AIREITEROpenAI says people create about 4 billion images per week across ChatGPT, Codex and the API, then shipped Images 2.6 on November 4, 2026 with faster generation and edits that keep characters and brand details intact. The catch from day-one testers is artifact reports and uncertainty about which variant serves you in ChatGPT, so the practical setup is Flare for drafts and Sunburst for finals. Official 2.6 API pricing was not yet listed at publication time.
Verdict: Flare for speed, Sunburst for finals, GIFs on probation
If you want the decision: use GPT-Image-2.6 Flare when turnaround matters and GPT-Image-2.6 Sunburst when consistency matters. OpenAI positions Flare as the fast option that can hit about 6 seconds at low quality, and Sunburst as the precision option for multi-round edits. Both are available in the API, while ChatGPT and Codex serve Images 2.6 across all tiers on web, desktop and mobile.
OpenAI publishes no GIF duration, frame-rate or size limits and early quality reports are mixed. Build on stills and markup first, run GIFs as a separate experiment.
"Update after 20min of playing with gpt-image-2.6-flare. I'm gonna be rolling back to 2.5-flare. I've found 2.6-flare to have too many artifacts (transparency grids baked in, broken lines) as well as the designs being overly simplistic." — @pwnies on X
One tester, 20 minutes in, not a benchmark, but it names the artifact failure mode OpenAI doesn't quantify.
What shipped on November 4
Images 2.6 went live globally on November 4, 2026 in ChatGPT, Codex and the API, according to OpenAI's announcement. ChatGPT availability covers all subscription tiers, including free. The API adds two model variants:
GPT-Image-2.6 FlareGPT-Image-2.6 Sunburst
OpenAI claims 50% faster generation than before. The only absolute latency number on the announcement page is Flare at low quality: as little as six seconds. Sunburst gets no latency number.
The release also brings GIF creation from a prompt or sketch, image markup in the API, SVG export, and a new complexity parameter that controls planning separately from image quality. OpenAI cites early partners including OpenArt for sprite-sheet GIF examples, Town for animated assistant characters, Picsart for character consistency, and Figma Weave for reusable creative workflows.
Flare vs Sunburst, decoded
OpenAI's announcement does not describe a ChatGPT variant selector, which is why API users should set the model explicitly.
Flare is the iteration engine. Use it for social graphics, poster concepts, product variations and quick edit rounds where you will throw away half the outputs. OpenAI specifically calls out better layouts for posters and product imagery on Flare, not just raw speed.
Sunburst is the consistency engine. Use it for brand assets, product shots that must match across a campaign, character sheets, and any scene with many constraints. OpenAI frames it as higher quality and greater consistency across editing rounds.
| Task | Pick | Why |
|---|---|---|
| Daily social drafts, 10+ variations | Flare | Lowest latency, layout improvements, fast to iterate |
| Logo, product or character must stay identical | Sunburst | Positioned for precision and cross-edit continuity |
| One clear recolor or text swap | Either | 10-edit 2.5 test showed 6 of 6 single-change edits worked on both |
| Remove or add an object from notes on the photo | Sunburst + written prompt | Same test: only Sunburst completed the full remove-and-add in 1 of 2 runs |
| Fast everyday images | Flare | OpenAI calls Flare its fastest image model |
Until OpenAI documents routing: if you call the API, set the model explicitly. If you use ChatGPT, assume you cannot control which variant serves you, and re-roll with a more constrained prompt plus a reference image when identity drifts.
GIFs from a single prompt: the 6-frame pattern that works
Images 2.6 can animate a mascot, turn a product shot into a loop, or turn a sketch into a character, per OpenAI. The clearest recipe shown in the cited examples is a six-frame sprite sheet from OpenArt examples:
- Exactly 6 sequential frames
- 3-column by 2-row grid, left-to-right then top-to-bottom
- Identical dimensions per panel, fixed camera
- Same character, outfit and background across frames
- Motion progresses incrementally, frame 6 transitions back toward frame 1 for a seamless loop
- No captions, words, numbers, logos, speech bubbles, labels, borders or gutters
Copy that structure into your prompt when you want a loopable asset for games or pre-video storyboards. Example prompt skeleton: "6-frame animation sprite sheet, 3x2 grid, same chibi office worker, same desk and monitor, front three-quarter camera, frame 1 neutral, frames 2-5 reaction progressing, frame 6 eases back to neutral, no text, no borders."
