase gives a reason to test Sunburst on that operation. A portrait chain in which both variants preserved faces and lost the same omitted object gives no demonstrated winner. Photography preferences without a complete brief and clear labels cannot settle the choice.
- End with a bounded decision. Keep Flare if it meets the brief and preservation requirements. Test Sunburst when the relevant comparison gives a reason to do so, then choose it only if it resolves the actual failure. If the variant, outcome or comparison remains unclear, record “not enough evidence to choose.”
This order is an editorial decision aid. It does not establish a universal model ranking.
When the variants cannot be separated
A recognizable face is not a complete preservation check. Both variants retained faces in the portrait sequence while losing an omitted item, so inspect objects and composition before calling either result successful.
Photographic taste and instruction-following can also disagree. Establish what the prompt requested, identify which image belongs to which model, and assess compliance separately from preference. The available photographic comparison does not establish a Flare-versus-Sunburst winner.
For the recorded timeout pattern, leave the result marked unresolved until you know whether an image arrived. Several waiting generations visibly cleared together, yet some results appeared later. The visible failure and the eventual outcome were not always the same.
Texture failures require another distinction: was the defect already present in the fresh image, or did it emerge during editing? Both situations occurred. Neither that distinction nor restarting the conversation establishes which variant would solve the problem.
Claims these records do not establish
These records do not establish that Sunburst always edits better than Flare, that increasing quality preserves an existing composition, or that a timeout proves generation failed. They also do not establish that opening a new conversation reliably removes texture defects, that a photographic preference identifies better prompt compliance, or that a sharper image has larger dimensions.
There is no supported numerical cutoff for switching variants here. The records cover different tasks and environments rather than a controlled workload with a common denominator. Assigning a success percentage, a maximum safe edit count or a universal waiting-time threshold would add numbers the evidence does not supply.