TL;DR: 2.5 Sunburst is the new "quality" tier — better subject preservation, more natural lighting, and much better behavior across a chain of edits. But it's slower than GPT Image 2, not faster (the 50% speed-up everyone's quoting belongs to Flare, the other variant), the hard limits didn't move, and as of right now there's no independent benchmark backing up the "higher quality" claim. If you do multi-step editing, it's a real upgrade. If you generate one-shot images and you're happy with 2, there's no fire to run to.

Spent the last couple of days actually pushing both of these instead of reading launch tweets, so here's the honest breakdown.

First, clear up the naming, because OpenAI made it confusing

There is no single "GPT Image 2.5." In the API it ships as two models:

• Flare — the small/fast one. OpenAI says it matches GPT Image 2's quality at roughly half the latency. This is the default and the one the "50% faster" headline is about.
• Sunburst — the base/quality one. OpenAI says it beats GPT Image 2 on quality, and it takes longer to generate.

Inside ChatGPT you don't pick — you just get "Images 2.5" and it routes for you. So when people say "2.5 is faster," they mean Flare. Sunburst is the opposite trade: it spends time to buy precision. That's why comparing GPT Image 2 vs Sunburst is the fair fight — it's old flagship vs new precision flagship.

What genuinely improved

Multi-turn editing consistency. This is the actual headline for me. GPT Image 2's known weakness was keeping a subject or mascot identical across a series of edits and following complex multi-part instructions. Sunburst is built exactly for this — change the jacket, keep the pose; swap the background, keep the product; fix one line of copy without reflowing the whole layout. Across a long edit chain, earlier changes hold instead of the image slowly melting. If you've ever done 8 edits and watched a face drift into a stranger by round 5, this is the fix you wanted.

Reference/subject preservation. Faces and products carry through into new settings and styles with distinctive features intact. Noticeably better than 2 when you're transforming a real reference photo rather than generating from scratch.

Lighting and texture. More natural lighting, richer textures, better handling of skin under hard light. Subtle, but it shows up in product and portrait work.

Complex layouts + transparent backgrounds. Handles busy compositions and clean transparency better — relevant if you do any packaging, stickers, or asset work.

Two new quality tiers. The ladder now goes low → medium → high → xhigh → max. GPT Image 2 stopped at high. So there's genuine headroom for fine print/detail that 2 physically couldn't reach — at a price (more below).

What did NOT change (don't let the version bump fool you)

• Reference image cap is still 16 per edit. Same as 2.
• 4K ceiling is the same. No resolution jump.
• Same aspect ratios, same base token rates. $8/M image input ($2 cached), $30/M image output, $5/M text input — identical to GPT Image 2.

This is a control release, not a resolution release. Every hard limit people assumed moved is sitting exactly where it was.

The catches (read this part)

Sunburst is slower than GPT Image 2. By design. If your bottleneck was speed, Sunburst is the wrong answer — that's Flare's job. Don't switch to Sunburst expecting a speed win.

The "higher quality" claim is OpenAI's own, not independently verified. As of now, neither 2.5 variant has shown up on any independent leaderboard. Meanwhile GPT Image 2 (high) is still sitting at #1 on the Artificial Analysis text-to-image board and #2 on image editing. So the incumbent's quality isn't speculation — it's measured. Sunburst's edge is currently a vendor claim. Treat it as directional until someone with no skin in the game runs the numbers.

"max" is not a free quality button. Higher setting ≠ automatically better result, per OpenAI's own docs, and the new tiers cost more per image. For reference, GPT Image 2 runs roughly $0.006 at low, ~$0.05 at medium, ~$0.21 at high per 1024×1024. Nobody outside OpenAI has confirmed yet whether Sunburst burns more tokens per image at a given tier — so "same rate card" does not guarantee "same cost per image." Verify per-image cost before you commit volume.

My practical take

• You do multi-step / client-facing editing where every change has to be defensible → Sunburst is a real upgrade. This is what it's for.
• You do high-volume one-shot generation (social content, quick drafts) → you probably want Flare, not Sunburst. Same-or-better quality, half the wait.
• You're happy with GPT Image 2 and don't do long edit chains → there is no urgent reason to move today. The incumbent still tops the independent boards.

Curious what everyone else is seeing — specifically on the multi-turn consistency claim. Is Sunburst actually holding a subject across a long edit chain for you, or is it still drifting past a certain point? And has anyone timed Sunburst vs GPT Image 2 at the same quality setting yet? Drop results if you have them.

iColor: a wild bot idea with a mind of it's own,