What OpenAI does not publish: output GIF duration, dimensions, frame rate, file size, whether the model returns a .gif directly or a sprite sheet you assemble yourself, and any temporal-consistency score. Plan to assemble the sheet into a GIF yourself unless the API response confirms direct GIF output. Treat those limits as unconfirmed until the image generation guide adds them.
Markup, SVG and complexity: three API controls worth using
One of the API changes documented in the pre-release spec, per the spec analysis, is markup. It is the most actionable part of 2.6 for developers.
Markup brings ChatGPT-style annotations to POST /v1/images/edits. Send a transparent PNG overlaid on the first input image to show where and what to change — circle a badge and write "change to star," draw an arrow where an apple should go. Rules from the spec:
- Transparent PNG, same dimensions as the first image after orientation, must contain transparent pixels
- Reference by file ID, HTTPS URL, base64 data URL, or multipart upload
- Cannot be combined with
maskin the same request - Applies to the first image when you pass up to 16 reference images
A mask says where the model may paint. Markup can say where plus what, with arrows, boxes and notes in one file. OmniaKey's pre-release test is a warning: written instructions were followed in 6 of 6 edits, but drawn-on notes alone worked in only 1 of 4. Always repeat the annotation in the text prompt.
SVG export is useful for logos, icons and print assets, but test text paths and fine lines because the announcement does not specify fidelity or element limits.
Complexity splits planning from pixels. Low complexity for quick edits, medium or high for scenes with many elements or constraints, per OpenAI. Quality still controls visual detail.
If you are building an editor UI, add a drawable annotation layer now and pass it as markup. Keep model IDs configurable so the 2.5 to 2.6 switch is a config change plus a same-prompt regression check on small text, hands, dense textures and multi-step edits.
What early testers are hitting
Launch-day signal is thin. Three failure modes keep showing up in anecdotal reports.
| Failure mode | Evidence | What to do |
|---|---|---|
| Flare artifacts: transparency grids, broken lines, simplified details | @pwnies 20-min test, rolled back to 2.5-Flare | Use Flare for drafts only; switch to Sunburst for finals |
| Prompt drift: ignores instructions, adds unrequested objects, waxy faces | u/EducationalPotato127: "follows prompts and context a lot worse than before" on r/ChatGPT; same thread reports grain shifts and changed likeness | Constrain prompts, add reference images, re-run same-prompt checks |
| Style limits: noise improved, but pixel-art remains weak | @Angaisb_: "noise issues seem much better, still can't do pixel art" | Keep a 2.5 evaluation set; re-run on both 2.6 variants before migrating |
What it costs and how to call it
OpenAI's announcement links out to pricing without printing numbers. The OpenAI pricing page lists no separate 2.6 row as of Nov 5; treat the 2.5 token rates below as a provisional budgeting reference only, not an official 2.6 price: $8 per 1M image input tokens, $30 per 1M image output tokens, $5 per 1M text input tokens, with batch halving image rates, per OmniaKey's pricing check.
Calls go through /v1/images/edits for markup workflows and the image generation endpoint for text-to-image, with up to 16 input images (PNG, WebP or JPG under 50 MB each) and prompts up to 32,000 characters, per the spec analysis.
FAQ
Can I pick Flare or Sunburst inside ChatGPT?
No documented selector exists. Set the model explicitly only via the API. In ChatGPT, constrain the prompt and add reference images when identity drifts.
Does markup replace the text prompt?
No. Markup guides the edit visually, but testing showed drawn notes alone rarely suffice. Restate the change in the prompt and keep markup and mask mutually exclusive.